The present invention is in the field of clinical diagnostics. Particularly the present invention relates to short-term outcome prognosis in patients suffering from heart failure by determination of the level of the marker peptide ADM.

Heart failure is a cardiac condition that occurs when a problem with the structure or function of the heart impairs its ability to supply sufficient blood flow to meet the body's needs. It can cause a large variety of symptoms, particularly shortness of breath and ankle swelling, but some patients can be completely symptom free. Heart failure is often undiagnosed due to a lack of a universally agreed definition and challenges in definitive diagnosis, particularly in early stage. With appropriate therapy, heart failure can be managed in the majority of patients, but it is a potentially life threatening condition, and progressive disease is associated with an annual mortality of 10%. It is the leading cause of hospitalization in people older than 65.

In this regard, Von Haehling et al. disclosed MR-pro-ADM and NT-proBNP as independent prognostic markers for congestive heart failure in terms of long-term prognosis ("Mid-regional pro-adrenomedullin as a novel and prognostic marker in chronic heart failure (CHF), European Heart Journal, Vo. 27, No. Suppl. 1, August 2006, page 16, XP002569337; also see World Congress of cardiology; Barcelona, Spain, on September 2, 2006, ISSN: 0195-668X).

However, the inventors surprisingly found that the determination of the level adrenomedullin (ADM) or its fragments thereof or its precursors or its fragments thereof can be reliably correlated with the short-term prognosis up to 90 days of an outcome for patients suffering from heart failure and/ or shortness of breath, and in addition can be reliably correlated with the stratification into risk groups of respective patients.

A subject of the present invention is the provision of a method for prognosis of an outcome after a time period of up to 90 days of a patient suffering from heart failure and/or shortness of breath, comprising the steps of:

1. a. providing a sample obtained from said patient,
2. b. determining the level of adrenomedullin (ADM) or fragments thereof or its precursor or fragments thereof in said sample, wherein the fragments are of at least six amino acids in length
3. c. correlating said level with said prognosis.

In another embodiment the present invention provides for a method for prognosis of an outcome after a time period of up to 90 days of a patient suffering from heart failure and/or shortness of breath, wherein the level of troponin is determined in addition to adrenomedullin (ADM) or fragments thereof or its precursor or fragments thereof as detailed above under steps a) to c).

In another embodiment of the invention said outcome regards survival and/or a functional outcome.

In another embodiment the present invention provides for a method for prognosis of an outcome after a time period of up to 90 days of a patient suffering from heart failure and/or shortness of breath according to the steps a) to c), wherein the outcome after 3 days, 5 days, 10 days, 14 days, 20 days, 3 weeks, 4 weeks, 30 days, preferably 30 days is predicted.

In another embodiment the present invention provides for a method for the stratification of a patient into risk groups, wherein said patient is suffering from heart failure and/or shortness of breath and said method comprises the steps a) to c) as detailed above.

In another embodiment the present invention provides for a method for prognosis of an outcome after a time period of up to 90 days of a patient suffering from heart failure and/or shortness of breath according to the steps a) to c), wherein adrenomedullin (ADM) or fragments thereof or its precursor or fragments thereof is MR-proADM.

In another embodiment of the invention said outcome regards survival.

In another embodiment of the invention said functional outcome is determined as ranking or the degree of severity of the outcome.

In another embodiment the present invention provides for a method for prognosis of an outcome after a time period of up to 90 days of a patient suffering from heart failure and/or shortness of breath according to the steps a) to c), wherein additionally at least one clinical parameter is determined selected from the group comprising: age, gender, systolic blood pressure, diastolic blood pressure, antihypertensive treatment, body mass index, heart rate, temperature, presence of diabetes mellitus, current smoking habits.

Also disclosed is a method for prognosis of an outcome after a time period of up to 90 days of a patient suffering from heart failure and/or shortness of breath according to the steps a) to c), wherein additionally at least one other laboratory parameter is determined selected from the group comprising troponin, myeloperoxidase, CRP, neopterin, GDF-15, ST2, cystatin-C, as well as the following peptides in form of their mature peptides, precursors, pro-hormones and associated prohormone fragments: atrial natriuretic peptide, endothelins, vasopressin.

In another embodiment the present invention provides for the use of the methods as detailed above for monitoring of the therapy in a patient suffering from heart failure and/or shortness of breath.

Heart failure herein preferably relates to congestive heart failure (CHF). The heart failure may preferably be an acute heart failure (AHF).

It is preferred in this particular embodiment that the short time outcome, i.e. the outcome within or after 45 days, 40 days, 35 days, 30 days, 25 days, 20 days, 15 days, 10 days or 5 days, preferably after 30 days is predicted. In another preferred embodiment of the invention the outcome up to 90 days is predicted by short-term prognosis pursuant to the invention. The invention also relates to the use of the described methods for short-term prognosis of an outcome up to 90 days of a patient suffering from heart failure and/or shortness of breath. Furthermore, the invention relates to the use of the methods for monitoring of the therapy in a patient suffering from heart failure and/or shortness of breath.

The levels of the markers as obtained by the methods or the use of the methods according to the present invention may be analyzed in a number of fashions well known to a person skilled in the art. For example, each assay result obtained may be compared to a "normal" value, or a value indicating a particular disease or outcome. A particular prognosis may depend upon the comparison of each assay result to such a value, which may be referred to as a prognostic "threshold". In certain embodiments, assays for one or more prognostic indicators are correlated to a condition or disease by merely the presence or absence of the indicator(s) in the assay. For example, an assay can be designed so that a positive signal only occurs above a particular threshold concentration of interest, and below which concentration the assay provides no signal above background.

