WO2014009418A1 - TnT, NTproBNP, sFlt-1 for CURB65 IN PNEUMONIA - Google Patents

TnT, NTproBNP, sFlt-1 for CURB65 IN PNEUMONIA Download PDF

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Publication number
WO2014009418A1
WO2014009418A1 PCT/EP2013/064591 EP2013064591W WO2014009418A1 WO 2014009418 A1 WO2014009418 A1 WO 2014009418A1 EP 2013064591 W EP2013064591 W EP 2013064591W WO 2014009418 A1 WO2014009418 A1 WO 2014009418A1
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Prior art keywords
subject
risk
score
amount
pneumonia
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PCT/EP2013/064591
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French (fr)
Inventor
Georg Hess
Andreas Gallusser
Andrea Horsch
Volker Klemt
Dietmar Zdunek
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Roche Diagnostics Gmbh
F. Hoffmann-La Roche Ag
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Publication of WO2014009418A1 publication Critical patent/WO2014009418A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/46—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans from vertebrates
    • G01N2333/47—Assays involving proteins of known structure or function as defined in the subgroups
    • G01N2333/4701—Details
    • G01N2333/4712—Muscle proteins, e.g. myosin, actin, protein
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/575—Hormones
    • G01N2333/58—Atrial natriuretic factor complex; Atriopeptin; Atrial natriuretic peptide [ANP]; Brain natriuretic peptide [BNP, proBNP]; Cardionatrin; Cardiodilatin
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
    • G01N2333/71—Assays involving receptors, cell surface antigens or cell surface determinants for growth factors; for growth regulators
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/50—Determining the risk of developing a disease

Definitions

  • the present invention relates to a method for optimizing a risk assessment of pneumonia based on a clinical prediction rule for classifying subjects with pneumonia.
  • the present invention also relates to a system for performing an optimized risk assessment of pneumo- nia as disclosed herein and to reagents and kits used in performing the methods disclosed herein.
  • the method is based on the determination of the amount of a least one marker selected from the group consisting of a cardiac Troponin, a brain natriuretic peptide, and sFlt-1, and on the comparison of the determined amount(s) to a reference amount. Further envisaged are kits and devices adapted to carry out the said method.
  • Community acquired pneumonia is the leading cause of death from infections in developed countries. Costs associated with pneumonia are related to hospital care.
  • the CURB65 Score reflects the following clinical features: confusion, blood urea above 19 mg per dl, respiratory rate above 30 breaths per minute, systolic blood pressure bellow 90 mmHg and/or diastolic blood pressure below 60 mmHg and age above 65 years. Each of these components receives 1 point and total points reflect mortality as follows: 0 point 0,6 %, 1 point 2,7 %, 2 points 6,8 %, 3 points 14,0 % and 4 or 5 points 27,8 %. Depending on the score obtained hospitalization, hospitalization with ICU admission or discharge is recommended.
  • the CURB65 score in principle reflects: general risk factors and comorbidities (65), cardiovascular responses (blood pressure, confusion), impairment of kidney function (urea) and extent of lung involvement (respiratory rate).
  • NT-proBNP has been shown to be a powerful predictor of short term mortality in pneumonia patients, however, this has not been related to the CURB65 score (Nowak A. et al, Chest, ahead of publication).
  • the technical problem underlying the present invention can be seen as the provision of means and methods for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia.
  • the technical problem is solved by the embodiments characterized in the claims and herein below.
  • the present invention relates to a method for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia, comprising the steps of
  • step b comparing the amount as determined in step a) with a reference amount, thereby optimizing the risk assessment based on the clinical prediction rule for classifying subjects with pneumonia.
  • the method of the present invention preferably, is an in vitro method. Moreover, it may comprise steps in addition to those explicitly mentioned above. For example, further steps may relate to sample pre-treatments or evaluation of the results obtained by the method.
  • the method may be carried out manually or assisted by automation.
  • step (a) and/or (b) may in total or in part be assisted by automation, e.g., by a suitable robotic and sensory equipment for the determination in step (a) or a computer-implemented comparison and/or diagnosis based on said comparison in step (b).
  • the present invention also preferably relates to a system for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia, comprising
  • an analyzer unit configured to contact, in vitro, a portion of a sample from a subject suffering from pneumonia with a ligand comprising specific binding affinity for at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1,
  • an analyzer unit configured to detect a signal from the portion of the sample from the subject contacted with the ligand
  • a non-transient machine readable media including a plurality of instruction executable by a the processor, the instructions, when executed calculate an amount of the at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1, and compare the amount of the at least one marker with a reference amount, thereby optimizing the risk assessment based on the clinical prediction rule for classifying subjects with pneumonia.
  • the amount at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 shall be determined.
  • the amount(s) of one, two, or three markers shall be determined and shall be compared to the respective reference amount(s).
  • Preferred combinations of markers are as follows:
  • a brain natriuretic peptide and a cardiac Troponin a brain natriuretic peptide and a cardiac Troponin
  • sFlt-1 a brain natriuretic peptide
  • cardiac Troponin a cardiac Troponin
  • a risk assessment which is based on a clinical prediction rule for classifying subjects with pneumonia shall be optimized.
  • an assessment is usually not intended to be correct for 100% of the subjects to be diagnosed.
  • the term requires that the assessment is correct for a statistically significant portion of the subjects (e.g. a cohort in a cohort study). Whether a portion is statistically significant can be determined without fur- ther ado by the person skilled in the art using various well known statistic evaluation tools, e.g., determination of confidence intervals, p-value determination, Student ' s t-test, Mann- Whitney test etc..
  • Preferred confidence intervals are at least 90%, at least 95%, at least 97%, at least 98% or at least 99 %.
  • the p-values are, preferably, 0.1, 0.05, 0.01, 0.005, or 0.0001.
  • subject as used herein relates to animals, preferably mammals, and, more preferably, humans.
  • the subject according to the present invention shall suffer from pneumo- nia.
  • the subject presents at the emergency room or at the primary care physician.
  • the method of the pre- sent invention shall, preferably, not be applied to those subjects. If the clinical history of a subject to be investigated by the method of the present invention with respect to the aforementioned diseases, disorders or life style behaviors is unknown, the subject may, in a preferred embodiment of the method of the present invention, be tested for the presence of the said disease or disorders as set forth elsewhere herein.
  • the subject preferably, does not suffer from an acute coronary syndrome (ACS).
  • ACS acute coronary syndrome
  • STEMI ST-elevation myocardial infarction
  • NSTEMI non ST-elevation myocardial infarction
  • unstable angina pectoris the subject does, preferably, not suffer from chronic renal failure.
  • the amount of the marker sFlt-1 is determined, it is envisaged that the subject is not pregnant.
  • pneumonia is understood by the skilled person. As used herein, the term, preferably, refers to an acute infection of one or both lungs. Pneumonia may be caused by an infection of the lung by bacteria, fungi or viruses. In the context of the method of the pre- sent invention, pneumonia is preferably caused by bacteria. Bacteria which cause pneumonia include Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, and Moraxella catarrh- alis. Chest pain, dyspnea and fever are other frequently found symptoms. Pneumonia is either primary or secondary pneumonia.
  • Primary pneumonia is, preferably, not precipitated by other pre-existing diseases or disorders. Secondary pneumonia is the complication of another pre-existing disease or disorder. Several diseases in-crease the risk of pneumonia in a subject. Diseases promoting pneumonia are, preferably, pulmonary oedema (caused by heart failure). Pneumonia may also be promoted by a suppressed immune system (e.g., in HIV or cancer subjects, or in subjects suffering from an autoimmune disease).
  • a suppressed immune system e.g., in HIV or cancer subjects, or in subjects suffering from an autoimmune disease.
  • the pneumonia is, preferably, community acquired pneumonia.
  • a risk assessment based on clinical prediction rule for classifying subjects with pneumonia shall be optimized.
  • the method of the present invention does, preferably, not encompass risk assessment itself.
  • the method does, preferably, not encompass the determination of the Scores as referred to herein (in particular of the CURB65 Score, the CRB-65 Score, the CURB Score, the APACHE II Score and/or the PSI Score).
  • the subject shall have been classified based on the clinical prediction rules as set forth herein prior to carrying out the present invention.
  • the subject shall have a known score, in particular a known CURB65 Score, CRB-65 Score, CURB Score, APACHE II Score and/or PSI Score.
  • the risk assessment that shall be optimized in the context of the method of the present invention shall be based on clinical prediction rule for classifying subjects with pneumonia.
  • the risk assessment to be optimized in the context of the pre- sent invention is the assessment whether the subject is admitted to hospital or not.
  • the risk assessment to be optimized is the prediction of the risk of mortality, in particular within a window period of 30 days.
  • a clinical prediction rule is a rule which encompasses a combination of medical signs and symptoms and which allow for predicting the outcome. E.g., based on a clinical prediction rule, a subject may be classified as low risk, moderate risk, or high risk subject.
  • a subject with a CURB65-Score of 0 has a risk 0,6 %, with a CURB-65 score of 1 a risk of 2,7 %, with a CURB65-Score of 2 a risk of 6,8 %, with a CURB65 of 3 a risk of 14,0 % and a CURB-Score of 4 or 5 a risk of 27,8 % of mortality (within a window period of 30 days).
  • a portion of subjects which are classified as low risk subjects according to the clinical prediction rules as set forth herein is at increased risk as compared to the average risk of low risk subjects, in particular of subjects having the same score ("high risk subjects” within a low risk group), whereas a portion of subject which are classified as moderate subjects according to the clinical prediction rules has a decreased risk as compared to the average risk of moderate risk subject, in particular of subjects having the same score ("low risk subjects” within a moderate risk group).
  • the determination of a brain natriuretic peptide, a cardiac Troponin and/or of sFlt-1 allows for identifying these "high risk subjects" and "low risk subject”.
  • the "high risk subjects” have an increased risk of mortality as compared to other subject having the same score and, thus, shall be admitted to hospital.
  • the "low risk subjects” have a decreased risk of mortality as compared to subjects having the same score and, thus, shall not be admitted to hospital or shall be discharged from hospital. These subjects may be treated at home. Without the additional determination of the markers as referred to herein in the context of the present invention, these "low risk subjects” may be treated too excessively resulting in increased health care costs and/or adverse side effects. On the other hand, the "high risk subjects” would - without the determination of the markers - be at further risk since they may not be treated sufficiently.
  • Clinical prediction rules for classifying subjects with pneumonia are well known in the art (for an overview, see e.g. Lim et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003 May;58(5):377-82 which herewith is incorporated by reference)
  • Preferred clinical prediction rules for classifying subjects with pneumonia are selected from the group consisting of the CURB65 Score, the CRB-65 Score, the CURB Score, the APACHE II Score and the PSI Score.
  • the aforementioned scores are well known in the art.
  • the CURB65 Score has been established by the British Thoracic Society. It is a widely used prognostic scoring system for community-acquired pneumonia.
  • the CURB65 Score preferably, takes into account the five following features to stratify subjects into low, moderate risk and high risk subjects. One point is given for each fulfilled feature. Whether these features are fulfilled or not can be assessed by skilled person without further ado
  • a subject with a CURB65 score of 0 or 1 has a low risk of mortality. Usually, the subject is treated at home. A subject with a CURB65 Score of 2 or 3 has a moderate risk of mortality and shall be hospitalized. A subject with a CURB65 Score of 4 or 5 suffers from severe pneumonia and should be hospitalized.
  • the CRB-65 Score takes into account the following features. Again, one point is given for each fulfilled feature:
  • a subject with a CRB65 score of 0 has a low risk of mortality. Usually, the subject is treated at home. A subject with a CRB65 Score of 1 and 2 has a moderate risk of mortality and shall be hospitalized. A subject with a CRB65 Score of 3 or 4 has a high risk of death and should be hospitalized.
  • the CURB Score takes into account the following features. Again, one point is given for each feature present in the subject.
  • a subject with a CURB-score of 0 has a low risk of mortality. Usually the subject is treated at home. A subject with a CURB-Score of 1 and 2 has a moderate risk of mortality and shall be hospitalized. A subject with a CURB-Score of 3 or 4 has a high risk of death and should be hospitalized.
  • the pneumonia severity index is a clinical prediction rule that medical practitioners can use to calculate the probability of morbidity and mortality among subjects with community acquired pneumonia.
  • the PSI can be calculated by the skilled person without further ado.
  • PSI calculators are e.g. available online, See "An interactive tool for the Pneumo- nia Severity Index from the Assessment of the Variation and Outcomes of Pneumonia: Pneumonia Patient Outcomes Research Team Final Report". AHRQ Publication No. 97- N009).
  • the purpose of the PSI is to classify the severity of a subject's pneumonia to determine the amount of resources to be allocated for care.
  • a Risk Class I pneumonia patient can be sent home on oral antibiotics.
  • a Risk Class II pneumonia patient may be sent home with IV antibiotics or treated and monitored for 24 hours in hospital. Patients with Risk Class IV-V pneumonia patient should be hospitalized for treatment.
  • Severity of pneumonia can be also classified by using the so called APACHE II score.
  • the APACHE II Score includes the assessment of temperature, mean blood pressure, heart rate, respiratory rate, arterial pH, oxygenation, serum sodium, serum potassium, hematocrit and white blood cell count.
  • the APACHE II scoring system is not restricted to the ICU but can also be performed in the emergency room, this system is however time consuming as it cannot differentiate between different organ failures (Kress J.P., Hall J.B. in Harrison Principles of Internal Medicine p 1673 ff).
  • the determination of the amount(s) of a cardiac Troponin, of a brain natriuretic peptide and/or of sFlt-1, and the comparison of the, thus, determined, amount(s) to a reference amount (reference amounts) is advantageous in subjects which are classified as low risk subjects based on the clinical prediction rule.
  • the determination of these markers allows for the identification of subjects who are at increased risk (in particular of mortality) as compared to the average risk (in particular of mortality) of subjects being at low risk according to the clinical prediction rule. These subjects shall be admitted to hospital (see comments elsewhere herein).
  • the subject has been classified as low risk subject based on the clinical prediction rule for classifying pneumonia.
  • Preferred scores for low risk subjects for the respective clinical prediction rules are indicated in table 1, see column "low risk”.
  • the subject if the subject is classified by applying the CURB65-Score, the subject has a CURB65-Score of 0 or 1.
  • the subject if the subject is classified by applying the CRB65-Score, the subject has a CRB65-Score of 0.
  • the subject is classified by applying the CURB-Score, the subject has a CURB-Score of 0.
  • the subject has a APACHE Il-Score between 0 to 9.
  • the subject has a PSI-Score of.
  • a subject who has been classified as low risk subject based on the clinical prediction rule shall be admitted to hospital if the amount of the at least one marker is larger than the reference amount(s) (for the respective marker).
  • a subject who has been classified as low risk subject based on the clinical prediction rule is at increased risk of mortality as compared to the average risk of mortality of a subject classified as low risk subject (based on the same clinical prediction rule).
  • the determination of a cardiac Troponin, of a brain natriuretic peptide and/or of sFlt-1 is advantageous in subjects which are classified as moderate risk subjects based on the clinical prediction rule.
  • the determination of these markers allows for the identification of subjects who are at decreased risk (in particular of mortality) as compared to the average risk (in particu- lar of mortality) of subjects being at moderate risk according to the clinical prediction rule. These subjects shall be discharged from hospital (or shall be not admitted to hospital).
  • the subject has been classified as moderate risk subject based on the clinical prediction rule for classifying pneumonia.
  • Preferred scores for mod- erate risk subjects for the clinical prediction rules are indicated in table 1, see column "moderate risk”:
  • the subject is classified by applying the CURB65-Score, the subject has a CURB65-Score of 2 or 3.
  • the subject has a CRB65-Score of 1 or 2.
  • the subject has a CURB-Score of 1 or 2.
  • the subject has a APACHE Il-Score of between 10 to 14.
  • the subject has a PSI-Score of III.
  • a subject who has been classified as moderate risk subject based on the clinical prediction rule shall not be admitted to hospital and/or shall be discharged from hospital, if the amount of the at least one marker is lower than the reference amount(s) (for the respective marker).
  • a subject who has been classified as moderate risk subject based on the clinical prediction rule is at decreased risk of mortality as compared to the average risk of mortality of a subject classified as moderate risk subject.
  • Table 1 Scores for low risk and moderate risk subjects according to various clinical prediction rules low risk moderate risk
  • the subject has been classified as low risk subject based on the clinical prediction rule, wherein an amount of the at least one marker in the sample from the subject which is larger than the reference amount (or which is essentially the same as compared to the reference amount) indicates that the subject shall be admitted to hospital.
  • the subject has been classified as moderate risk subject based on the clinical prediction rule, wherein an amount of the at least one marker in the sample from the subject which is lower than the reference amount (or which is essentially the same as compared to the reference amount) indicates that the subject shall not be admitted to hospital or shall be discharged from hospital.
  • the subject has been classified as low risk subject based on the clinical prediction rule, wherein an amount of the at least one marker in the sample from the subject which is larger than the reference amount (or which is essentially the same as compared to the reference amount) indicates that the subject is at increased risk of mortality as compared to the average risk of mortality of a subject classified as low risk subject (and, preferably, having the same score as the test subject).
  • the subject is classified as moderate risk subject based on the clinical prediction rule, wherein an amount of the at least one marker in the sample from the subject which is lower than the reference amount (or which is essentially the same as compared to the reference amount) indicates that the subject is at reduced risk of mortal- ity as compared to the average risk of mortality of a subject classified as moderate risk subject, (and, preferably, having the same score as the test subject).
  • sample refers to a sample of a body fluid, to a sample of separated cells or to a sample from a tissue or an organ.
  • Samples of body fluids can be obtained by well known techniques and include, preferably, samples of blood, plasma, serum, or urine, more pref- erably, samples of blood, plasma or serum.
  • Tissue or organ samples may be obtained from any tissue or organ by, e.g., biopsy.
  • Separated cells may be obtained from the body fluids or the tissues or organs by separating techniques such as centrifugation or cell sorting.
  • cell-, tissue- or organ samples are obtained from those cells, tissues or organs which express or produce the peptides referred to herein.
  • the sample has been preferably obtained at presentation at the emergency room or at the primary care physician.
  • the step of obtaining the sample is preferably not comprised by the method of the present invention.
  • soluble Flt-1 or "sFlt-1" (soluble fms-like tyrosine kinase-1) as used herein refers to polypeptide which is a soluble form of the VEGF receptor Fltl . It was identified in conditioned culture medium of human umbilical vein endothelial cells. The endogenous soluble Fltl (sFltl) receptor is chromatographically and immunologically similar to recombinant human sFltl and binds [1251] VEGF with a comparable high affinity. Human sFltl is shown to form a VEGF-stabilized complex with the extracellular domain of KDR/Flk-1 in vitro.
  • sFltl refers to human sFltl . More preferably, human sFltl can be deduced from the amino acid sequence of Flt-1 as shown in Genbank accession number P17948, GI: 125361. An amino acid sequence for mouse sFltl is shown in Genbank accession number BAA24499.1, GI: 2809071.
  • the term "sFlt-1" used herein also encompasses variants of the aforementioned specific sFlt-1 polypeptide. Such variants have at least the same essential biological and immunological properties as the specific sFlt-1 polypeptide.
  • a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and/or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the amino sequence of the specific sFlt-1 polypeptide (preferably over the whole length of said polypeptide.
  • the degree of identity between two amino acid sequences can be determined by algorithms well known in the art.
  • the degree of identity is to be determined by comparing two optimally aligned sequences over a comparison window, where the fragment of amino acid sequence in the comparison window may comprise additions or dele- tions (e.g., gaps or overhangs) as compared to the reference sequence (which does not comprise additions or deletions) for optimal alignment.
  • the percentage is calculated by determining the number of positions at which the identical amino acid residue occurs in both sequences to yield the number of matched positions, dividing the number of matched positions by the total number of positions in the window of comparison and multiplying the result by 100 to yield the percentage of sequence identity.
  • Optimal alignment of sequences for comparison may be conducted by the local homology algorithm of Smith and Waterman Add. APL. Math.
  • GAP Garnier et al. (1981), by the homology alignment algorithm of Needleman and Wunsch J. Mol. Biol. 48:443 (1970), by the search for similarity method of Pearson and Lipman Proc. Natl. Acad Sci. (USA) 85: 2444 (1988), by computerized implementations of these algorithms (GAP, BESTFIT, BLAST, PASTA, and TFASTA in the Wisconsin Genetics Software Package, Genetics Computer Group (GCG), 575 Science Dr., Madison, WI), or by visual inspection. Given that two sequences have been identified for comparison, GAP and BESTFIT are preferably employed to determine their optimal alignment and, thus, the degree of identity. Preferably, the default values of 5.00 for gap weight and 0.30 for gap weight length are used.
  • Variants referred to above may be allelic variants or any other species specific homologs, paralogs, or orthologs.
  • the vari- ants referred to herein include fragments or subunits of the specific sFlt-1 polypeptide or the aforementioned types of variants as long as these fragments have the essential immunological and biological properties as referred to above.
  • Such fragments may be, e.g., degradation products of the sFlt-1 peptide.
  • variants which differ due to posttranslational modifications such as phosphorylation or myristylation.
  • cardiac Troponin refers to all Troponin iso forms expressed in cells of the heart and, preferably, the subendocardial cells. These isoforms are well characterized in the art as described, e.g., in Anderson 1995, Circulation Research, vol. 76, no. 4: 681-686 and Ferrieres 1998, Clinical Chemistry, 44: 487-493.
  • cardiac Troponin refers to Troponin T and/or Troponin I, and, most preferably, to Troponin T. It is to be understood that isoforms of Troponins may be determined in the method of the present invention together, i.e. simultaneously or sequentially, or individually, i.e. without determining the other iso form at all. Amino acid sequences for human Troponin T and human Troponin I are disclosed in Anderson, loc cit and Ferrieres 1998, Clinical Chemistry, 44: 487-493.
  • cardiac Troponin encompasses also variants of the aforementioned specific Troponins, i.e., preferably, of Troponin I, and more preferably, of Troponin T. Such variants have at least the same essential biological and immunological properties as the specific cardiac Troponins. In particular, they share the same essential biological and immuno- logical properties if they are detectable by the same specific assays referred to in this specification, e.g., by ELISA Assays using polyclonal or monoclonal antibodies specifically recognizing the said cardiac Troponins.
  • a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and/or addition wherein the amino acid sequence of the variant is still, preferably, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 85%, at least about 90%, at least about 92%, at least about 95%, at least about 97%, at least about 98%, or at least about 99% identical with the amino sequence of the specific Troponin. How to determine the degree of identity is disclosed elsewhere herein.
  • brain natriuretic peptide comprises Brain Natiuretic Peptide (BNP)-type pep- tides and variants thereof having the same predictive potential.
  • Natriuretic peptides according to the present invention comprise BNP-type peptides and variants thereof (see e.g. Bonow, R. O. (1996). New insights into the cardiac natriuretic peptides. Circulation 93: 1946-1950).
  • BNP-type peptides comprise pre-proBNP, proBNP, NT-proBNP, and BNP.
  • the pre-pro peptide (134 amino acids in the case of pre-proBNP) comprises a short signal peptide, which is enzymatically cleaved off to release the pro peptide (108 amino acids in the case of proBNP).
  • the pro peptide is further cleaved into an N-terminal pro peptide (NT -pro peptide, 76 amino acids in case of NT -proBNP) and the active hormone (32 amino acids in the case of BNP).
  • Preferred natriuretic peptides according to the present invention are NT -proBNP, BNP, and variants thereof.
  • BNP is the active hormone and has a shorter half-life than their respective inactive counterparts NT -proBNP, BNP is metabolized in the blood, whereas NT -proBNP circulates in the blood as an intact molecule and as such is eliminated renally.
  • the in- vivo half- life of NT -pro BNP is 120 min longer than that of BNP, which is 20 min (Smith M W, Espiner E A, Yandle T G, Charles C J, Richards A M. Delayed metabolism of human brain natriuretic peptide reflects resistance to neutral endopeptidase. J. Endocrinol. 2000; 167:239-46).
  • natriuretic peptides are NT-proBNP or variants thereof.
  • the human NT-proBNP as referred to in accordance with the present invention is a polypeptide comprising, preferably, 76 amino acids in length corresponding to the N-terminal portion of the human NT-proBNP molecule.
  • human BNP and NT-proBNP has been described already in detail in the prior art, e.g., WO 02/089657, WO 02/083913, Bonow 1996, New Insights into the cardiac natriuretic peptides. Circulation 93: 1946-1950.
  • human NT-proBNP as used herein is human NT-proBNP as disclosed in EP 0 648 228 Bl .
  • the NT-proBNP referred to in accordance with the present invention further encompasses allelic and other variants of said specific sequence for human NT-proBNP discussed above. Specifically, envisaged are variant polypeptides which are on the amino acid level at least 60% identical, more preferably at least 70%, at least 80%, at least 90%, at least 95%, at least 98% or at least 99% identical, to human NT-proBNP, preferably, over the entire length. How to calculate the degree of identified between two sequence is described elsewhere herein.
  • Determining the amount of a brain natriuretic peptide, in particular of NT-proBNP, of a cardiac Troponin, in particular of Troponin T, and of sFlt-1 or any other peptide or polypeptide referred to in this specification relates to measuring the amount or concentration, preferably semi-quantitatively or quantitatively. Measuring can be done directly or indirectly. Direct measuring relates to measuring the amount or concentration of the peptide or polypeptide based on a signal which is obtained from the peptide or polypeptide itself and the intensity of which directly correlates with the number of molecules of the peptide present in the sample.
  • Such a signal - sometimes referred to herein as intensity signal - may be obtained, e.g., by measuring an intensity value of a specific physical or chemical property of the peptide or polypeptide.
  • Indirect measuring includes measuring of a signal obtained from a secondary component (i.e. a component not being the peptide or polypeptide itself) or a biological read out system, e.g., measurable cellular responses, ligands, labels, or enzymatic reaction products.
  • determining the amount of a peptide or polypeptide can be achieved by all known means for determining the amount of a peptide in a sample.
  • Said means comprise immunoassay devices and methods which may utilize labelled molecules in various sandwich, competition, or other assay formats. Said assays will develop a signal which is indicative for the presence or absence of the peptide or polypeptide.
  • the signal strength can, preferably, be correlated directly or indirectly (e.g. reverse- proportional) to the amount of polypeptide present in a sample.
  • Further suitable methods comprise measuring a physical or chemical property specific for the peptide or polypeptide such as its precise molecular mass or NMR spectrum.
  • Said methods comprise, preferably, biosensors, optical devices coupled to immunoassays, biochips, analytical devices such as mass- spectrometers, NMR- analyzers, or chromatography devices.
  • methods include micro-plate ELISA-based methods, fully-automated or robotic immunoassays (available for example on ElecsysTM analyzers), CBA (an enzymatic Cobalt Binding Assay, available for example on Roche-HitachiTM analyzers), and latex agglutination assays (available for example on Roche-HitachiTM analyzers).
  • determining the amount of a peptide or polypeptide comprises the steps of (a) contacting a cell capable of eliciting a cellular response the intensity of which is indicative of the amount of the peptide or polypeptide with the said peptide or polypeptide for an ad- equate period of time, (b) measuring the cellular response.
  • the sample or processed sample is, preferably, added to a cell culture and an internal or external cellular response is measured.
  • the cellular response may include the measurable expression of a reporter gene or the secretion of a substance, e.g. a peptide, polypeptide, or a small molecule.
  • the expression or substance shall generate an intensity signal which cor- relates to the amount of the peptide or polypeptide.
  • determining the amount of a peptide or polypeptide comprises the step of measuring a specific intensity signal obtainable from the peptide or polypeptide in the sample.
  • a specific intensity signal may be the signal intensity observed at an m/z variable specific for the peptide or polypeptide observed in mass spectra or a NMR spectrum specific for the peptide or polypeptide.
  • Determining the amount of a peptide or polypeptide may, preferably, comprises the steps of (a) contacting the peptide with a specific ligand, (b) preferably, removing non-bound ligand and other components which may be present in the sample, (c) measuring the amount of bound ligand, i.e.
  • said steps of contacting, removing and measuring may be performed by an analyzer unit of the system disclosed herein.
  • said steps may be performed by a single analyzer unit of said system or by more than one analyzer unit in operable communication with each other.
  • said system disclosed herein may include a first ana- lyzer unit for performing said steps of contacting and removing and a second analyzer unit, operably connected to said first analyzer unit by a transport unit (for example, a robotic arm), which performs said step of measuring.
  • binding according to the present invention includes both covalent and non-covalent binding.
  • a ligand according to the present invention can be any compound, e.g., a peptide, polypeptide, nucleic acid, or small molecule, binding to the peptide or polypeptide described herein.
  • Preferred ligands include antibodies, nucleic acids, peptides or polypeptides such as receptors or binding partners for the peptide or polypeptide and fragments thereof comprising the binding domains for the peptides, and aptamers, e.g.
  • nucleic acid or peptide ap- tamers nucleic acid or peptide ap- tamers.
  • Methods to prepare such ligands are well-known in the art. For example, identification and production of suitable antibodies or aptamers is also offered by commercial suppliers. The person skilled in the art is familiar with methods to develop derivatives of such ligands with higher affinity or specificity. For example, random mutations can be introduced into the nucleic acids, peptides or polypeptides. These derivatives can then be tested for binding according to screening procedures known in the art, e.g. phage display.
  • Antibodies as referred to herein include both polyclonal and monoclonal antibodies, as well as fragments thereof, such as Fv, Fab and F(ab)2 fragments that are capable of binding anti- gen or hapten.
  • the present invention also includes single chain antibodies and humanized hybrid antibodies wherein amino acid sequences of a non-human donor antibody exhibiting a desired antigen-specificity are combined with sequences of a human acceptor antibody.
  • the donor sequences will usually include at least the antigen-binding amino acid residues of the donor but may comprise other structurally and/or functionally relevant ami- no acid residues of the donor antibody as well.
  • Such hybrids can be prepared by several methods well known in the art.
  • the ligand or agent binds specifically to the peptide or polypeptide.
  • Specific binding according to the present invention means that the lig- and or agent should not bind substantially to, i.e. cross-react with, another peptide, polypeptide or substance present in the sample to be analysed.
  • the specifically bound peptide or polypeptide should be bound with at least 3 times higher, more preferably at least 10 times higher and even more preferably at least 50 times higher affinity than any other relevant peptide or polypeptide.
  • Non-specific binding may be tolerable, if it can still be distinguished and measured unequivocally, e.g. according to its size on a Western Blot, or by its relatively higher abundance in the sample. Binding of the ligand can be measured by any method known in the art. Preferably, said method is semi-quantitative or quantitative.
  • Binding of a ligand may be measured directly, e.g. by NMR or surface plasmon resonance. Measurement of the binding of a ligand, according to preferred embodiments, is performed by an analyzer unit of a system disclosed herein. Thereafter, an amount of the measured binding may be calculated by a computing device of a system disclosed herein. Second, if the ligand also serves as a substrate of an enzymatic activity of the peptide or polypeptide of interest, an enzymatic reaction product may be measured (e.g. the amount of a protease can be measured by measuring the amount of cleaved substrate, e.g. on a Western Blot).
  • the ligand may exhibit enzymatic properties itself and the "ligand/peptide or polypeptide" complex or the ligand which was bound by the peptide or polypeptide, re- spectively, may be contacted with a suitable substrate allowing detection by the generation of an intensity signal.
  • a suitable substrate allowing detection by the generation of an intensity signal.
  • the amount of substrate is saturating.
  • the substrate may also be labelled with a detectable label prior to the reaction.
  • the sample is contacted with the substrate for an adequate period of time.
  • An adequate period of time refers to the time necessary for an detectable, preferably measurable, amount of product to be produced. Instead of measuring the amount of product, the time necessary for appearance of a given (e.g.
  • the ligand may be coupled covalently or non-covalently to a label allowing detection and measurement of the ligand.
  • Labelling may be done by direct or indirect methods. Direct labelling involves coupling of the label directly (covalently or non-covalently) to the ligand. Indirect labelling involves binding (covalently or non- covalently) of a secondary ligand to the first ligand. The secondary ligand should specifically bind to the first ligand. Said secondary ligand may be coupled with a suitable label and/or be the target (receptor) of tertiary ligand binding to the secondary ligand.
  • Suita- ble secondary and higher order ligands may include antibodies, secondary antibodies, and the well-known streptavidin-biotin system (Vector Laboratories, Inc.).
  • the ligand or substrate may also be "tagged" with one or more tags as known in the art. Such tags may then be targets for higher order ligands. Suitable tags include biotin, digoxygenin, His-Tag, Glu- tathion-S-Transferase, FLAG, GFP, myc-tag, influenza A virus haemagglutinin (HA), maltose binding protein, and the like.
  • the tag is preferably at the N-terminus and/or C-terminus.
  • Suitable labels are any labels detectable by an appropriate detection method. Typical labels include gold particles, latex beads, acridan ester, luminol, ruthenium, enzymatically active labels, radioactive labels, magnetic labels ("e.g. magnetic beads", including paramagnetic and superparamagnetic labels), and fluorescent labels.
  • Enzymatically active labels include e.g. horseradish peroxidase, alkaline phosphatase, beta-Galactosidase, Luciferase, and derivatives thereof.
  • Suitable substrates for detection include di-amino-benzidine (DAB), 3,3'-5,5'-tetramethylbenzidine, NBT- BCIP (4-nitro blue tetrazolium chloride and 5-bromo-4-chloro-3-indolyl-phosphate, available as ready-made stock solution from Roche Diagnostics), CDP-StarTM (Amersham Biosciences), ECFTM (Amersham Biosciences).
  • a suitable enzyme-substrate combination may result in a coloured reaction product, fluorescence or chemiluminescence, which can be measured according to methods known in the art (e.g. using a light-sensitive film or a suitable camera system). As for measuring the enyzmatic reaction, the criteria given above apply analogously.
  • Typical fluorescent labels include fluorescent proteins (such as GFP and its derivatives), Cy3, Cy5, Texas Red, Fluorescein, and the Alexa dyes (e.g. Alexa 568). Further fluorescent labels are available e.g. from Molecular Probes (Oregon). Also the use of quantum dots as fluorescent labels is contemplated.
  • Typical radioactive labels include 35S, 1251, 32P, 33P and the like. A radioactive label can be detected by any method known and appropriate, e.g. a light-sensitive film or a phosphor imager.
  • Suitable measurement methods according the present invention also include precipitation (particularly immunoprecipitation), electrochemiluminescence (electro-generated chemiluminescence), RIA (radioimmunoassay), ELISA (enzyme- linked immunosorbent assay), sandwich enzyme immune tests, electrochemiluminescence sandwich immunoassays (ECLIA), dissociation-enhanced lanthanide fluoro immuno assay (DELFIA), scintillation proximity assay (SPA), turbidimetry, nephelometry, latex-enhanced turbidimetry or nephelometry, or solid phase immune tests.
  • precipitation particularly immunoprecipitation
  • electrochemiluminescence electrochemiluminescence (electro-generated chemiluminescence)
  • RIA radioimmunoassay
  • ELISA enzyme- linked immunosorbent assay
  • sandwich enzyme immune tests sandwich enzyme immune tests
  • the amount of a peptide or polypeptide may be, also preferably, determined as follows: (a) contacting a solid support comprising a ligand for the peptide or polypeptide as specified above with a sample comprising the peptide or polypeptide, (b) preferably, removing unbound peptide or polypeptide as well as remaining sample material and (c) measuring the amount peptide or polypeptide which is bound to the support. Preferably, the amount of the complex of the ligand and the peptide or polypeptide formed on the solid support is measured.
  • the amount of the complex formed during the determination shall represent the amount of the peptide or polypeptide originally present in the sample.
  • the ligand is, preferably chosen from the group consisting of nucleic acids, peptides, poly- peptides, antibodies and aptamers and is, preferably, present on a solid support in immobilized form.
  • Materials for manufacturing solid supports are well known in the art and include, inter alia, commercially available column materials, polystyrene beads, latex beads, magnetic beads, colloid metal particles, glass and/or silicon chips and surfaces, nitrocellulose strips, membranes, sheets, duracytes, wells and walls of reaction trays, plastic tubes etc.
  • the ligand or agent may be bound to many different carriers.
  • Examples of well-known carriers include glass, polystyrene, polyvinyl chloride, polypropylene, polyethylene, polycarbonate, dextran, nylon, amyloses, natural and modified celluloses, polyacrylamides, agaroses, and magnetite.
  • the nature of the carrier can be either soluble or insoluble for the purposes of the invention. Suitable methods for fixing/immobilizing said ligand are well known and include, but are not limited to ionic, hydrophobic, covalent interactions and the like. It is also contemplated to use "suspension arrays" as arrays according to the present invention (Nolan 2002, Trends Biotechnol. 20(1):9-12). In such suspension arrays, the carrier, e.g.
  • microbead or microsphere is present in suspension.
  • the array consists of different microbeads or microspheres, possibly labelled, carrying different ligands.
  • Methods of producing such arrays for example based on solid-phase chemistry and photo-labile protective groups, are generally known (US 5,744,305).
  • amount encompasses the absolute amount of a polypeptide or peptide, the relative amount or concentration of the said polypeptide or peptide as well as any value or parameter which correlates thereto or can be derived therefrom.
  • values or parameters comprise intensity signal values from all specific physical or chemical properties obtained from the said peptides by direct measurements, e.g., intensity values in mass spectra or NMR spectra.
  • values or parameters which are obtained by indirect measurements specified elsewhere in this description e.g., re- sponse levels determined from biological read out systems in response to the peptides or intensity signals obtained from specifically bound ligands.
  • comparing encompasses comparing the determined amount for at least one marker as referred to herein to a reference. It is to be understood that comparing as used herein refers to any kind of comparison made between the value for the amount with the reference.
  • the comparison referred to in step (b) of the method of the present invention may be carried out manually or by a computing device (e.g., of a system disclosed herein).
  • the value of the amount and the reference can be, e.g., compared to each other and the said comparison can be automatically carried out by a computer program executing an algorithm for the comparison.
  • the computer program carrying out the said evaluation will provide the desired assessment in a suitable output format.
  • the value of the determined amount may be compared to values corresponding to suitable references which are stored in a database by a computer program.
  • the computer program may further evaluate the result of the comparison, i.e. automatically provide the desired assessment in a suitable output format. Based on the comparison of the amount determined in step a) and the reference amount, it is possible to assess whether a subject exhibiting a symptom of an acute cardiovascular event suffers from pulmonary complication, or not.
  • a result of a comparison may be given as raw data (absolute or relative amounts), and in some cases as an indicator in the form of a word, phrase, symbol, or numerical value which may be indicative of a particular diagnosis.
  • the reference amount is to be chosen so that either a difference or a similarity in the compared amounts allows identifying those test subjects which belong into the group of subjects having an increased risk or a decreased risk (in particular of mortality, in particular within a window period of 30 days).
  • the term "reference amount” as used herein refers to an amount which allows for assessing whether a subject suffering from pneumonia is at increased risk or decreased risk, e.g. of mortality as set forth herein elsewhere, or whether a subject shall be hospitalized or not.
  • the term refers to an amount which allows assessing whether a subject suffering from pneumonia is at increased risk or decreased risk (in particular of mortality) as compared to the average risk (in particular of mortality) of a subject who has been classified with the same score, in particular according to the CURB65-Score.
  • the term refers to an amount which allows for assessing whether a subject shall be hospitalized or not.
  • the reference amount may be used to define and establish a threshold amount.
  • the threshold amount preferably, allows for a rule-in and/or a rule-out diagnosis.
  • Said rule-in and/or rule-out diagnosis may be provided by the computing device of a system disclosed herein based on said comparison of the calculated "amount" to a reference or a threshold.
  • a computing device of a system may provide an indicator, in the form of a word, symbol, or numerical value which is indicative of one of a rule-in or rule-out diagnosis.
  • the reference amount applicable for an individual subject may vary depending on various physiological parameters such as age, gender, or subpopulation, as well as on the means used for the determination of the polypeptide or peptide referred to herein.
  • a suitable ref- erence amount may be determined from a reference sample to be analysed together, i.e. simultaneously or subsequently, with the test sample.
  • Reference amounts can be calculated for a cohort of subjects (i.e. (i) a subject or group of subjects who is at increased risk of mortality and/or who shall be hospitalized as set forth herein or (ii) a subject or group of subjects who is at decreased risk of mortality and/or who shall not be hospitalized as set forth herein) based on the average or mean values for a given biomarker by applying standard statistically methods.
  • accuracy of a test such as a method aiming to diagnose an event, or not, is best described by its receiver- operating characteristics (ROC) (see especially Zweig 1993, Clin. Chem. 39:561-577).
  • the ROC graph is a plot of all of the sensitivity/specificity pairs resulting from continuously varying the decision threshold over the entire range of data observed.
  • the clinical performance of a diagnostic method depends on its accuracy, i.e. its ability to correctly allocate subjects to a certain prognosis or diagnosis.
  • the ROC plot indicates the overlap between the two distributions by plotting the sensitivity versus 1 -specificity for the complete range of thresholds suitable for making a distinction.
  • sensitivity or the true- positive fraction which is defined as the ratio of number of true-positive test results to the product of number of true-positive and number of false-negative test results. This has also been referred to as positivity in the presence of a disease or condition. It is calculated solely from the affected subgroup.
  • the false-positive fraction On the x-axis is the false-positive fraction, or 1 -specificity which is defined as the ratio of number of false-positive results to the product of number of true-negative and number of false-positive results. It is an index of specificity and is calculated entirely from the unaffected subgroup. Because the true- and false-positive fractions are calculated entirely separately, by using the test results from two different subgroups, the ROC plot is independent of the prevalence of the event in the cohort. Each point on the ROC plot represents a sensitivity/-specificity pair corresponding to a particular decision threshold.
  • a test with perfect discrimination has an ROC plot that passes through the upper left corner, where the true-positive fraction is 1.0, or 100% (perfect sensitivity), and the false-positive fraction is 0 (perfect specificity).
  • the theoretical plot for a test with no discrimination is a 45° diagonal line from the lower left corner to the upper right corner. Most plots fall in between these two extremes. (If the ROC plot falls completely below the 45° diagonal, this is easily remedied by reversing the criterion for "positivity" from "greater than” to "less than” or vice versa.) Qualitatively, the closer the plot is to the upper left corner, the higher the overall accuracy of the test.
  • a threshold can be derived from the ROC curve allowing for the diagnosis or prediction for a given event with a proper balance of sensitivity and specificity, respectively.
  • the reference to be used for the aforementioned method of the present invention i.e. a threshold which allows to discriminate between subjects suffering from a pulmonary complication, or not, can be generated, preferably, by establishing a ROC for said cohort as described above and deriving a threshold amount therefrom.
  • the reference amount may be derived from
  • a subject who has been classified with the same score (as the test subject) based on the clinical prediction rule and being known to be at increased risk of mortality as compared to the average risk of mortality of a subject who has been classified with the same score, or (ii) a subject who has been classified with the same score based on the clinical prediction rule and being known to be at decreased risk of mortality as compared to the average risk of a subject who has been classified with the same score.
  • the subject in i) has been classified as low risk subject based on the clinical prediction rule (for the scores for low risks subjects, see table 1, column "low risk”).
  • the subject in ii) has been classified a moderate risk subject based on the clinical predication rule (for the scores for moderate risk subjects, see table 1, column "moderate risk”).
  • the (test) subject has been classified as low risk subject based on the clinical prediction rule
  • the reference amount(s) is (are) derived from a subject who has been classified as low risk subject based on said clinical prediction rule, said subject being known to be at increased risk of mortality as compared to the average risk of mortality of a subject who has been classified with the same score
  • an increased amount (increased amounts) of the at least one marker as set forth herein in the sample from the (test) subject as compared to the reference amount(s), or an amount (amounts) of the at least one marker which is (are) essentially the same as compared to the reference amount(s) indicates that the subject has an increased risk of mortality as compared to the average risk of mortality of a subject who has been classified with the same score.
  • the (test) subject has been classified as moderate risk subject based on the clinical prediction rule
  • the reference amount(s) is (are) derived from a subject who has been classified as moderate risk subject based on said clinical prediction rule, said subject being known to be at decreased risk of mortality as compared to the average risk of mortality of a subject who has been classified with the same score
  • an decreased amount (decreased amounts) of the at least one marker as set forth herein in the sample from the (test) subject as compared to the reference amount(s), or an amount (amounts) of the at least one marker which is (are) essentially the same as compared to the reference amount (s) indicates that the subject has a decreased risk of mortality as compared to the average risk of mortality of a subject who has been classified with the same score.
  • the reference amount may be derived from a
  • the subject in i) has been classified as low risk subject based on the clinical prediction rule (see table 1, "low risk”).
  • the subject in ii) has been classified a moderate risk subject based on the clinical predication rule (see table 1, "moderate risk”).
  • the (test) subject has been classified as low risk subject based on the clinical prediction rule, wherein the reference amount(s) is (are) derived from a subject who has been classified as low risk subject based on said clinical prediction rule, wherein the subject has been admitted to hospital, wherein an increased amount (increased amounts) of at least one marker as set forth herein in the sample from the (test) subject as compared to the reference amount(s), or an amount (amounts) of the at least one marker which is (are) essentially the same as compared to the reference amount (s) indicates that the subject shall be hospitalized.
  • the (test) subject has been classified as moderate risk subject based on the clinical prediction rule, in particular, wherein the subject has not been admit- ted to hospital, or wherein the subject has been discharged from hospital
  • the reference amount(s) is (are) derived from a subject who has been classified as moderate risk subject based on said clinical prediction rule, wherein an decreased amount (decreased amounts) of at least one marker as set forth herein in the sample from the (test) subject as compared to the reference amount(s), or an amount(s) of the at least one marker which is (are) essentially the same as compared to the reference amount indicates that the subject shall not be hospitalized or shall be discharged from hospital.
  • test subject the subject to be tested
  • reference subject the subject from whom the reference amount(s) is (are) derived
  • reference amount(s) is (are) derived from a subject who has been classified as low risk subject based on the clinical prediction rule as set forth herein above, preferred reference amounts are as follows:
  • Preferred reference amounts for a brain natriuretic peptide, in particular of NT-proBNP are within a range of 1000 to 2300 pg/ml, in particular within a range of 1300 to 2000 pg/ml.
  • the reference amount is 2000 pg/ml, more preferably, 1200 pg/ml and, most preferably, 1600 pg/ml.
  • Preferred reference amounts for a cardiac Troponin, in particular of Troponin T are within a range of 10 to 25 pg/ml, in particular within a range of 15 to 25 pg/ml.
  • the reference amount is 10 pg/ml, more preferably, 15 pg/ml and, most preferably, 20 pg/ml.
  • Preferred reference amounts for sFlt-1 are within a range of 120 to 200 pg/ml, in particular within a range of 130 to 180 pg/ml.
  • the reference amount is 130 pg/ml, more preferably, 170 pg/ml and, most preferably, 150 pg/ml.
  • preferred reference amounts are as follows: Preferred reference amounts for a brain natriuretic peptide, in particular of NT-proBNP, are within a range of 100 to 400 pg/ml, in particular within a range 200 to 400 of pg/ml. Preferably, the reference amount is 400 pg/ml, more preferably, 300 pg/ml and, most preferably, 200 pg/ml.
  • Preferred reference amounts for a cardiac Troponin, in particular of Troponin T are within a range of 1 to 9 pg/ml, in particular within a range of 3 to 8 pg/ml.
  • the reference amount is 8 pg/ml, more preferably, 6 pg/ml and, most preferably, 3 pg/ml.
  • Preferred reference amounts for a sFlt-1 are within a range of 60 to 100 pg/ml, in particular within a range of 70 to 90 pg/ml.
  • the reference amount is 90 pg/ml, more preferably, 80 pg/ml and, most preferably, 70 pg/ml.
  • a method for establishing an aid for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia comprising:
  • a) determining the amount of at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 i) bringing the sample into contact with a detection agent (detection agents) that specifically bind(s) to said at least one marker for a time sufficient to allow for the formation of a complex of the said detection agent and the at least one marker from the sample, (ii) measuring the amount of the formed complex, wherein the said amount of the formed complex is proportional to the amount of the at least one marker present in the sample, and (iii) transforming the amount of the formed complex into an amount of the at least one marker reflecting the amount of the at least one marker present in the sample; b) comparing said amount to a reference; and
  • step b) establishing an aid for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia based on the result of the comparison made in step b).
  • a system for establishing an aid for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia comprising:
  • an analyzer unit configured to bringing the sample into contact with a detection agent (detection agents) that specifically bind(s) to said at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 for a time sufficient to allow for the formation of a complex of the said detection agent and the at least one marker from the sample, b) an analyzer unit configured to measure the amount of the formed complex, wherein the said amount of the formed complex is proportional to the amount of the at least one marker present in the sample,
  • a non-transient machine readable media including a plurality of instructions executable by the processor, the instructions, when executed transform the amount of the formed complex into an amount of the at least one marker reflecting the amount of the at least one marker present in the sample, compare said amount to a reference, and establish an aid for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia based on the result of said comparison to said reference.
  • a suitable detection agent may be, in an aspect, an antibody which is specifically binds to the at least one marker, i.e. a detection agent which binds to a brain natriuretic peptide, a cardiac troponin or to sFlt-1, in a sample of a subject to be investigated by the method of the invention.
  • Another detection agent that can be applied in an aspect, may be an apta- mere which specifically binds to the at least one marker in the sample.
  • sample is removed from the complex formed between the detection agent and the at least one marker prior to the measurement of the amount of formed complex.
  • the detection agent may be immobilized on a solid support.
  • the sample can be removed from the formed complex on the solid support by applying a washing solution.
  • the formed complex shall be proportional to the amount of the at least one marker present in the sample. It will be understood that the specificity and/or sensitivity of the detection agent to be applied defines the degree of proportion of at least one marker comprised in the sample which is capable of being specifically bound. Further details on how the determination can be carried out are also found elsewhere herein.
  • the amount of formed complex shall be transformed into an amount of at least one marker reflecting the amount indeed present in the sample. Such an amount, in an aspect, may be essentially the amount present in the sample or may be, in another aspect, an amount which is a certain proportion thereof due to the relationship between the formed complex and the amount present in the original sample.
  • step a) may be carried out by an analyzer unit (or analyzing unit), in an aspect, an analyzer unit (or analyzing unit) as defined elsewhere herein.
  • the amount(s) determined in step a) is (are) compared to a reference.
  • the reference is a reference as defined elsewhere herein.
  • the reference takes into account the proportional relationship between the measured amount of complex and the amount present in the original sample.
  • said relationship can be also taken into account when carrying out the comparison, e.g., by including a normalization and/or correction calculation step for the determined amount prior to actually comparing the value of the determined amount and the reference.
  • the normalization and/or correction calculation step for the determined amount adopts the comparison step such that the limitations of the detection agent that has been used are reflected properly.
  • the comparison is carried out automatically, e.g., assisted by a computer system or the like.
  • the aid for optimizing a risk assessment is established based on the comparison carried out in step b) by allocating the subject either into a group of subjects having an increased risk or decreased risk as set forth herein elsewhere. As discussed elsewhere herein already, the allocation of the investigated subject must not be correct in 100% of the investigated cases.
  • the groups of subjects into which the investigated subject is allocated are artifi- cial groups in that they are established based on statistical considerations, i.e. a certain preselected degree of likelihood based on which the method of the invention shall operate.
  • the aid for optimizing a risk assessment is established automatically, e.g., assisted by a computing device or the like, as described and disclosed herein.
  • said method further comprises a step of recommending and/or managing the subject according to the result established in step c) as set forth elsewhere herein in detail, and/or adapting intensiveness of disease monitoring.
  • steps b) and/or c) are carried out by one or more analyzer units as set forth elsewhere herein.
  • the present invention also relates to the use of i) at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 or ii) of a detection agent which specifically binds to a natriuretic peptide, and/or of a detection agent which specifically binds to a cardiac Troponin, and/or of a detection agent which specifically binds to sFlt-1, in a sample of a subject suffering from pneumonia for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia.
  • the present invention also relates to the use of i) at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1, or ii) of a detection agent which specifically binds to a natriuretic peptide, and/or of a detection agent which specifically binds to a cardiac Troponin, and/or of a detection agent which specifically binds to sFlt-1, for the manufacture of a pharmaceutical or diagnostic composition for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia.
  • detection agent refers to an agent that is capable of specifically recognizing and binding to the biomarker polypeptide(s) present in a sample.
  • the said agent shall allow for direct or indirect detection of the complex formed by the said agent and the biomarker. Direct detection can be achieved by including into the agent a detectable label. Indirect labelling may be achieved by a further agent that specifically binds to the complex comprising the biomarker and the detection agent wherein the said further agent is than capable of generating a detectable signal. Suitable compounds which can be used as detection agents are well known in the art.
  • the detection agent is an antibody or aptamere which specifically binds to the biomarker.
  • antibody has been described elsewhere herein.
  • a device adapted for carrying out a method of the invention comprising
  • an analyzer unit comprising a detection agent (or agents) which specifically bind(s) to a marker selected from the group consisting of a brain natriuretic peptide, a cardiac troponin, and sFlt-1, said unit being adapted for determining the amount(s) of the marker(s) in a sample of a subject suffering from pneumonia; and
  • an analyzer unit for comparing the determined amount(s) with reference amount(s), whereby a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia is optimized, said unit comprising a database with a reference amount (or amounts) and a computer-implemented algorithm for carrying out the comparison.
  • the term "device” as used herein preferably, relates to a system comprising the aforementioned units operatively linked to each other as to allow the diagnosis or monitoring according to the methods of the invention.
  • Preferred detection agents which can be used for the analysing unit are disclosed elsewhere herein.
  • the analysing unit preferably, compris- es said detection agents in immobilized form on a solid support which is to be contacted to the sample comprising the biomarkers the amount of which is to be determined.
  • the analysing unit can also comprise a detector which determines the amount of detection agent which is specifically bound to the biomarker(s). The determined amount can be transmitted to the evaluation unit.
  • Said evaluation unit comprises a data processing element, such as a computer, with an implemented algorithm for carrying out a comparison between the determined amount and a suitable reference.
  • Suitable references are either derived from a subject or group of subjects as defined above in context with the method of the present invention.
  • the results may be given as output of parametric diagnostic raw da- ta, preferably, as absolute or relative amounts. It is to be understood that these data will need interpretation by the clinician. However, also envisage are expert system devices wherein the output comprises processed diagnostic raw data the interpretation of which does not require a specialized clinician.
  • a preferred embodiment of the instant disclosure includes a system for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia.
  • exemplary systems of the instant disclosure may include Roche ElecsysTM Systems and Cobas ® e Immunoassay Analyzers, Abbott ArchitectTM and AxsymTM Analyzers, Siemens CentaurTM and ImmuliteTM Analyzers, and Beckman Coulter UniCelTM and AcessTM Analyzers, or the like.
  • Embodiments of the system may include one or more analyzer units utilized for practicing the subject disclosure.
  • an analyzer unit may comprise a stand-alone apparatus, or module with- in a larger instrument, which performs one or both of the detection, e.g. qualitative and/or quantitative evaluation of samples for diagnostic purpose.
  • an analyzer unit may perform or assist with the pipetting, dosing, mixing of samples and/or reagents.
  • An analyzer unit may comprise a reagent holding unit for holding reagents to perform the assays.
  • Reagents may be arranged for example in the form of containers or cassettes contain- ing individual reagents or group of reagents, placed in appropriate receptacles or positions within a storage compartment or conveyor. Detection reagents may also be in immobilized form on a solid support which are contacted with the sample. Further, an analyzer unit may include a process and/or detection component which is optimizable for specific analysis.
  • an analyzer unit may be configured for optical detection of an analyte, for example a marker, with a sample.
  • An exemplary analyzer unit configured for optical detection comprises a device configured for converting electro -magnetic energy into an electrical signal, which includes both single and multi-element or array optical detectors.
  • an optical detector is capable of monitoring an optical electro -magnetic signal and providing an electrical outlet signal or re- sponse signal relative to a baseline signal indicative of the presence and/or concentration of an analyte in a sample being located in an optical path.
  • Such devices may also include, for example, photodiodes, including avalanche photodiodes, phototransistors, photo conductive detectors, linear sensor arrays, CCD detectors, CMOS detectors, including CMOS array detectors, photomultipliers, and photomultiplier arrays.
  • an optical detector such as a photodiode or photomultiplier, may contain additional signal conditioning or processing electronics.
  • an optical detector may include at least one pre-amplifier, electronic filter, or integrated circuit. Suitable pre-preamplifiers include, for example, integrating, transimpedance, and current gain (current mirror) preamplifiers.
  • one or more analyzer unit may comprise a light source for emitting light.
  • a light source of an analyzer unit may consist of at least one light emitting element (such as a light emitting diode, an electric powered radiation source such as an incandescent lamp, an electroluminescent lamp, a gas discharge lamp, a high-intensity discharge lamp, a laser) for measuring analyte concentrations with a sample being tested or for enabling an energy transfer (for example, through florescent resonance energy transfer or catalyzing an enzyme).
  • a light emitting element such as a light emitting diode, an electric powered radiation source such as an incandescent lamp, an electroluminescent lamp, a gas discharge lamp, a high-intensity discharge lamp, a laser
  • an analyzer unit of the system may include one or more incubation units (for ex- ample, for maintaining a sample or a reagent at a specified temperature or temperature range).
  • an analyzer unit may include a thermocycler, include a real-time thermocycler, for subjecting a sample to repeated temperature cycles and monitoring a change in the amount of an amplification product with the sample.
  • an analyzer unit of the system disclosed herein may comprise, or be operationally connected to, a reaction vessel or cuvette feeding unit.
  • Exemplary feeding units include liquid processing units, such as a pipetting unit, to deliver samples and/or reagents to the reaction vessels.
  • the pipetting unit may comprise a reusable washable needle, e.g.
  • the analyzer unit may further comprise one or more mixing units, for example a shaker to shake a cuvette comprising a liquid, or a mixing paddle to mix liquids in a cuvette, or reagent container.
  • mixing units for example a shaker to shake a cuvette comprising a liquid, or a mixing paddle to mix liquids in a cuvette, or reagent container.
  • a computing device may be a general purpose computer or a portable computing device, for example. It should also be understood that multiple computing devices may be used together, such as over a network or other methods of transferring data, for performing one or more steps of the methods disclosed herein. Exemplary computing devices include desktop computers, laptop computers, personal data assistants ("PDA"), such as BLACKBERRY brand devices, cellular devices, tablet computers, servers, and the like.
  • PDA personal data assistants
  • a computing device comprises a processor capable of executing a plurality of instructions (such as a program of software).
  • a computing device has access to a memory.
  • a memory is a computer readable medium and may comprise a single storage device or multiple storage devices, located either locally with the computing device or accessible to the computing device across a network, for example.
  • Computer-readable media may be any available media that can be accessed by the computing device and includes both volatile and non- volatile media. Further, computer readable-media may be one or both of removable and non-removable media. By way of example, and not limitation, computer-readable media may comprise computer storage media.
  • Exemplary computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or any other memory technology, CD-ROM, Digital Versatile Disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used for storing a plurality of instructions capable of being accessed by the computing device and exe- cuted by the processor of the computing device.
  • RAM random access memory
  • ROM read only memory
  • EEPROM electrically erasable programmable read-only memory
  • flash memory any other memory technology
  • CD-ROM Compact Disk
  • DVD Digital Versatile Disk
  • magnetic cassettes magnetic tape
  • magnetic disk storage magnetic disk storage devices
  • software may include instructions which, when executed by a processor of the computing device, may perform one or more steps of the methods disclosed herein. Some of the instructions may be adapted to produce signals that control operation of other machines and thus may operate through those control signals to transform materials far removed from the computer itself.
  • the plurality of instructions may also comprise an algorithm which is generally conceived to be a self-consistent sequence of steps leading to a desired result. These steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic pulses or signals capable of being stored, transferred, transformed, combined, compared, and otherwise manipulated. It proves convenient at times, principally for reasons of common usage, to refer to these sig- nals as values, characters, display data, numbers, or the like as a reference to the physical items or manifestations in which such signals are embodied or expressed. It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely used here as convenient labels applied to these quantities.
  • an algorithm for carrying out a comparison between a determined amount of one or more markers disclosed herein, and a suitable reference is embodied and performed by executing the instructions.
  • the results may be given as output of parametric diagnostic raw data or as absolute or relative amounts.
  • a "diagnosis" may be provided by the computing device of a system disclosed herein based on said comparison of the calculated "amount" to a reference or a threshold.
  • a computing device of a system may provide an indicator, in the form of a word, symbol, or numerical value which is indicative of a particular diagnosis.
  • the computing device may also have access to an output device.
  • exemplary output devices include fax machines, displays, printers, and files, for example.
  • a computing device may perform one or more steps of a method disclosed herein, and thereafter provide an output, via an output device, relating to a result, indication, ratio or other factor of the method.
  • the invention pertains to a kit adapted for carrying out a method of the present in- vention comprising a detection agent which specifically binds to a marker selected from the group consisting of a brain natriuretic peptide, a cardiac troponin, and sFlt-1 , reference standards as well as instructions for carrying out the said method.
  • kit refers to a collection of the aforementioned components, preferably, provided in separately or within a single container.
  • the container also comprises instructions for carrying out the method of the present invention. These instructions may be in the form of a manual or may be provided by a computer program code which is capa- ble of carrying out the comparisons referred to in the methods of the present invention and to establish a diagnosis accordingly when implemented on a computer or a data processing device.
  • the computer program code may be provided on a data storage medium or device such as a optical storage medium (e.g., a Compact Disc) or directly on a computer or data processing device.
  • the kit shall comprise at least one standard for a reference as defined herein above, i.e.
  • a solution with a pre-defined amount for the SP-B peptide polypeptide representing a reference amount may represent, e.g., the amount of SP-B peptide from a subject or group of subjects exhibiting a symptom of an acute cardiovascular event and suffering from a pulmonary complication or a subject or group of subjects exhibiting a symptom of an acute cardiovascular event and not suffering from a pulmonary complication or a clinically apparently healthy subject or group thereof.
  • kits disclosed herein includes at least one component or a packaged combination of components for practicing a disclosed method.
  • packaged combi- nation it is meant that the kits provide a single package that contains a combination of one or more components, such as probes (for example, an antibody), controls, buffers, reagents (for example, conjugate and/or substrate) instructions, and the like, as disclosed herein.
  • probes for example, an antibody
  • buffers for example, buffers
  • reagents for example, conjugate and/or substrate instructions, and the like
  • a kit containing a single container is also included within the definition of "packaged combination.”
  • the kits include at least one probe, for example an anti- body (having specific affinity for an epitope of a biomarker as disclosed herein.
  • kits may include an antibody that is labelled with a fluorophore or an antibody that is a member of a fusion protein.
  • the probe may be immobilized, and may be immobilised in a specific conformation.
  • an immobilized probe may be provided in a kit to specifically bind target protein, to detect target protein in a sample, and/or to remove target protein from a sample.
  • kits include at least one probe, which may be immobilized, in at least one container.
  • Kits may also include multiple probes, optionally immobilized, in one or more containers.
  • the multiple probes may be present in a sin- gle container or in separate containers, for example, wherein each container contains a single probe.
  • a kit may include one or more non-immobilized probe and one or more solid support that does or does not include an immobilized probe. Some such embod- iments may comprise some or all of the reagents and supplies needed for immobilizing one or more probes to the solid support, or some or all of the reagents and supplies needed for binding of immobilized probes to specific proteins within a sample.
  • a single probe (including multiple copies of the same probe) may be immobilized on a single solid support and provided in a single container.
  • an immobilized probe may be provided in multiple different containers (e.g., in single-use form), or multiple immobilized probes may be provided in multiple different containers.
  • the probes may be immobilized on multiple different type of solid supports. Any combination of immobilized probe(s) and container(s) is contemplated for the kits disclosed herein, and any combination thereof may be selected to achieve a suitable kit for a desired use.
  • a container of the kits may be any container that is suitable for packaging and/or containing one or more components disclosed herein, including for example probes (for example, an antibody), controls, buffers, and reagents (for example, conjugate and/or substrate). Suitable materials include, but are not limited to, glass, plastic, cardboard or other paper product, wood, metal, and any alloy thereof.
  • the container may completely encase an immobilized probe(s) or may simply cover the probe to minimize contamination by dust, oils, etc., and expose to light.
  • he kits may comprise a single container or multiple containers, and where multiple containers are present, each container may be the same as all other containers, different than others, or different than some but not all other containers.
  • Figure 1 shows a ROC curve and statistical analysis thereof for NT-proBNP comparing CURB65 0 versus CURB65 3 and 4
  • Figure 2 shows a ROC curve and statistical analysis thereof for NT-proBNP comparing CURB65 0 and 1 versus CURB65 2 and 3
  • Figure 3 shows a ROC curve and statistical analysis thereof for Troponin T comparing CURB65 0 versus CURB65 3 and 4
  • Figure 4 shows a ROC curve and statistical analysis thereof for Troponin T comparing CURB65 0 and 1 versus CURB65 2, 3 and 4
  • Figure 5 shows a ROC curve and statistical analysis thereof for sFlt-1 comparing CURB65 0 versus CURB65 3 and 4
  • Figure 6 shows a ROC curve and statistical analysis thereof for sFlt-1 comparing CURB65 0 and 1 versus CURB65 2, 3 and 4
  • Example 1 Patient cohorts
  • a total of 84 subjects with pneumonia confirmed by chest x ray were included into the study, they also received an ECHO in order to identify pre-existing heart failure.
  • blood was drawn for laboratory testing.
  • a total of 48 patients with chronic artery disease and with and without signs of heart failure were included into the study to form a reference group. All patients were classified according to the NYHA classification and their LVEF was also determined.
  • Example 2 Determination of blood levels of sFlt-1, Troponin T and NT-proBNP
  • sFlt-1 and NT-proBNP were determined with sandwich immuno-assays using analyzers from Roche/Hitachi, Elecsys or COBAS e-series.
  • the assays comprise two monoclonal antibodies specific for the respective peptide. The first of these iv biotinylated and the second one in labelled with a Tris(2,2'-bibyridyl)ruthemium (Il)-complex. In a first incubation step both antibodies are incubated with the sample.
  • a sandwich complex comprising the peptide to be determined and the two different antibodies is formed.
  • streptavidin-coated beads are added to this complex.
  • the beads bind the sandwich complexes.
  • the reaction mixture is then aspirated into a measuring cell where the beads are magnetically captured on the surface of the electrode.
  • the application of a voltage then induces a chemiluminescent emission from the ruthenium complex which is measured by a photomultiplier.
  • the emitted amount of light is dependent on the amount of sandwich complexes on the electrode.
  • sFlt-1 amounts between 10 to 85,000 pg/ml
  • NT-proBNP amounts between 2 pg/ml and 35,000 pg/ml can be measured.
  • Troponin T (hsTNT) was also determined using the aforementioned automatic analysers. The test followed the same test principles as described for NT -pro BNP. The high sensitivity Troponin T test used in this study has a sensitivity of 1 pg/ml and can be used on ELECSYS 2010 as well as on COB AS e 411 or an COB AS e 601 analysers.
  • LVEF pulmonary infiltrates and pre-existing heart failure
  • markers such as those without any significant information (CRP), markers that could identify low risk patients but did not differentiate risk categories (pro-SP-B, c fragment pro SP-B) and markers that clearly increased with CURB65 score, these markers included NT -pro BNP, sensitive Troponin T and sFlTl .
  • CRP significant information
  • markers that could identify low risk patients but did not differentiate risk categories pro-SP-B, c fragment pro SP-B
  • markers that clearly increased with CURB65 score these markers included NT -pro BNP, sensitive Troponin T and sFlTl .
  • NT-pro BNP Troponin T sFlTl NHYA II LVEF below 60 % 396 pg/ml 9 pg/ml 107 pg/ml NYHA III LVEF below 60 % 1576 g/ml 12 pg/ml 150 pg/ml
  • systolic blood pressure was 110 mmHg
  • breathing rate is 28/min.
  • He is classified as CURB65 class II
  • his NT -pro BNP is 265 pg/ml
  • Troponin T was 6 pg/ml
  • sFlTl was 68 pg/ml.
  • He is reclassified to CURB Class I, given fluid because he is exsiccated, he condition improves and he is discharged.
  • a 66 year old male with a history of heart failure presents with pneumonia, systolic blood pressure is 120 mmHg, the breathing rate is 25/min and he has no somnia. He is classified as CURB Class I, his NT-pro BNP is 2320 pg/ml, Troponin T is 14 pg/ml and sFlTl is 104 pg/ml. He is admitted to the hospital.
  • a 56 year old patient with pneumonia and normal vigilance, systolic blood pressure of 85 mmHg, respiratory rate of 26/min is classified as CURB65 Score 1.
  • His NT -pro BNP is 3120 pg/ml
  • his Troponin T is 24 pg/ml
  • his sFltl is 92 pg/ml.
  • He is reclassified to CURB65 score II and admitted to hospital.
  • a cardiovascular examination reveals a LVEF below 20% and thus heart failure which has not been recognized before.
  • NT -pro BNP as a marker of cardiac function
  • Troponin T as a marker of cardiac necrosis
  • sFltl as a marker of ischemia

Abstract

The present invention relates to a method for optimizing a risk assessment of pneumonia based on a clinical prediction rule for classifying subjects with pneumonia. The method is based on the determination of the amount of a least one marker selected from the group consisting of a cardiac Troponin, a brain natriuretic peptide, and sFlt-1, and on the comparison of the determined amount(s) to a reference amount. Further envisaged are kits and devices adapted to carry out the said method.

Description

TnT, NTproBNP, sFlt-1 for CURB65 in pneumonia
The present invention relates to a method for optimizing a risk assessment of pneumonia based on a clinical prediction rule for classifying subjects with pneumonia. The present invention also relates to a system for performing an optimized risk assessment of pneumo- nia as disclosed herein and to reagents and kits used in performing the methods disclosed herein. The method is based on the determination of the amount of a least one marker selected from the group consisting of a cardiac Troponin, a brain natriuretic peptide, and sFlt-1, and on the comparison of the determined amount(s) to a reference amount. Further envisaged are kits and devices adapted to carry out the said method. Community acquired pneumonia is the leading cause of death from infections in developed countries. Costs associated with pneumonia are related to hospital care. In order to give guidance to clinicians with respect to hospitalization various clinical prediction rules for classifying subjects with pneumonia such as the CURB65 score have been developed (for an overview, see e.g. Lim et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003 May;58(5):377-82.)
The CURB65 Score reflects the following clinical features: confusion, blood urea above 19 mg per dl, respiratory rate above 30 breaths per minute, systolic blood pressure bellow 90 mmHg and/or diastolic blood pressure below 60 mmHg and age above 65 years. Each of these components receives 1 point and total points reflect mortality as follows: 0 point 0,6 %, 1 point 2,7 %, 2 points 6,8 %, 3 points 14,0 % and 4 or 5 points 27,8 %. Depending on the score obtained hospitalization, hospitalization with ICU admission or discharge is recommended. The CURB65 score in principle reflects: general risk factors and comorbidities (65), cardiovascular responses (blood pressure, confusion), impairment of kidney function (urea) and extent of lung involvement (respiratory rate).
NT-proBNP has been shown to be a powerful predictor of short term mortality in pneumonia patients, however, this has not been related to the CURB65 score (Nowak A. et al, Chest, ahead of publication).
Recently, the value of the CURB65 score has been questioned with respect to discharge of patients being classified as CURB65 score 0 or 1 patients (Alberti S. et al, Respiratoy Medicine 2011, 105: 1732 - 1738). There may be patients with a CURB 65 score of 0 or 1 in need of hospitalization.
Thus, there is need for improving the assessment of patients with pneumonia beyond the clinical prediction rules for classifying patients with pneumonia.
The technical problem underlying the present invention can be seen as the provision of means and methods for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia. The technical problem is solved by the embodiments characterized in the claims and herein below.
Accordingly, the present invention relates to a method for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia, comprising the steps of
a. determining the amount of at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 in a sample from a subject suffering from pneumonia, and
b. comparing the amount as determined in step a) with a reference amount, thereby optimizing the risk assessment based on the clinical prediction rule for classifying subjects with pneumonia.
The method of the present invention, preferably, is an in vitro method. Moreover, it may comprise steps in addition to those explicitly mentioned above. For example, further steps may relate to sample pre-treatments or evaluation of the results obtained by the method. The method may be carried out manually or assisted by automation. Preferably, step (a) and/or (b) may in total or in part be assisted by automation, e.g., by a suitable robotic and sensory equipment for the determination in step (a) or a computer-implemented comparison and/or diagnosis based on said comparison in step (b).
Accordingly, the present invention also preferably relates to a system for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia, comprising
a) an analyzer unit configured to contact, in vitro, a portion of a sample from a subject suffering from pneumonia with a ligand comprising specific binding affinity for at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1,
b) an analyzer unit configured to detect a signal from the portion of the sample from the subject contacted with the ligand,
c) a computing device having a processor and in operable communication with said analysis units, and
d) a non-transient machine readable media including a plurality of instruction executable by a the processor, the instructions, when executed calculate an amount of the at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1, and compare the amount of the at least one marker with a reference amount, thereby optimizing the risk assessment based on the clinical prediction rule for classifying subjects with pneumonia.
In the context of the present invention the amount at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 shall be determined. Thus, the amount(s) of one, two, or three markers shall be determined and shall be compared to the respective reference amount(s). Preferred combinations of markers are as follows:
a. sFlt-1 and a brain natriuretic peptide,
b. sFlt-1 and cardiac Troponin,
c. a brain natriuretic peptide and a cardiac Troponin, or
d. sFlt-1, a brain natriuretic peptide, and a cardiac Troponin.
In the context of the method of the present invention, a risk assessment which is based on a clinical prediction rule for classifying subjects with pneumonia shall be optimized. As will be understood by those skilled in the art, such an assessment is usually not intended to be correct for 100% of the subjects to be diagnosed. The term, however, requires that the assessment is correct for a statistically significant portion of the subjects (e.g. a cohort in a cohort study). Whether a portion is statistically significant can be determined without fur- ther ado by the person skilled in the art using various well known statistic evaluation tools, e.g., determination of confidence intervals, p-value determination, Student's t-test, Mann- Whitney test etc.. Details are found in Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York 1983. Preferred confidence intervals are at least 90%, at least 95%, at least 97%, at least 98% or at least 99 %. The p-values are, preferably, 0.1, 0.05, 0.01, 0.005, or 0.0001.
The term "subject" as used herein relates to animals, preferably mammals, and, more preferably, humans. The subject according to the present invention shall suffer from pneumo- nia. Preferably, the subject presents at the emergency room or at the primary care physician.
It is known that several diseases or disorders can also cause an elevation of the markers to be determined in the context of the present invention. Accordingly, the method of the pre- sent invention shall, preferably, not be applied to those subjects. If the clinical history of a subject to be investigated by the method of the present invention with respect to the aforementioned diseases, disorders or life style behaviors is unknown, the subject may, in a preferred embodiment of the method of the present invention, be tested for the presence of the said disease or disorders as set forth elsewhere herein.
Thus, the subject, preferably, does not suffer from an acute coronary syndrome (ACS). The term "ACS" as used herein includes STEMI (ST-elevation myocardial infarction); NSTEMI (non ST-elevation myocardial infarction) and unstable angina pectoris. Further, the subject does, preferably, not suffer from chronic renal failure. Moreover, if the amount of the marker sFlt-1 is determined, it is envisaged that the subject is not pregnant.
The term "pneumonia" is understood by the skilled person. As used herein, the term, preferably, refers to an acute infection of one or both lungs. Pneumonia may be caused by an infection of the lung by bacteria, fungi or viruses. In the context of the method of the pre- sent invention, pneumonia is preferably caused by bacteria. Bacteria which cause pneumonia include Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, and Moraxella catarrh- alis. Chest pain, dyspnea and fever are other frequently found symptoms. Pneumonia is either primary or secondary pneumonia. Primary pneumonia is, preferably, not precipitated by other pre-existing diseases or disorders. Secondary pneumonia is the complication of another pre-existing disease or disorder. Several diseases in-crease the risk of pneumonia in a subject. Diseases promoting pneumonia are, preferably, pulmonary oedema (caused by heart failure). Pneumonia may also be promoted by a suppressed immune system (e.g., in HIV or cancer subjects, or in subjects suffering from an autoimmune disease).
In the context of the present invention, the pneumonia is, preferably, community acquired pneumonia.
In the context of the method of the present invention, a risk assessment based on clinical prediction rule for classifying subjects with pneumonia shall be optimized. The method of the present invention, however, does, preferably, not encompass risk assessment itself. Thus, the method does, preferably, not encompass the determination of the Scores as referred to herein (in particular of the CURB65 Score, the CRB-65 Score, the CURB Score, the APACHE II Score and/or the PSI Score). However, the subject shall have been classified based on the clinical prediction rules as set forth herein prior to carrying out the present invention. Thus, the subject shall have a known score, in particular a known CURB65 Score, CRB-65 Score, CURB Score, APACHE II Score and/or PSI Score.
The risk assessment that shall be optimized in the context of the method of the present invention shall be based on clinical prediction rule for classifying subjects with pneumonia. In a preferred embodiment, the risk assessment to be optimized in the context of the pre- sent invention is the assessment whether the subject is admitted to hospital or not. In another embodiment, the risk assessment to be optimized is the prediction of the risk of mortality, in particular within a window period of 30 days.
A clinical prediction rule is a rule which encompasses a combination of medical signs and symptoms and which allow for predicting the outcome. E.g., based on a clinical prediction rule, a subject may be classified as low risk, moderate risk, or high risk subject.
E.g., the CURB65-Score which is described herein below in more detail is frequently used for risk stratification. For example, a subject with a CURB65-Score of 0 has a risk 0,6 %, with a CURB-65 score of 1 a risk of 2,7 %, with a CURB65-Score of 2 a risk of 6,8 %, with a CURB65 of 3 a risk of 14,0 % and a CURB-Score of 4 or 5 a risk of 27,8 % of mortality (within a window period of 30 days). Depending of the risk of mortality, it can be decided whether a subject shall be hospitalized or not. Advantageously, it was shown in the context of the studies underlying the present invention that a portion of subjects which are classified as low risk subjects according to the clinical prediction rules as set forth herein is at increased risk as compared to the average risk of low risk subjects, in particular of subjects having the same score ("high risk subjects" within a low risk group), whereas a portion of subject which are classified as moderate subjects according to the clinical prediction rules has a decreased risk as compared to the average risk of moderate risk subject, in particular of subjects having the same score ("low risk subjects" within a moderate risk group). The determination of a brain natriuretic peptide, a cardiac Troponin and/or of sFlt-1 allows for identifying these "high risk subjects" and "low risk subject". The "high risk subjects" have an increased risk of mortality as compared to other subject having the same score and, thus, shall be admitted to hospital. The "low risk subjects" have a decreased risk of mortality as compared to subjects having the same score and, thus, shall not be admitted to hospital or shall be discharged from hospital. These subjects may be treated at home. Without the additional determination of the markers as referred to herein in the context of the present invention, these "low risk subjects" may be treated too excessively resulting in increased health care costs and/or adverse side effects. On the other hand, the "high risk subjects" would - without the determination of the markers - be at further risk since they may not be treated sufficiently.
Clinical prediction rules for classifying subjects with pneumonia are well known in the art (for an overview, see e.g. Lim et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003 May;58(5):377-82 which herewith is incorporated by reference) Preferred clinical prediction rules for classifying subjects with pneumonia are selected from the group consisting of the CURB65 Score, the CRB-65 Score, the CURB Score, the APACHE II Score and the PSI Score. The aforementioned scores are well known in the art. The CURB65 Score has been established by the British Thoracic Society. It is a widely used prognostic scoring system for community-acquired pneumonia. The CURB65 Score, preferably, takes into account the five following features to stratify subjects into low, moderate risk and high risk subjects. One point is given for each fulfilled feature. Whether these features are fulfilled or not can be assessed by skilled person without further ado
• Confusion
• Blood urea nitrogen (larger than 19 mg per dl)
• respiratory rate (larger than or equal to 30 breaths per minute)
· Blood pressure (systolic blood pressure lower than 90 mmHg or diastolic blood pressure larger than or equal to 60 mmHg)
• Age equal to or larger than 65 years A subject with a CURB65 score of 0 or 1 has a low risk of mortality. Usually, the subject is treated at home. A subject with a CURB65 Score of 2 or 3 has a moderate risk of mortality and shall be hospitalized. A subject with a CURB65 Score of 4 or 5 suffers from severe pneumonia and should be hospitalized.
The CRB-65 Score takes into account the following features. Again, one point is given for each fulfilled feature:
• Confusion
· respiratory rate (larger than or equal to 30 breaths per minute)
• Blood pressure (systolic blood pressure lower than 90 mmHg or diastolic blood pressure larger than or equal to 60 mmHg)
• Age equal to or larger than 65 years A subject with a CRB65 score of 0 has a low risk of mortality. Usually, the subject is treated at home. A subject with a CRB65 Score of 1 and 2 has a moderate risk of mortality and shall be hospitalized. A subject with a CRB65 Score of 3 or 4 has a high risk of death and should be hospitalized. The CURB Score takes into account the following features. Again, one point is given for each feature present in the subject.
• Confusion
• Blood urea nitrogen (larger than 19 mg per dl)
· respiratory rate (larger than or equal to 30 breaths per minute)
• Blood pressure (systolic blood pressure lower than 90 mmHg or diastolic blood pressure larger than or equal to 60 mmHg)
A subject with a CURB-score of 0 has a low risk of mortality. Usually the subject is treated at home. A subject with a CURB-Score of 1 and 2 has a moderate risk of mortality and shall be hospitalized. A subject with a CURB-Score of 3 or 4 has a high risk of death and should be hospitalized.
The pneumonia severity index (PSI) is a clinical prediction rule that medical practitioners can use to calculate the probability of morbidity and mortality among subjects with community acquired pneumonia. The PSI can be calculated by the skilled person without further ado. PSI calculators are e.g. available online, See "An interactive tool for the Pneumo- nia Severity Index from the Assessment of the Variation and Outcomes of Pneumonia: Pneumonia Patient Outcomes Research Team Final Report". AHRQ Publication No. 97- N009). The purpose of the PSI is to classify the severity of a subject's pneumonia to determine the amount of resources to be allocated for care. Most commonly, the PSI scoring system has been used to decide whether subjects with pneumonia can be treated as outsubjects or as (hospitalized) inpatients. A Risk Class I pneumonia patient can be sent home on oral antibiotics. A Risk Class II pneumonia patient may be sent home with IV antibiotics or treated and monitored for 24 hours in hospital. Patients with Risk Class IV-V pneumonia patient should be hospitalized for treatment.
Severity of pneumonia can be also classified by using the so called APACHE II score. The APACHE II Score includes the assessment of temperature, mean blood pressure, heart rate, respiratory rate, arterial pH, oxygenation, serum sodium, serum potassium, hematocrit and white blood cell count. The APACHE II scoring system is not restricted to the ICU but can also be performed in the emergency room, this system is however time consuming as it cannot differentiate between different organ failures (Kress J.P., Hall J.B. in Harrison Principles of Internal Medicine p 1673 ff).
It has been shown in the context of the present invention that the determination of the amount(s) of a cardiac Troponin, of a brain natriuretic peptide and/or of sFlt-1, and the comparison of the, thus, determined, amount(s) to a reference amount (reference amounts) is advantageous in subjects which are classified as low risk subjects based on the clinical prediction rule. In these subjects, the determination of these markers allows for the identification of subjects who are at increased risk (in particular of mortality) as compared to the average risk (in particular of mortality) of subjects being at low risk according to the clinical prediction rule. These subjects shall be admitted to hospital (see comments elsewhere herein).
Thus, in a preferred embodiment, the subject has been classified as low risk subject based on the clinical prediction rule for classifying pneumonia. Preferred scores for low risk subjects for the respective clinical prediction rules are indicated in table 1, see column "low risk". Preferably, if the subject is classified by applying the CURB65-Score, the subject has a CURB65-Score of 0 or 1. Preferably, if the subject is classified by applying the CRB65-Score, the subject has a CRB65-Score of 0. Preferably, if the subject is classified by applying the CURB-Score, the subject has a CURB-Score of 0. Preferably, if the sub- ject is classified by applying the APACHE Il-Score, the subject has a APACHE Il-Score between 0 to 9. Preferably, if the subject is classified by applying the PSI-Score, the subject has a PSI-Score of. Preferably, a subject who has been classified as low risk subject based on the clinical prediction rule, shall be admitted to hospital if the amount of the at least one marker is larger than the reference amount(s) (for the respective marker). Preferably, a subject who has been classified as low risk subject based on the clinical prediction rule is at increased risk of mortality as compared to the average risk of mortality of a subject classified as low risk subject (based on the same clinical prediction rule). It has been further shown in the context of the present invention that the determination of a cardiac Troponin, of a brain natriuretic peptide and/or of sFlt-1 is advantageous in subjects which are classified as moderate risk subjects based on the clinical prediction rule. In these subjects, the determination of these markers allows for the identification of subjects who are at decreased risk (in particular of mortality) as compared to the average risk (in particu- lar of mortality) of subjects being at moderate risk according to the clinical prediction rule. These subjects shall be discharged from hospital (or shall be not admitted to hospital).
Thus, in a preferred embodiment, the subject has been classified as moderate risk subject based on the clinical prediction rule for classifying pneumonia. Preferred scores for mod- erate risk subjects for the clinical prediction rules are indicated in table 1, see column "moderate risk": Preferably, if the subject is classified by applying the CURB65-Score, the subject has a CURB65-Score of 2 or 3. Preferably, if the subject is classified by applying the CRB65-Score, the subject has a CRB65-Score of 1 or 2. Preferably, if the subject is classified by applying the CURB-Score, the subject has a CURB-Score of 1 or 2. Prefera- bly, if the subject is classified by applying the APACHE Il-Score, the subject has a APACHE Il-Score of between 10 to 14. Preferably, if the subject is classified by applying the PSI-Score, the subject has a PSI-Score of III. Preferably, a subject who has been classified as moderate risk subject based on the clinical prediction rule, shall not be admitted to hospital and/or shall be discharged from hospital, if the amount of the at least one marker is lower than the reference amount(s) (for the respective marker). Preferably, a subject who has been classified as moderate risk subject based on the clinical prediction rule is at decreased risk of mortality as compared to the average risk of mortality of a subject classified as moderate risk subject. Table 1 : Scores for low risk and moderate risk subjects according to various clinical prediction rules low risk moderate risk
CURB-65 0 or 1 2 or 3
CRB-65 0 1 or 2
CURB 0 1 or 2
Apache II O to 9 10 to 14
PSI l or II III
Thus, in a preferred embodiment, the subject has been classified as low risk subject based on the clinical prediction rule, wherein an amount of the at least one marker in the sample from the subject which is larger than the reference amount (or which is essentially the same as compared to the reference amount) indicates that the subject shall be admitted to hospital.
In another preferred embodiment, the subject has been classified as moderate risk subject based on the clinical prediction rule, wherein an amount of the at least one marker in the sample from the subject which is lower than the reference amount (or which is essentially the same as compared to the reference amount) indicates that the subject shall not be admitted to hospital or shall be discharged from hospital.
In yet another preferred embodiment, the subject has been classified as low risk subject based on the clinical prediction rule, wherein an amount of the at least one marker in the sample from the subject which is larger than the reference amount (or which is essentially the same as compared to the reference amount) indicates that the subject is at increased risk of mortality as compared to the average risk of mortality of a subject classified as low risk subject (and, preferably, having the same score as the test subject).
In a further preferred embodiment, the subject is classified as moderate risk subject based on the clinical prediction rule, wherein an amount of the at least one marker in the sample from the subject which is lower than the reference amount (or which is essentially the same as compared to the reference amount) indicates that the subject is at reduced risk of mortal- ity as compared to the average risk of mortality of a subject classified as moderate risk subject, (and, preferably, having the same score as the test subject).
The term "sample" refers to a sample of a body fluid, to a sample of separated cells or to a sample from a tissue or an organ. Samples of body fluids can be obtained by well known techniques and include, preferably, samples of blood, plasma, serum, or urine, more pref- erably, samples of blood, plasma or serum. Tissue or organ samples may be obtained from any tissue or organ by, e.g., biopsy. Separated cells may be obtained from the body fluids or the tissues or organs by separating techniques such as centrifugation or cell sorting. Preferably, cell-, tissue- or organ samples are obtained from those cells, tissues or organs which express or produce the peptides referred to herein. The sample has been preferably obtained at presentation at the emergency room or at the primary care physician. The step of obtaining the sample is preferably not comprised by the method of the present invention.
The term "soluble Flt-1" or "sFlt-1" (soluble fms-like tyrosine kinase-1) as used herein refers to polypeptide which is a soluble form of the VEGF receptor Fltl . It was identified in conditioned culture medium of human umbilical vein endothelial cells. The endogenous soluble Fltl (sFltl) receptor is chromatographically and immunologically similar to recombinant human sFltl and binds [1251] VEGF with a comparable high affinity. Human sFltl is shown to form a VEGF-stabilized complex with the extracellular domain of KDR/Flk-1 in vitro. Preferably, sFltl refers to human sFltl . More preferably, human sFltl can be deduced from the amino acid sequence of Flt-1 as shown in Genbank accession number P17948, GI: 125361. An amino acid sequence for mouse sFltl is shown in Genbank accession number BAA24499.1, GI: 2809071. The term "sFlt-1" used herein also encompasses variants of the aforementioned specific sFlt-1 polypeptide. Such variants have at least the same essential biological and immunological properties as the specific sFlt-1 polypeptide. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification, e.g., by ELISA assays using polyclonal or mono- clonal antibodies specifically recognizing the said sFlt-1 polypeptide. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and/or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the amino sequence of the specific sFlt-1 polypeptide (preferably over the whole length of said polypeptide. The degree of identity between two amino acid sequences can be determined by algorithms well known in the art. Preferably, the degree of identity is to be determined by comparing two optimally aligned sequences over a comparison window, where the fragment of amino acid sequence in the comparison window may comprise additions or dele- tions (e.g., gaps or overhangs) as compared to the reference sequence (which does not comprise additions or deletions) for optimal alignment. The percentage is calculated by determining the number of positions at which the identical amino acid residue occurs in both sequences to yield the number of matched positions, dividing the number of matched positions by the total number of positions in the window of comparison and multiplying the result by 100 to yield the percentage of sequence identity. Optimal alignment of sequences for comparison may be conducted by the local homology algorithm of Smith and Waterman Add. APL. Math. 2:482 (1981), by the homology alignment algorithm of Needleman and Wunsch J. Mol. Biol. 48:443 (1970), by the search for similarity method of Pearson and Lipman Proc. Natl. Acad Sci. (USA) 85: 2444 (1988), by computerized implementations of these algorithms (GAP, BESTFIT, BLAST, PASTA, and TFASTA in the Wisconsin Genetics Software Package, Genetics Computer Group (GCG), 575 Science Dr., Madison, WI), or by visual inspection. Given that two sequences have been identified for comparison, GAP and BESTFIT are preferably employed to determine their optimal alignment and, thus, the degree of identity. Preferably, the default values of 5.00 for gap weight and 0.30 for gap weight length are used. Variants referred to above may be allelic variants or any other species specific homologs, paralogs, or orthologs. Moreover, the vari- ants referred to herein include fragments or subunits of the specific sFlt-1 polypeptide or the aforementioned types of variants as long as these fragments have the essential immunological and biological properties as referred to above. Such fragments may be, e.g., degradation products of the sFlt-1 peptide. Further included are variants which differ due to posttranslational modifications such as phosphorylation or myristylation.
The term "cardiac Troponin" refers to all Troponin iso forms expressed in cells of the heart and, preferably, the subendocardial cells. These isoforms are well characterized in the art as described, e.g., in Anderson 1995, Circulation Research, vol. 76, no. 4: 681-686 and Ferrieres 1998, Clinical Chemistry, 44: 487-493. Preferably, cardiac Troponin refers to Troponin T and/or Troponin I, and, most preferably, to Troponin T. It is to be understood that isoforms of Troponins may be determined in the method of the present invention together, i.e. simultaneously or sequentially, or individually, i.e. without determining the other iso form at all. Amino acid sequences for human Troponin T and human Troponin I are disclosed in Anderson, loc cit and Ferrieres 1998, Clinical Chemistry, 44: 487-493.
The term "cardiac Troponin" encompasses also variants of the aforementioned specific Troponins, i.e., preferably, of Troponin I, and more preferably, of Troponin T. Such variants have at least the same essential biological and immunological properties as the specific cardiac Troponins. In particular, they share the same essential biological and immuno- logical properties if they are detectable by the same specific assays referred to in this specification, e.g., by ELISA Assays using polyclonal or monoclonal antibodies specifically recognizing the said cardiac Troponins. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and/or addition wherein the amino acid sequence of the variant is still, preferably, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 85%, at least about 90%, at least about 92%, at least about 95%, at least about 97%, at least about 98%, or at least about 99% identical with the amino sequence of the specific Troponin. How to determine the degree of identity is disclosed elsewhere herein.
The term "brain natriuretic peptide" comprises Brain Natiuretic Peptide (BNP)-type pep- tides and variants thereof having the same predictive potential. Natriuretic peptides according to the present invention comprise BNP-type peptides and variants thereof (see e.g. Bonow, R. O. (1996). New insights into the cardiac natriuretic peptides. Circulation 93: 1946-1950). BNP-type peptides comprise pre-proBNP, proBNP, NT-proBNP, and BNP.
The pre-pro peptide (134 amino acids in the case of pre-proBNP) comprises a short signal peptide, which is enzymatically cleaved off to release the pro peptide (108 amino acids in the case of proBNP). The pro peptide is further cleaved into an N-terminal pro peptide (NT -pro peptide, 76 amino acids in case of NT -proBNP) and the active hormone (32 amino acids in the case of BNP).
Preferred natriuretic peptides according to the present invention are NT -proBNP, BNP, and variants thereof. BNP is the active hormone and has a shorter half-life than their respective inactive counterparts NT -proBNP, BNP is metabolized in the blood, whereas NT -proBNP circulates in the blood as an intact molecule and as such is eliminated renally. The in- vivo half- life of NT -pro BNP is 120 min longer than that of BNP, which is 20 min (Smith M W, Espiner E A, Yandle T G, Charles C J, Richards A M. Delayed metabolism of human brain natriuretic peptide reflects resistance to neutral endopeptidase. J. Endocrinol. 2000; 167:239-46).
Preanalyses are more robust with NT -proBNP allowing easy transportation of the sample to a central laboratory (Mueller T, Gegenhuber A, Dieplinger B, Poelz W, Haltmayer M. Long-term stability of endogenous B-type natriuretic peptide (BNP) and amino terminal proBNP (NT -proBNP) in frozen plasma samples. Clin Chem Lab Med 2004; 42:942-4). Blood samples can be stored at room temperature for several days or may be mailed or shipped without recovery loss. In contrast, storage of BNP for 48 hours at room tempera- ture or at 4°Celsius leads to a concentration loss of at least 20% (Mueller T, Gegenhuber A, et al, Clin Chem Lab Med 2004; 42:942-4, supra; Wu A H, Packer M, Smith A, Bijou R, Fink D, Mair J, Wallentin L, Johnston N, Feldcamp C S, Haverstick D M, Ahnadi C E, Grant A, Despres N, Bluestein B, Ghani F. Analytical and clinical evaluation of the Bayer AD VI A Centaur automated B-type natriuretic peptide assay in subjects with heart failure: a multisite study. Clin Chem 2004; 50: 867-73). Therefore, depending on the time-course or properties of interest, either measurement of the active or the inactive forms of the natriuretic peptide can be advantageous. The most preferred natriuretic peptides according to the present invention are NT-proBNP or variants thereof. As briefly discussed above, the human NT-proBNP as referred to in accordance with the present invention is a polypeptide comprising, preferably, 76 amino acids in length corresponding to the N-terminal portion of the human NT-proBNP molecule. The structure of the human BNP and NT-proBNP has been described already in detail in the prior art, e.g., WO 02/089657, WO 02/083913, Bonow 1996, New Insights into the cardiac natriuretic peptides. Circulation 93: 1946-1950. Preferably, human NT-proBNP as used herein is human NT-proBNP as disclosed in EP 0 648 228 Bl . These prior art documents are herewith incorporated by reference with respect to the specific sequences of NT- proBNP and variants thereof disclosed therein.
The NT-proBNP referred to in accordance with the present invention further encompasses allelic and other variants of said specific sequence for human NT-proBNP discussed above. Specifically, envisaged are variant polypeptides which are on the amino acid level at least 60% identical, more preferably at least 70%, at least 80%, at least 90%, at least 95%, at least 98% or at least 99% identical, to human NT-proBNP, preferably, over the entire length. How to calculate the degree of identified between two sequence is described elsewhere herein.
Determining the amount of a brain natriuretic peptide, in particular of NT-proBNP, of a cardiac Troponin, in particular of Troponin T, and of sFlt-1 or any other peptide or polypeptide referred to in this specification relates to measuring the amount or concentration, preferably semi-quantitatively or quantitatively. Measuring can be done directly or indirectly. Direct measuring relates to measuring the amount or concentration of the peptide or polypeptide based on a signal which is obtained from the peptide or polypeptide itself and the intensity of which directly correlates with the number of molecules of the peptide present in the sample. Such a signal - sometimes referred to herein as intensity signal -may be obtained, e.g., by measuring an intensity value of a specific physical or chemical property of the peptide or polypeptide. Indirect measuring includes measuring of a signal obtained from a secondary component (i.e. a component not being the peptide or polypeptide itself) or a biological read out system, e.g., measurable cellular responses, ligands, labels, or enzymatic reaction products.
In accordance with the present invention, determining the amount of a peptide or polypeptide can be achieved by all known means for determining the amount of a peptide in a sample. Said means comprise immunoassay devices and methods which may utilize labelled molecules in various sandwich, competition, or other assay formats. Said assays will develop a signal which is indicative for the presence or absence of the peptide or polypeptide. Moreover, the signal strength can, preferably, be correlated directly or indirectly (e.g. reverse- proportional) to the amount of polypeptide present in a sample. Further suitable methods comprise measuring a physical or chemical property specific for the peptide or polypeptide such as its precise molecular mass or NMR spectrum. Said methods comprise, preferably, biosensors, optical devices coupled to immunoassays, biochips, analytical devices such as mass- spectrometers, NMR- analyzers, or chromatography devices. Further, methods include micro-plate ELISA-based methods, fully-automated or robotic immunoassays (available for example on ElecsysTM analyzers), CBA (an enzymatic Cobalt Binding Assay, available for example on Roche-HitachiTM analyzers), and latex agglutination assays (available for example on Roche-HitachiTM analyzers).
Preferably, determining the amount of a peptide or polypeptide comprises the steps of (a) contacting a cell capable of eliciting a cellular response the intensity of which is indicative of the amount of the peptide or polypeptide with the said peptide or polypeptide for an ad- equate period of time, (b) measuring the cellular response. For measuring cellular responses, the sample or processed sample is, preferably, added to a cell culture and an internal or external cellular response is measured. The cellular response may include the measurable expression of a reporter gene or the secretion of a substance, e.g. a peptide, polypeptide, or a small molecule. The expression or substance shall generate an intensity signal which cor- relates to the amount of the peptide or polypeptide.
Also preferably, determining the amount of a peptide or polypeptide comprises the step of measuring a specific intensity signal obtainable from the peptide or polypeptide in the sample. As described above, such a signal may be the signal intensity observed at an m/z variable specific for the peptide or polypeptide observed in mass spectra or a NMR spectrum specific for the peptide or polypeptide. Determining the amount of a peptide or polypeptide may, preferably, comprises the steps of (a) contacting the peptide with a specific ligand, (b) preferably, removing non-bound ligand and other components which may be present in the sample, (c) measuring the amount of bound ligand, i.e. the complex of the peptide and the ligand formed in step (a). According to a preferred embodiment, said steps of contacting, removing and measuring may be performed by an analyzer unit of the system disclosed herein. According to some embodiments, said steps may be performed by a single analyzer unit of said system or by more than one analyzer unit in operable communication with each other. For example, according to a specific embodiment, said system disclosed herein may include a first ana- lyzer unit for performing said steps of contacting and removing and a second analyzer unit, operably connected to said first analyzer unit by a transport unit (for example, a robotic arm), which performs said step of measuring.
The bound ligand, i.e. the ligand or the ligand/peptide complex, will generate an intensity signal which reflects the amount of peptide or polypeptide originally present in the sample. Binding according to the present invention includes both covalent and non-covalent binding. A ligand according to the present invention can be any compound, e.g., a peptide, polypeptide, nucleic acid, or small molecule, binding to the peptide or polypeptide described herein. Preferred ligands include antibodies, nucleic acids, peptides or polypeptides such as receptors or binding partners for the peptide or polypeptide and fragments thereof comprising the binding domains for the peptides, and aptamers, e.g. nucleic acid or peptide ap- tamers. Methods to prepare such ligands are well-known in the art. For example, identification and production of suitable antibodies or aptamers is also offered by commercial suppliers. The person skilled in the art is familiar with methods to develop derivatives of such ligands with higher affinity or specificity. For example, random mutations can be introduced into the nucleic acids, peptides or polypeptides. These derivatives can then be tested for binding according to screening procedures known in the art, e.g. phage display. Antibodies as referred to herein include both polyclonal and monoclonal antibodies, as well as fragments thereof, such as Fv, Fab and F(ab)2 fragments that are capable of binding anti- gen or hapten. The present invention also includes single chain antibodies and humanized hybrid antibodies wherein amino acid sequences of a non-human donor antibody exhibiting a desired antigen-specificity are combined with sequences of a human acceptor antibody. The donor sequences will usually include at least the antigen-binding amino acid residues of the donor but may comprise other structurally and/or functionally relevant ami- no acid residues of the donor antibody as well. Such hybrids can be prepared by several methods well known in the art. Preferably, the ligand or agent binds specifically to the peptide or polypeptide. Specific binding according to the present invention means that the lig- and or agent should not bind substantially to, i.e. cross-react with, another peptide, polypeptide or substance present in the sample to be analysed. Preferably, the specifically bound peptide or polypeptide should be bound with at least 3 times higher, more preferably at least 10 times higher and even more preferably at least 50 times higher affinity than any other relevant peptide or polypeptide. Non-specific binding may be tolerable, if it can still be distinguished and measured unequivocally, e.g. according to its size on a Western Blot, or by its relatively higher abundance in the sample. Binding of the ligand can be measured by any method known in the art. Preferably, said method is semi-quantitative or quantitative.
Binding of a ligand may be measured directly, e.g. by NMR or surface plasmon resonance. Measurement of the binding of a ligand, according to preferred embodiments, is performed by an analyzer unit of a system disclosed herein. Thereafter, an amount of the measured binding may be calculated by a computing device of a system disclosed herein. Second, if the ligand also serves as a substrate of an enzymatic activity of the peptide or polypeptide of interest, an enzymatic reaction product may be measured (e.g. the amount of a protease can be measured by measuring the amount of cleaved substrate, e.g. on a Western Blot). Alternatively, the ligand may exhibit enzymatic properties itself and the "ligand/peptide or polypeptide" complex or the ligand which was bound by the peptide or polypeptide, re- spectively, may be contacted with a suitable substrate allowing detection by the generation of an intensity signal. For measurement of enzymatic reaction products, preferably the amount of substrate is saturating. The substrate may also be labelled with a detectable label prior to the reaction. Preferably, the sample is contacted with the substrate for an adequate period of time. An adequate period of time refers to the time necessary for an detectable, preferably measurable, amount of product to be produced. Instead of measuring the amount of product, the time necessary for appearance of a given (e.g. detectable) amount of product can be measured. Third, the ligand may be coupled covalently or non-covalently to a label allowing detection and measurement of the ligand. Labelling may be done by direct or indirect methods. Direct labelling involves coupling of the label directly (covalently or non-covalently) to the ligand. Indirect labelling involves binding (covalently or non- covalently) of a secondary ligand to the first ligand. The secondary ligand should specifically bind to the first ligand. Said secondary ligand may be coupled with a suitable label and/or be the target (receptor) of tertiary ligand binding to the secondary ligand. The use of secondary, tertiary or even higher order ligands is often used to increase the signal. Suita- ble secondary and higher order ligands may include antibodies, secondary antibodies, and the well-known streptavidin-biotin system (Vector Laboratories, Inc.). The ligand or substrate may also be "tagged" with one or more tags as known in the art. Such tags may then be targets for higher order ligands. Suitable tags include biotin, digoxygenin, His-Tag, Glu- tathion-S-Transferase, FLAG, GFP, myc-tag, influenza A virus haemagglutinin (HA), maltose binding protein, and the like. In the case of a peptide or polypeptide, the tag is preferably at the N-terminus and/or C-terminus. Suitable labels are any labels detectable by an appropriate detection method. Typical labels include gold particles, latex beads, acridan ester, luminol, ruthenium, enzymatically active labels, radioactive labels, magnetic labels ("e.g. magnetic beads", including paramagnetic and superparamagnetic labels), and fluorescent labels. Enzymatically active labels include e.g. horseradish peroxidase, alkaline phosphatase, beta-Galactosidase, Luciferase, and derivatives thereof. Suitable substrates for detection include di-amino-benzidine (DAB), 3,3'-5,5'-tetramethylbenzidine, NBT- BCIP (4-nitro blue tetrazolium chloride and 5-bromo-4-chloro-3-indolyl-phosphate, available as ready-made stock solution from Roche Diagnostics), CDP-Star™ (Amersham Biosciences), ECF™ (Amersham Biosciences). A suitable enzyme-substrate combination may result in a coloured reaction product, fluorescence or chemiluminescence, which can be measured according to methods known in the art (e.g. using a light-sensitive film or a suitable camera system). As for measuring the enyzmatic reaction, the criteria given above apply analogously. Typical fluorescent labels include fluorescent proteins (such as GFP and its derivatives), Cy3, Cy5, Texas Red, Fluorescein, and the Alexa dyes (e.g. Alexa 568). Further fluorescent labels are available e.g. from Molecular Probes (Oregon). Also the use of quantum dots as fluorescent labels is contemplated. Typical radioactive labels include 35S, 1251, 32P, 33P and the like. A radioactive label can be detected by any method known and appropriate, e.g. a light-sensitive film or a phosphor imager. Suitable measurement methods according the present invention also include precipitation (particularly immunoprecipitation), electrochemiluminescence (electro-generated chemiluminescence), RIA (radioimmunoassay), ELISA (enzyme- linked immunosorbent assay), sandwich enzyme immune tests, electrochemiluminescence sandwich immunoassays (ECLIA), dissociation-enhanced lanthanide fluoro immuno assay (DELFIA), scintillation proximity assay (SPA), turbidimetry, nephelometry, latex-enhanced turbidimetry or nephelometry, or solid phase immune tests. Further methods known in the art (such as gel electrophoresis, 2D gel electrophoresis, SDS polyacrylamid gel electrophoresis (SDS-PAGE), Western Blotting, and mass spectrometry), can be used alone or in combination with labelling or other detection methods as described above.
Further suitable techniques for the determination of a polypeptide or peptide are described in the following. The amount of a peptide or polypeptide may be, also preferably, determined as follows: (a) contacting a solid support comprising a ligand for the peptide or polypeptide as specified above with a sample comprising the peptide or polypeptide, (b) preferably, removing unbound peptide or polypeptide as well as remaining sample material and (c) measuring the amount peptide or polypeptide which is bound to the support. Preferably, the amount of the complex of the ligand and the peptide or polypeptide formed on the solid support is measured. It will be understood that the amount of the complex formed during the determination shall represent the amount of the peptide or polypeptide originally present in the sample. The ligand is, preferably chosen from the group consisting of nucleic acids, peptides, poly- peptides, antibodies and aptamers and is, preferably, present on a solid support in immobilized form. Materials for manufacturing solid supports are well known in the art and include, inter alia, commercially available column materials, polystyrene beads, latex beads, magnetic beads, colloid metal particles, glass and/or silicon chips and surfaces, nitrocellulose strips, membranes, sheets, duracytes, wells and walls of reaction trays, plastic tubes etc. The ligand or agent may be bound to many different carriers. Examples of well-known carriers include glass, polystyrene, polyvinyl chloride, polypropylene, polyethylene, polycarbonate, dextran, nylon, amyloses, natural and modified celluloses, polyacrylamides, agaroses, and magnetite. The nature of the carrier can be either soluble or insoluble for the purposes of the invention. Suitable methods for fixing/immobilizing said ligand are well known and include, but are not limited to ionic, hydrophobic, covalent interactions and the like. It is also contemplated to use "suspension arrays" as arrays according to the present invention (Nolan 2002, Trends Biotechnol. 20(1):9-12). In such suspension arrays, the carrier, e.g. a microbead or microsphere, is present in suspension. The array consists of different microbeads or microspheres, possibly labelled, carrying different ligands. Methods of producing such arrays, for example based on solid-phase chemistry and photo-labile protective groups, are generally known (US 5,744,305).
The term "amount" as used herein encompasses the absolute amount of a polypeptide or peptide, the relative amount or concentration of the said polypeptide or peptide as well as any value or parameter which correlates thereto or can be derived therefrom. Such values or parameters comprise intensity signal values from all specific physical or chemical properties obtained from the said peptides by direct measurements, e.g., intensity values in mass spectra or NMR spectra. Moreover, encompassed are all values or parameters which are obtained by indirect measurements specified elsewhere in this description, e.g., re- sponse levels determined from biological read out systems in response to the peptides or intensity signals obtained from specifically bound ligands. It is to be understood that values correlating to the aforementioned amounts or parameters can also be obtained by all stand- ard mathematical operations. According to preferred embodiments of the subject invention, the determination of an "amount" is performed by the disclosed system, whereby a computing device determines the "amount" based on contacting and measuring steps performed by one or more analyzer units of said system.
The term "comparing" as used herein encompasses comparing the determined amount for at least one marker as referred to herein to a reference. It is to be understood that comparing as used herein refers to any kind of comparison made between the value for the amount with the reference. The comparison referred to in step (b) of the method of the present invention may be carried out manually or by a computing device (e.g., of a system disclosed herein). The value of the amount and the reference can be, e.g., compared to each other and the said comparison can be automatically carried out by a computer program executing an algorithm for the comparison. The computer program carrying out the said evaluation will provide the desired assessment in a suitable output format. For a computer assisted com- parison, the value of the determined amount may be compared to values corresponding to suitable references which are stored in a database by a computer program. The computer program may further evaluate the result of the comparison, i.e. automatically provide the desired assessment in a suitable output format. Based on the comparison of the amount determined in step a) and the reference amount, it is possible to assess whether a subject exhibiting a symptom of an acute cardiovascular event suffers from pulmonary complication, or not. For example, a result of a comparison may be given as raw data (absolute or relative amounts), and in some cases as an indicator in the form of a word, phrase, symbol, or numerical value which may be indicative of a particular diagnosis. Therefore, the reference amount is to be chosen so that either a difference or a similarity in the compared amounts allows identifying those test subjects which belong into the group of subjects having an increased risk or a decreased risk (in particular of mortality, in particular within a window period of 30 days).
Accordingly, the term "reference amount" as used herein refers to an amount which allows for assessing whether a subject suffering from pneumonia is at increased risk or decreased risk, e.g. of mortality as set forth herein elsewhere, or whether a subject shall be hospitalized or not. Thus, one embodiment, the term refers to an amount which allows assessing whether a subject suffering from pneumonia is at increased risk or decreased risk (in particular of mortality) as compared to the average risk (in particular of mortality) of a subject who has been classified with the same score, in particular according to the CURB65-Score. In another embodiment, the term refers to an amount which allows for assessing whether a subject shall be hospitalized or not. The reference amount may be used to define and establish a threshold amount. The threshold amount, preferably, allows for a rule-in and/or a rule-out diagnosis. Said rule-in and/or rule-out diagnosis may be provided by the computing device of a system disclosed herein based on said comparison of the calculated "amount" to a reference or a threshold. For example, a computing device of a system may provide an indicator, in the form of a word, symbol, or numerical value which is indicative of one of a rule-in or rule-out diagnosis. The reference amount applicable for an individual subject may vary depending on various physiological parameters such as age, gender, or subpopulation, as well as on the means used for the determination of the polypeptide or peptide referred to herein. A suitable ref- erence amount may be determined from a reference sample to be analysed together, i.e. simultaneously or subsequently, with the test sample.
Reference amounts can be calculated for a cohort of subjects (i.e. (i) a subject or group of subjects who is at increased risk of mortality and/or who shall be hospitalized as set forth herein or (ii) a subject or group of subjects who is at decreased risk of mortality and/or who shall not be hospitalized as set forth herein) based on the average or mean values for a given biomarker by applying standard statistically methods. In particular, accuracy of a test such as a method aiming to diagnose an event, or not, is best described by its receiver- operating characteristics (ROC) (see especially Zweig 1993, Clin. Chem. 39:561-577). The ROC graph is a plot of all of the sensitivity/specificity pairs resulting from continuously varying the decision threshold over the entire range of data observed. The clinical performance of a diagnostic method depends on its accuracy, i.e. its ability to correctly allocate subjects to a certain prognosis or diagnosis. The ROC plot indicates the overlap between the two distributions by plotting the sensitivity versus 1 -specificity for the complete range of thresholds suitable for making a distinction. On the y-axis is sensitivity, or the true- positive fraction which is defined as the ratio of number of true-positive test results to the product of number of true-positive and number of false-negative test results. This has also been referred to as positivity in the presence of a disease or condition. It is calculated solely from the affected subgroup. On the x-axis is the false-positive fraction, or 1 -specificity which is defined as the ratio of number of false-positive results to the product of number of true-negative and number of false-positive results. It is an index of specificity and is calculated entirely from the unaffected subgroup. Because the true- and false-positive fractions are calculated entirely separately, by using the test results from two different subgroups, the ROC plot is independent of the prevalence of the event in the cohort. Each point on the ROC plot represents a sensitivity/-specificity pair corresponding to a particular decision threshold. A test with perfect discrimination (no overlap in the two distributions of results) has an ROC plot that passes through the upper left corner, where the true-positive fraction is 1.0, or 100% (perfect sensitivity), and the false-positive fraction is 0 (perfect specificity). The theoretical plot for a test with no discrimination (identical distributions of results for the two groups) is a 45° diagonal line from the lower left corner to the upper right corner. Most plots fall in between these two extremes. (If the ROC plot falls completely below the 45° diagonal, this is easily remedied by reversing the criterion for "positivity" from "greater than" to "less than" or vice versa.) Qualitatively, the closer the plot is to the upper left corner, the higher the overall accuracy of the test. Dependent on a desired confidence interval, a threshold can be derived from the ROC curve allowing for the diagnosis or prediction for a given event with a proper balance of sensitivity and specificity, respectively. Ac- cordingly, the reference to be used for the aforementioned method of the present invention, i.e. a threshold which allows to discriminate between subjects suffering from a pulmonary complication, or not, can be generated, preferably, by establishing a ROC for said cohort as described above and deriving a threshold amount therefrom. In an embodiment, the reference amount may be derived from
(i) a subject who has been classified with the same score (as the test subject) based on the clinical prediction rule and being known to be at increased risk of mortality as compared to the average risk of mortality of a subject who has been classified with the same score, or (ii) a subject who has been classified with the same score based on the clinical prediction rule and being known to be at decreased risk of mortality as compared to the average risk of a subject who has been classified with the same score.
Preferably, the subject in i) has been classified as low risk subject based on the clinical prediction rule (for the scores for low risks subjects, see table 1, column "low risk"). Preferably, the subject in ii) has been classified a moderate risk subject based on the clinical predication rule (for the scores for moderate risk subjects, see table 1, column "moderate risk"). Thus, in an embodiment, the (test) subject has been classified as low risk subject based on the clinical prediction rule, wherein the reference amount(s) is (are) derived from a subject who has been classified as low risk subject based on said clinical prediction rule, said subject being known to be at increased risk of mortality as compared to the average risk of mortality of a subject who has been classified with the same score, wherein an increased amount (increased amounts) of the at least one marker as set forth herein in the sample from the (test) subject as compared to the reference amount(s), or an amount (amounts) of the at least one marker which is (are) essentially the same as compared to the reference amount(s) indicates that the subject has an increased risk of mortality as compared to the average risk of mortality of a subject who has been classified with the same score.
Thus, in an embodiment, the (test) subject has been classified as moderate risk subject based on the clinical prediction rule, wherein the reference amount(s) is (are) derived from a subject who has been classified as moderate risk subject based on said clinical prediction rule, said subject being known to be at decreased risk of mortality as compared to the average risk of mortality of a subject who has been classified with the same score, wherein an decreased amount (decreased amounts) of the at least one marker as set forth herein in the sample from the (test) subject as compared to the reference amount(s), or an amount (amounts) of the at least one marker which is (are) essentially the same as compared to the reference amount (s) indicates that the subject has a decreased risk of mortality as compared to the average risk of mortality of a subject who has been classified with the same score.
In another embodiment, the reference amount may be derived from a
(i) a subject who has been classified with the same score (as the test subject) based on the clinical prediction rule, wherein the subject has been admitted to hospital, or
(ii) a subject who has been classified with the same score based on the clinical prediction rule, wherein the subject has not been admitted to hospital, or has been discharged from hospital.
Preferably, the subject in i) has been classified as low risk subject based on the clinical prediction rule (see table 1, "low risk"). Preferably, the subject in ii) has been classified a moderate risk subject based on the clinical predication rule (see table 1, "moderate risk").
Thus, in an embodiment, the (test) subject has been classified as low risk subject based on the clinical prediction rule, wherein the reference amount(s) is (are) derived from a subject who has been classified as low risk subject based on said clinical prediction rule, wherein the subject has been admitted to hospital, wherein an increased amount (increased amounts) of at least one marker as set forth herein in the sample from the (test) subject as compared to the reference amount(s), or an amount (amounts) of the at least one marker which is (are) essentially the same as compared to the reference amount (s) indicates that the subject shall be hospitalized.
Thus, in an embodiment, the (test) subject has been classified as moderate risk subject based on the clinical prediction rule, in particular, wherein the subject has not been admit- ted to hospital, or wherein the subject has been discharged from hospital, wherein the reference amount(s) is (are) derived from a subject who has been classified as moderate risk subject based on said clinical prediction rule, wherein an decreased amount (decreased amounts) of at least one marker as set forth herein in the sample from the (test) subject as compared to the reference amount(s), or an amount(s) of the at least one marker which is (are) essentially the same as compared to the reference amount indicates that the subject shall not be hospitalized or shall be discharged from hospital.
Preferably, the subject to be tested (herein also referred to as the "test subject") and the subject from whom the reference amount(s) is (are) derived (herein also referred to as the "reference subject") have been classified with the same score based on the clinical prediction rule.
If the reference amount(s) is (are) derived from a subject who has been classified as low risk subject based on the clinical prediction rule as set forth herein above, preferred reference amounts are as follows:
Preferred reference amounts for a brain natriuretic peptide, in particular of NT-proBNP, are within a range of 1000 to 2300 pg/ml, in particular within a range of 1300 to 2000 pg/ml. Preferably, the reference amount is 2000 pg/ml, more preferably, 1200 pg/ml and, most preferably, 1600 pg/ml.
Preferred reference amounts for a cardiac Troponin, in particular of Troponin T, are within a range of 10 to 25 pg/ml, in particular within a range of 15 to 25 pg/ml. Preferably, the reference amount is 10 pg/ml, more preferably, 15 pg/ml and, most preferably, 20 pg/ml.
Preferred reference amounts for sFlt-1, are within a range of 120 to 200 pg/ml, in particular within a range of 130 to 180 pg/ml. Preferably, the reference amount is 130 pg/ml, more preferably, 170 pg/ml and, most preferably, 150 pg/ml.
If the reference amount(s) is (are) derived from a subject who has been classified as moderate risk subject based on the clinical prediction rule as set forth herein above, preferred reference amounts are as follows: Preferred reference amounts for a brain natriuretic peptide, in particular of NT-proBNP, are within a range of 100 to 400 pg/ml, in particular within a range 200 to 400 of pg/ml. Preferably, the reference amount is 400 pg/ml, more preferably, 300 pg/ml and, most preferably, 200 pg/ml.
Preferred reference amounts for a cardiac Troponin, in particular of Troponin T, are within a range of 1 to 9 pg/ml, in particular within a range of 3 to 8 pg/ml. Preferably, the reference amount is 8 pg/ml, more preferably, 6 pg/ml and, most preferably, 3 pg/ml.
Preferred reference amounts for a sFlt-1 , are within a range of 60 to 100 pg/ml, in particular within a range of 70 to 90 pg/ml. Preferably, the reference amount is 90 pg/ml, more preferably, 80 pg/ml and, most preferably, 70 pg/ml.
In an aspect of the invention, a method for establishing an aid for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia, is contemplated, said method comprising:
a) determining the amount of at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 (i) bringing the sample into contact with a detection agent (detection agents) that specifically bind(s) to said at least one marker for a time sufficient to allow for the formation of a complex of the said detection agent and the at least one marker from the sample, (ii) measuring the amount of the formed complex, wherein the said amount of the formed complex is proportional to the amount of the at least one marker present in the sample, and (iii) transforming the amount of the formed complex into an amount of the at least one marker reflecting the amount of the at least one marker present in the sample; b) comparing said amount to a reference; and
c) establishing an aid for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia based on the result of the comparison made in step b).
In another aspect of the invention, a system for establishing an aid for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia, is contemplated, comprising:
a) an analyzer unit configured to bringing the sample into contact with a detection agent (detection agents) that specifically bind(s) to said at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 for a time sufficient to allow for the formation of a complex of the said detection agent and the at least one marker from the sample, b) an analyzer unit configured to measure the amount of the formed complex, wherein the said amount of the formed complex is proportional to the amount of the at least one marker present in the sample,
c) a computing device having a processor and in operable communication with said analysis units, and
d) a non-transient machine readable media including a plurality of instructions executable by the processor, the instructions, when executed transform the amount of the formed complex into an amount of the at least one marker reflecting the amount of the at least one marker present in the sample, compare said amount to a reference, and establish an aid for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia based on the result of said comparison to said reference.
A suitable detection agent may be, in an aspect, an antibody which is specifically binds to the at least one marker, i.e. a detection agent which binds to a brain natriuretic peptide, a cardiac troponin or to sFlt-1, in a sample of a subject to be investigated by the method of the invention. Another detection agent that can be applied, in an aspect, may be an apta- mere which specifically binds to the at least one marker in the sample. In yet an aspect the, sample is removed from the complex formed between the detection agent and the at least one marker prior to the measurement of the amount of formed complex. Accordingly, in an aspect, the detection agent may be immobilized on a solid support. In yet an aspect, the sample can be removed from the formed complex on the solid support by applying a washing solution. The formed complex shall be proportional to the amount of the at least one marker present in the sample. It will be understood that the specificity and/or sensitivity of the detection agent to be applied defines the degree of proportion of at least one marker comprised in the sample which is capable of being specifically bound. Further details on how the determination can be carried out are also found elsewhere herein. The amount of formed complex shall be transformed into an amount of at least one marker reflecting the amount indeed present in the sample. Such an amount, in an aspect, may be essentially the amount present in the sample or may be, in another aspect, an amount which is a certain proportion thereof due to the relationship between the formed complex and the amount present in the original sample.
In yet an aspect of the aforementioned method, step a) may be carried out by an analyzer unit (or analyzing unit), in an aspect, an analyzer unit (or analyzing unit) as defined elsewhere herein. In an aspect of the method of the invention, the amount(s) determined in step a) is (are) compared to a reference. In an aspect, the reference is a reference as defined elsewhere herein. In yet another aspect, the reference takes into account the proportional relationship between the measured amount of complex and the amount present in the original sample. Thus, the references applied in an aspect of the method of the invention are artificial references which are adopted to reflect the limitations of the detection agent that has been used. In another aspect, said relationship can be also taken into account when carrying out the comparison, e.g., by including a normalization and/or correction calculation step for the determined amount prior to actually comparing the value of the determined amount and the reference. Again, the normalization and/or correction calculation step for the determined amount adopts the comparison step such that the limitations of the detection agent that has been used are reflected properly. In an aspect, the comparison is carried out automatically, e.g., assisted by a computer system or the like. The aid for optimizing a risk assessment is established based on the comparison carried out in step b) by allocating the subject either into a group of subjects having an increased risk or decreased risk as set forth herein elsewhere. As discussed elsewhere herein already, the allocation of the investigated subject must not be correct in 100% of the investigated cases. Moreover, the groups of subjects into which the investigated subject is allocated are artifi- cial groups in that they are established based on statistical considerations, i.e. a certain preselected degree of likelihood based on which the method of the invention shall operate. In an aspect of the invention, the aid for optimizing a risk assessment is established automatically, e.g., assisted by a computing device or the like, as described and disclosed herein. In an aspect of the method of the invention, said method further comprises a step of recommending and/or managing the subject according to the result established in step c) as set forth elsewhere herein in detail, and/or adapting intensiveness of disease monitoring.
In an aspect of the aforementioned method, steps b) and/or c) are carried out by one or more analyzer units as set forth elsewhere herein.
The present invention also relates to the use of i) at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 or ii) of a detection agent which specifically binds to a natriuretic peptide, and/or of a detection agent which specifically binds to a cardiac Troponin, and/or of a detection agent which specifically binds to sFlt-1, in a sample of a subject suffering from pneumonia for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia. The present invention also relates to the use of i) at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1, or ii) of a detection agent which specifically binds to a natriuretic peptide, and/or of a detection agent which specifically binds to a cardiac Troponin, and/or of a detection agent which specifically binds to sFlt-1, for the manufacture of a pharmaceutical or diagnostic composition for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia.
The term "detection agent" as used herein refers to an agent that is capable of specifically recognizing and binding to the biomarker polypeptide(s) present in a sample. Moreover, the said agent shall allow for direct or indirect detection of the complex formed by the said agent and the biomarker. Direct detection can be achieved by including into the agent a detectable label. Indirect labelling may be achieved by a further agent that specifically binds to the complex comprising the biomarker and the detection agent wherein the said further agent is than capable of generating a detectable signal. Suitable compounds which can be used as detection agents are well known in the art. Preferably, the detection agent is an antibody or aptamere which specifically binds to the biomarker. The term "antibody" has been described elsewhere herein.
According to a preferred embodiment of the present invention, a device adapted for carrying out a method of the invention is provided comprising
a) an analyzer unit (or analyzing unit) comprising a detection agent (or agents) which specifically bind(s) to a marker selected from the group consisting of a brain natriuretic peptide, a cardiac troponin, and sFlt-1, said unit being adapted for determining the amount(s) of the marker(s) in a sample of a subject suffering from pneumonia; and
b) an analyzer unit (or evaluation unit) for comparing the determined amount(s) with reference amount(s), whereby a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia is optimized, said unit comprising a database with a reference amount (or amounts) and a computer-implemented algorithm for carrying out the comparison.
Preferred reference amounts and algorithms are disclosed elsewhere herein.
The term "device" as used herein, preferably, relates to a system comprising the aforementioned units operatively linked to each other as to allow the diagnosis or monitoring according to the methods of the invention. Preferred detection agents which can be used for the analysing unit are disclosed elsewhere herein. The analysing unit, preferably, compris- es said detection agents in immobilized form on a solid support which is to be contacted to the sample comprising the biomarkers the amount of which is to be determined. Moreover, the analysing unit can also comprise a detector which determines the amount of detection agent which is specifically bound to the biomarker(s). The determined amount can be transmitted to the evaluation unit. Said evaluation unit comprises a data processing element, such as a computer, with an implemented algorithm for carrying out a comparison between the determined amount and a suitable reference. Suitable references are either derived from a subject or group of subjects as defined above in context with the method of the present invention. The results may be given as output of parametric diagnostic raw da- ta, preferably, as absolute or relative amounts. It is to be understood that these data will need interpretation by the clinician. However, also envisage are expert system devices wherein the output comprises processed diagnostic raw data the interpretation of which does not require a specialized clinician. A preferred embodiment of the instant disclosure includes a system for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia. Examples of systems include clinical chemistry analyzers, coagulation chemistry analyzers, immunochemistry analyzers, urine analyzers, nucleic acid analyzers, used to detect the result of chemical or biological reactions or to monitor the progress of chemical or biologi- cal reactions. More specifically, exemplary systems of the instant disclosure may include Roche Elecsys™ Systems and Cobas® e Immunoassay Analyzers, Abbott Architect™ and Axsym™ Analyzers, Siemens Centaur™ and Immulite™ Analyzers, and Beckman Coulter UniCel™ and Acess™ Analyzers, or the like. Embodiments of the system may include one or more analyzer units utilized for practicing the subject disclosure. The analyzer units of the system disclosed herein are in operable communication with the computing device disclosed herein through any of a wired connection, Bluetooth, LANS, or wireless signal, as are known. Additionally, according to the instant disclosure, an analyzer unit may comprise a stand-alone apparatus, or module with- in a larger instrument, which performs one or both of the detection, e.g. qualitative and/or quantitative evaluation of samples for diagnostic purpose. For example, an analyzer unit may perform or assist with the pipetting, dosing, mixing of samples and/or reagents. An analyzer unit may comprise a reagent holding unit for holding reagents to perform the assays. Reagents may be arranged for example in the form of containers or cassettes contain- ing individual reagents or group of reagents, placed in appropriate receptacles or positions within a storage compartment or conveyor. Detection reagents may also be in immobilized form on a solid support which are contacted with the sample. Further, an analyzer unit may include a process and/or detection component which is optimizable for specific analysis.
According to some embodiments, an analyzer unit may be configured for optical detection of an analyte, for example a marker, with a sample. An exemplary analyzer unit configured for optical detection comprises a device configured for converting electro -magnetic energy into an electrical signal, which includes both single and multi-element or array optical detectors. According to the present disclosure, an optical detector is capable of monitoring an optical electro -magnetic signal and providing an electrical outlet signal or re- sponse signal relative to a baseline signal indicative of the presence and/or concentration of an analyte in a sample being located in an optical path. Such devices may also include, for example, photodiodes, including avalanche photodiodes, phototransistors, photo conductive detectors, linear sensor arrays, CCD detectors, CMOS detectors, including CMOS array detectors, photomultipliers, and photomultiplier arrays. According to certain embodiments, an optical detector, such as a photodiode or photomultiplier, may contain additional signal conditioning or processing electronics. For example, an optical detector may include at least one pre-amplifier, electronic filter, or integrated circuit. Suitable pre-preamplifiers include, for example, integrating, transimpedance, and current gain (current mirror) preamplifiers.
Additionally, one or more analyzer unit according to the instant disclosure may comprise a light source for emitting light. For example, a light source of an analyzer unit may consist of at least one light emitting element (such as a light emitting diode, an electric powered radiation source such as an incandescent lamp, an electroluminescent lamp, a gas discharge lamp, a high-intensity discharge lamp, a laser) for measuring analyte concentrations with a sample being tested or for enabling an energy transfer (for example, through florescent resonance energy transfer or catalyzing an enzyme).
Further, an analyzer unit of the system may include one or more incubation units (for ex- ample, for maintaining a sample or a reagent at a specified temperature or temperature range). In some embodiments, an analyzer unit may include a thermocycler, include a real-time thermocycler, for subjecting a sample to repeated temperature cycles and monitoring a change in the amount of an amplification product with the sample. Additionally, an analyzer unit of the system disclosed herein may comprise, or be operationally connected to, a reaction vessel or cuvette feeding unit. Exemplary feeding units include liquid processing units, such as a pipetting unit, to deliver samples and/or reagents to the reaction vessels. The pipetting unit may comprise a reusable washable needle, e.g. a steel needle, or disposable pipette tips. The analyzer unit may further comprise one or more mixing units, for example a shaker to shake a cuvette comprising a liquid, or a mixing paddle to mix liquids in a cuvette, or reagent container.
It follows from the above that according to some embodiments of the instant disclosure, portions of some steps of methods disclosed and described herein may be performed by a computing device. A computing device may be a general purpose computer or a portable computing device, for example. It should also be understood that multiple computing devices may be used together, such as over a network or other methods of transferring data, for performing one or more steps of the methods disclosed herein. Exemplary computing devices include desktop computers, laptop computers, personal data assistants ("PDA"), such as BLACKBERRY brand devices, cellular devices, tablet computers, servers, and the like. In general, a computing device comprises a processor capable of executing a plurality of instructions (such as a program of software).
A computing device has access to a memory. A memory is a computer readable medium and may comprise a single storage device or multiple storage devices, located either locally with the computing device or accessible to the computing device across a network, for example. Computer-readable media may be any available media that can be accessed by the computing device and includes both volatile and non- volatile media. Further, computer readable-media may be one or both of removable and non-removable media. By way of example, and not limitation, computer-readable media may comprise computer storage media. Exemplary computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or any other memory technology, CD-ROM, Digital Versatile Disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used for storing a plurality of instructions capable of being accessed by the computing device and exe- cuted by the processor of the computing device.
According to embodiments of the instant disclosure, software may include instructions which, when executed by a processor of the computing device, may perform one or more steps of the methods disclosed herein. Some of the instructions may be adapted to produce signals that control operation of other machines and thus may operate through those control signals to transform materials far removed from the computer itself. These descriptions and representations are the means used by those skilled in the art of data processing, for example, to most effectively convey the substance of their work to others skilled in the art.
The plurality of instructions may also comprise an algorithm which is generally conceived to be a self-consistent sequence of steps leading to a desired result. These steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic pulses or signals capable of being stored, transferred, transformed, combined, compared, and otherwise manipulated. It proves convenient at times, principally for reasons of common usage, to refer to these sig- nals as values, characters, display data, numbers, or the like as a reference to the physical items or manifestations in which such signals are embodied or expressed. It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely used here as convenient labels applied to these quantities. According to some embodiments of the instant disclosure, an algorithm for carrying out a comparison between a determined amount of one or more markers disclosed herein, and a suitable reference, is embodied and performed by executing the instructions. The results may be given as output of parametric diagnostic raw data or as absolute or relative amounts. According to various embodiments of the system disclosed herein, a "diagnosis" may be provided by the computing device of a system disclosed herein based on said comparison of the calculated "amount" to a reference or a threshold. For example, a computing device of a system may provide an indicator, in the form of a word, symbol, or numerical value which is indicative of a particular diagnosis.
The computing device may also have access to an output device. Exemplary output devices include fax machines, displays, printers, and files, for example. According to some embodiments of the present disclosure, a computing device may perform one or more steps of a method disclosed herein, and thereafter provide an output, via an output device, relating to a result, indication, ratio or other factor of the method.
Finally, the invention pertains to a kit adapted for carrying out a method of the present in- vention comprising a detection agent which specifically binds to a marker selected from the group consisting of a brain natriuretic peptide, a cardiac troponin, and sFlt-1 , reference standards as well as instructions for carrying out the said method.
The term "kit" as used herein refers to a collection of the aforementioned components, preferably, provided in separately or within a single container. The container also comprises instructions for carrying out the method of the present invention. These instructions may be in the form of a manual or may be provided by a computer program code which is capa- ble of carrying out the comparisons referred to in the methods of the present invention and to establish a diagnosis accordingly when implemented on a computer or a data processing device. The computer program code may be provided on a data storage medium or device such as a optical storage medium (e.g., a Compact Disc) or directly on a computer or data processing device. Further, the kit shall comprise at least one standard for a reference as defined herein above, i.e. a solution with a pre-defined amount for the SP-B peptide polypeptide representing a reference amount. Such a standard may represent, e.g., the amount of SP-B peptide from a subject or group of subjects exhibiting a symptom of an acute cardiovascular event and suffering from a pulmonary complication or a subject or group of subjects exhibiting a symptom of an acute cardiovascular event and not suffering from a pulmonary complication or a clinically apparently healthy subject or group thereof.
In some embodiments, a kit disclosed herein includes at least one component or a packaged combination of components for practicing a disclosed method. By "packaged combi- nation" it is meant that the kits provide a single package that contains a combination of one or more components, such as probes (for example, an antibody), controls, buffers, reagents (for example, conjugate and/or substrate) instructions, and the like, as disclosed herein. A kit containing a single container is also included within the definition of "packaged combination." In some embodiments, the kits include at least one probe, for example an anti- body (having specific affinity for an epitope of a biomarker as disclosed herein. For example, the kits may include an antibody that is labelled with a fluorophore or an antibody that is a member of a fusion protein. In the kit, the probe may be immobilized, and may be immobilised in a specific conformation. For example, an immobilized probe may be provided in a kit to specifically bind target protein, to detect target protein in a sample, and/or to remove target protein from a sample.
According to some embodiments, kits include at least one probe, which may be immobilized, in at least one container. Kits may also include multiple probes, optionally immobilized, in one or more containers. For example, the multiple probes may be present in a sin- gle container or in separate containers, for example, wherein each container contains a single probe.
In some embodiments, a kit may include one or more non-immobilized probe and one or more solid support that does or does not include an immobilized probe. Some such embod- iments may comprise some or all of the reagents and supplies needed for immobilizing one or more probes to the solid support, or some or all of the reagents and supplies needed for binding of immobilized probes to specific proteins within a sample. In certain embodiments, a single probe (including multiple copies of the same probe) may be immobilized on a single solid support and provided in a single container. In other embodiments, two or more probes, each specific for a different target protein or a different form of a single target protein (such as a specific epitope), a provided in a single container. In some such embodiments, an immobilized probe may be provided in multiple different containers (e.g., in single-use form), or multiple immobilized probes may be provided in multiple different containers. In further embodiments, the probes may be immobilized on multiple different type of solid supports. Any combination of immobilized probe(s) and container(s) is contemplated for the kits disclosed herein, and any combination thereof may be selected to achieve a suitable kit for a desired use.
A container of the kits may be any container that is suitable for packaging and/or containing one or more components disclosed herein, including for example probes (for example, an antibody), controls, buffers, and reagents (for example, conjugate and/or substrate). Suitable materials include, but are not limited to, glass, plastic, cardboard or other paper product, wood, metal, and any alloy thereof. In some embodiments, the container may completely encase an immobilized probe(s) or may simply cover the probe to minimize contamination by dust, oils, etc., and expose to light. In some further embodiments, he kits may comprise a single container or multiple containers, and where multiple containers are present, each container may be the same as all other containers, different than others, or different than some but not all other containers.
All references cited in this specification are herewith incorporated by reference with re- spect to their entire disclosure content and the disclosure content specifically mentioned in this specification.
FIGURES
Figure 1 shows a ROC curve and statistical analysis thereof for NT-proBNP comparing CURB65 0 versus CURB65 3 and 4
Figure 2 shows a ROC curve and statistical analysis thereof for NT-proBNP comparing CURB65 0 and 1 versus CURB65 2 and 3 Figure 3 shows a ROC curve and statistical analysis thereof for Troponin T comparing CURB65 0 versus CURB65 3 and 4
Figure 4 shows a ROC curve and statistical analysis thereof for Troponin T comparing CURB65 0 and 1 versus CURB65 2, 3 and 4
Figure 5 shows a ROC curve and statistical analysis thereof for sFlt-1 comparing CURB65 0 versus CURB65 3 and 4 Figure 6 shows a ROC curve and statistical analysis thereof for sFlt-1 comparing CURB65 0 and 1 versus CURB65 2, 3 and 4
EXAMPLES
The following Examples shall merely illustrate the invention. They shall not be construed, whatsoever, to limit the scope of the invention.
Example 1 : Patient cohorts
A total of 84 subjects with pneumonia confirmed by chest x ray were included into the study, they also received an ECHO in order to identify pre-existing heart failure. In addition blood was drawn for laboratory testing. A total of 48 patients with chronic artery disease and with and without signs of heart failure were included into the study to form a reference group. All patients were classified according to the NYHA classification and their LVEF was also determined.
Example 2: Determination of blood levels of sFlt-1, Troponin T and NT-proBNP
Blood levels of sFLTl, Troponin T and NT-proBNP were determined using the commercially available immunoassays In particular, the following assays have been used. sFlt-1 and NT-proBNP were determined with sandwich immuno-assays using analyzers from Roche/Hitachi, Elecsys or COBAS e-series. The assays comprise two monoclonal antibodies specific for the respective peptide. The first of these iv biotinylated and the second one in labelled with a Tris(2,2'-bibyridyl)ruthemium (Il)-complex. In a first incubation step both antibodies are incubated with the sample. A sandwich complex comprising the peptide to be determined and the two different antibodies is formed. In a next incubation step streptavidin-coated beads are added to this complex. The beads bind the sandwich complexes. The reaction mixture is then aspirated into a measuring cell where the beads are magnetically captured on the surface of the electrode. The application of a voltage then induces a chemiluminescent emission from the ruthenium complex which is measured by a photomultiplier. The emitted amount of light is dependent on the amount of sandwich complexes on the electrode. sFlt-1 amounts between 10 to 85,000 pg/ml, and NT-proBNP amounts between 2 pg/ml and 35,000 pg/ml can be measured.
Troponin T (hsTNT) was also determined using the aforementioned automatic analysers. The test followed the same test principles as described for NT -pro BNP. The high sensitivity Troponin T test used in this study has a sensitivity of 1 pg/ml and can be used on ELECSYS 2010 as well as on COB AS e 411 or an COB AS e 601 analysers.
Example 3: Results
Patients were separated into CURB65 Scores and the results of chest X-ray and ECHO (LVEF) was assigned to this score.
CURB65 0 1 2 3
N=89 14 19 46 10
Chest x ray
0 6 10 4 1 8 19 3 2 2 5 3 3 2 5 0
LVEF
Above 60 % 4 9 5 40 - 60 % 1 11 1 20 - 40 % 5 5 2 Below 20 % 1 3 0 LVEF was not available from all patients. As can be seen, extent of pulmonary infiltrates and pre-existing heart failure (LVEF) was distributed across all CURB65 scores. and did not add to the assessment of severity of pneumonia but adds to the identification of preexisting heart failure.
In order to obtain further insight which markers could identify low or high risk patients a variety of markers were analysed believed to present relevant information. This is shown in the Table below (units: proSP-B, C-fragment of proSP-B: ng/ml, CRP: mg/dl, NT- proBNP, Troponin T and sFlt-1 : pg/ml).
CURB65 Score 0 1 2 3
N=89 14 19 46 10
Pro SP-B 59 146 168 134
(40-113) (90-287) (93 -279) (100-250)
C frag pro SP-B 94 417 400 354
(66-307) (180-808) (207-791) (217-490)
NT-pro BNP 86 1388 2375 5917
(67- 189) (405 - 3905) (582 - 5099) (1659 - 8810) CRP 99 96 72 89
(64-81) (86- 137) (82- 127) (92- 158)
Troponin T 0 19 24 61
(0-4) (8-50) ( 13- 37) (17-66) sFltl 69 95 102 133
(64-81) (86- 137) (82- 127) (92- 158)
LVEF (n)
Above 60% 13 11 25 9
40-60 % 0 3 11 20-40 % 0 5 10
Below 20% 1 0 0 Hospital admission: 8 10 21 5
(university hospital/other)
Discharged 6 9 25 5
(= sent home)
30 d mortality 0 0 3 1
As can be seen from the Table, there were different categories of markers, such as those without any significant information (CRP), markers that could identify low risk patients but did not differentiate risk categories (pro-SP-B, c fragment pro SP-B) and markers that clearly increased with CURB65 score, these markers included NT -pro BNP, sensitive Troponin T and sFlTl . Currently patients presenting with CURB65 0 and 1 are recommended to be treated as outpatients and patients meeting the criteria of CURB65 2 to 4 are believed to be treated in the hospital.
However, a ROC analysis was done for NT -pro BNP, troponin T and sFlTl comparing CURB65 0 vs 2/3 and CURB65 1/2 vs 3/4. The results are shown in Figures 1 - 6.
As can be seen form the Figures discrimination between groups worsened when CURB65 Scorel was added to Score 0. In order to further elucidate the role of biomarkers to add to the CURB65 Score reference values were obtained from heart failure patients that did not suffer from pneumonia or other acute infections.
In order to determine significant reference values the median value of patients presenting with chronic artery disease and with and without heart failure were taken. Reference was taken from patients with NYHA class II and impaired ejection fraction and from NYHA class III patients with impaired LVEF (below 60 %).. They were the predominant groups in their categories: The median obtained was as follows:
NT-pro BNP Troponin T sFlTl NHYA II, LVEF below 60 % 396 pg/ml 9 pg/ml 107 pg/ml NYHA III LVEF below 60 % 1576 g/ml 12 pg/ml 150 pg/ml
These reference values were taken and compared to the values obtained in pneumonia patients with the result shown below:
CURB65 0 1 2 3
N = 89 14 19 46 10
NT-pro BNP
below 400 pg/ml 11 5 9 3
400 - 1600 pg/ml 2 6 11 1
Above 1600 pg/ml 1 8 26 7
Troponin T
Below 9 pg/ml 13 5 9 1
9 - 12 pg/ml 0 2 3 0
Above 12 pg/ml 1 12 34 9 sFlTl
below 105 pg/ml 13 11 27 3
105 - 150 pg/ml 1 5 12 3
Above 150 pg/ml 0 3 7 4
This further assessment confirms the ROC analysis in CURB65 results of Score 0, there is only 1 patient with significantly abnormal cardiac function (who has a history of heart failure).
In contrast in CURB65 Scores 1, 2 and 3 there are based on cardiac markers a significant number of false negatives (in CURB Score 1 with highly elevated NT -pro BNP and Troponin T preferably) and a significant number of false positives ( in CURB65 Scores 2 and 3 with "low" cardiac markers, preferably NT - pro BNP and troponin T). Thus the introduction of cardiac markers improves the CURB65 Score (probably because of "unspecific- ity" of the CURB65 signs). Example 4:
72 year old male who was previously healthy presents with pneumonia and somnolence, systolic blood pressure was 110 mmHg, breathing rate is 28/min. He is classified as CURB65 class II, his NT -pro BNP is 265 pg/ml, Troponin T was 6 pg/ml and sFlTl was 68 pg/ml.
He is reclassified to CURB Class I, given fluid because he is exsiccated, he condition improves and he is discharged. A 66 year old male with a history of heart failure presents with pneumonia, systolic blood pressure is 120 mmHg, the breathing rate is 25/min and he has no somnia. He is classified as CURB Class I, his NT-pro BNP is 2320 pg/ml, Troponin T is 14 pg/ml and sFlTl is 104 pg/ml. He is admitted to the hospital. A 56 year old patient with pneumonia and normal vigilance, systolic blood pressure of 85 mmHg, respiratory rate of 26/min is classified as CURB65 Score 1. His NT -pro BNP is 3120 pg/ml, his Troponin T is 24 pg/ml and his sFltl is 92 pg/ml. He is reclassified to CURB65 score II and admitted to hospital. A cardiovascular examination reveals a LVEF below 20% and thus heart failure which has not been recognized before.
Conclusion:
Patients with community acquired pneumonia are currently assessed using Scoring systems such as the CURB65 score to identify those to be admitted to the hospital and those to be discharged. The above recommendation relies on the assessment of 30 day mortality of these patients. The criteria used for this assessment are primarily clinical (vigilance, blood pressure, breathing rate and kidney function) as well as general risk criteria (age).The validity of these criteria has been questioned. As patients with pre-existing heart disease are at increased risk of pneumonia, this requires consideration in decision making. A shown here specifically a subgroup of patients with CURB65 class 1 had evidence of cardiac dysfunction compatible to patients with NYHA class III in patients with heart failure with without pneumonia, similarly a subgroup of patients with CURB65 class II and III had only evidence of moderate cardiac dysfunction which was below those with heart failure without pneumonia and NYHA Class II. Thus the addition of NT -pro BNP as a marker of cardiac function, Troponin T as a marker of cardiac necrosis and sFltl as a marker of ischemia is able to covert patients from low risk (CURB class I) to high risk patients and conversely high risk patients (CURB II and III) to low risk patients and thus to correct classification for admission and discharge.

Claims

Claims
A method for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia, comprising the steps of
a. determining the amount of at least one marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 in a sample from a subject suffering from pneumonia, and b. comparing the amount as determined in step a) with a reference amount, thereby optimizing the risk prediction based on the clinical prediction rule for classifying subjects with pneumonia.
The method of claim 1, wherein the clinical prediction rule for classifying subjects with pneumonia is selected from the CURB65 Score, the CRB-65 Score, the CURB Score, the APACHE II Score, and the PSI Score.
The method of claims 1 and 2, wherein the sample is a blood, serum or plasma sample.
The method of any one of claims 1 to 3, wherein the risk assessment is the assessment whether the subject is admitted to hospital or not.
The method of claim 4, wherein the subject has been classified as low risk subject based on the clinical prediction rule, and wherein an amount of the at least one marker in the sample from the subject which is larger than the reference amount indicates that the subject shall be admitted to hospital.
The method of claim 5, wherein the subject who has been classified as low risk subject has been classified with a CURB-65 Score of 0 or 1, with a CRB-65 Score of 0, with a CURB Score of 0, with an APACHE II Score between 0 and 9, or with a PSI Score of I or II.
7. The method of claim 4, wherein the subject has been classified as moderate risk subject based on the clinical prediction rule, and wherein an amount of the at least one marker in the sample from the subject which is lower than the reference amount indicates that the subject shall not be admitted to hospital or shall be discharged from hospital.
8. The method of claim 7, wherein the subject who has been classified as moderate risk subject has been classified with a CURB-65 Score of 2 or 3, with a CRB-65 Score of 1 or 2, with a CURB Score of 1 or 2, with an APACHE II Score between 10 and 14, or with a PSI Score of III.
9. The method of any one of claims 1 to 3, wherein the risk assessment is the prediction of the risk of mortality.
10. The method of claim 4, wherein the subject has been classified as low risk subject based on the clinical prediction rule, and wherein an amount of the at least one marker in the sample from the subject which is larger than the reference amount indicates that the subject is at increased risk of mortality as compared to the average risk of mortality of a subject classified as low risk subject.
11. The method of claim 4, wherein the subject is classified as moderate risk subject based on the clinical prediction rule, and wherein an amount of the at least one marker in the sample from the subject which is lower than the reference amount indicates that the subject is at reduced risk of mortality as compared to the average risk of mortality of a subject classified as moderate risk subject.
12. The method of any one of claims 1 to 11, comprising the determination of the amounts of the following marker combinations:
a. sFlt-1 and a brain natriuretic peptide,
b. sFlt-1 and cardiac Troponin,
c. a brain natriuretic peptide and a cardiac Troponin, or
d. sFlt-1, a brain natriuretic peptide, and a cardiac Troponin.
13. The method of any one of claims 1 to 12, wherein the subject is human.
14. Use of a marker selected from the group consisting of a brain natriuretic peptide, a cardiac Troponin and sFlt-1 or ii) of a detection agent which specifically binds thereto, in a sample of a subject suffering from pneumonia for optimizing a risk assessment based on a clinical prediction rule for classifying subjects with pneumonia.
15. A device adapted for carrying out a method of any one of claims 1 to 13, comprising a) an analyzing unit comprising a detection agent (or detection agents) which specifically bind(s) to a marker selected from the group consisting of a brain natriuretic peptide, a cardiac troponin, and sFlt-1, said unit being adapted for determining the amount(s) of the at least one marker in a sample of a subject suffering from pneumonia; and
b) an evaluation unit for comparing the determined amount with reference amounts whereby the risk assessment based on a clinical prediction rule for classifying subjects with pneumonia is optimized, said unit comprising a database with a reference amount (reference amounts) and a computer- implemented algorithm for carrying out the comparison.
PCT/EP2013/064591 2012-07-10 2013-07-10 TnT, NTproBNP, sFlt-1 for CURB65 IN PNEUMONIA WO2014009418A1 (en)

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