The sensitivity and specificity of a prognostic test depends on more than just the analytical "quality" of the test, they also depend on the definition of what constitutes an abnormal result. In practice, Receiver Operating Characteristic curves (ROC curves), are typically calculated by plotting the value of a variable versus its relative frequency in "normal" (i.e. apparently healthy) and "disease" populations. For any particular marker, a distribution of marker levels for subjects with and without a disease will likely overlap. Under such conditions, a test does not absolutely distinguish normal from disease with 100% accuracy, and the area of overlap indicates where the test cannot distinguish normal from disease. A threshold is selected, above which (or below which, depending on how a marker changes with the disease) the test is considered to be abnormal and below which the test is considered to be normal. The area under the ROC curve is a measure of the probability that the perceived measurement will allow correct identification of a condition. ROC curves can be used even when test results don't necessarily give an accurate number. As long as one can rank results, one can create a ROC curve. For example, results of a test on "disease" samples obtained from patient might be ranked according to degree (e.g. 1=low, 2=normal, and 3=high). This ranking can be correlated to results in the "normal" population, and a ROC curve created. These methods are well known in the art. See, e.g., Hanley et al. 1982. Radiology 143: 29-36. Preferably, a threshold is selected to provide a ROC curve area of greater than about 0.5, more preferably greater than about 0.7, still more preferably greater than about 0.8, even more preferably greater than about 0.85, and most preferably greater than about 0.9. The term "about" in this context refers to +/- 5% of a given measurement.

The horizontal axis of the ROC curve represents (1-specificity), which increases with the rate of false positives. The vertical axis of the curve represents sensitivity, which increases with the rate of true positives. Thus, for a particular cut-off selected, the value of (1-specificity) may be determined, and a corresponding sensitivity may be obtained. The area under the ROC curve is a measure of the probability that the measured marker level will allow correct identification of a disease or condition. Thus, the area under the ROC curve can be used to determine the effectiveness of the test.

In certain embodiments, particular thresholds for one or more markers in a panel are not relied upon to determine if a profile of marker levels obtained from a subject are indicative of a particular prognosis. Rather, the present invention may utilize an evaluation of a marker panel "profile" as a unitary whole. A particular "fingerprint" pattern of changes in such a panel of markers may, in effect, act as a specific prognostic indicator. As discussed herein, that pattern of changes may be obtained from a single sample, or from temporal changes in one or more members of the panel (or a panel response value). A panel herein refers to a set of markers.

As described herein after, a panel response value is preferably determined by plotting ROC curves for the sensitivity (i.e. true positives) of a particular panel of markers versus 1-(specificity) (i.e. false positives) for the panel at various cut-offs. In these methods, a profile of marker measurements from a subject is considered together to provide a global probability (expressed either as a numeric score or as a percentage risk) of prognosis. In such embodiments, an increase in a certain subset of markers may be sufficient to indicate a particular prognosis in a sample obtained from one patient, while an increase in a different subset of markers may be sufficient to indicate the same or a different prognosis in a sample obtained from another patient. Weighting factors may also be applied to one or more markers in a panel, for example, when a marker is of particularly high utility in identifying a particular prognosis, it may be weighted so that at a given level it alone is sufficient to signal a positive result. Likewise, a weighting factor may provide that no given level of a particular marker is sufficient to signal a positive result, but only signals a result when another marker also contributes to the analysis.

In certain embodiments, markers and/or marker panels are selected to exhibit at least about 70% sensitivity, more preferably at least about 80% sensitivity, even more preferably at least about 85% sensitivity, still more preferably at least about 90% sensitivity, and most preferably at least about 95% sensitivity, combined with at least about 70% specificity, more preferably at least about 80% specificity, even more preferably at least about 85% specificity, still more preferably at least about 90% specificity, and most preferably at least about 95% specificity. In particularly preferred embodiments, both the sensitivity and specificity are at least about 75%, more preferably at least about 80%, even more preferably at least about 85%, still more preferably at least about 90%, and most preferably at least about 95%. The term "about" in this context refers to +/- 5% of a given measurement.

In other embodiments, a positive likelihood ratio, negative likelihood ratio, odds ratio, or hazard ratio is used as a measure of a test's ability to predict risk or diagnose a disease. In the case of a positive likelihood ratio, a value of 1 indicates that a positive result is equally likely among subjects in both the "diseased" and "control" groups; a value greater than 1 indicates that a positive result is more likely in the diseased group; and a value less than 1 indicates that a positive result is more likely in the control group. In the case of a negative likelihood ratio, a value of 1 indicates that a negative result is equally likely among subjects in both the "diseased" and "control" groups; a value greater than 1 indicates that a negative result is more likely in the test group; and a value less than 1 indicates that a negative result is more likely in the control group. In certain preferred embodiments, markers and/or marker panels are preferably selected to exhibit a positive or negative likelihood ratio of at least about 1.5 or more or about 0.67 or less, more preferably at least about 2 or more or about 0.5 or less, still more preferably at least about 5 or more or about 0.2 or less, even more preferably at least about 10 or more or about 0.1 or less, and most preferably at least about 20 or more or about 0.05 or less. The term "about" in this context refers to +/- 5% of a given measurement.

In the case of an odds ratio, a value of 1 indicates that a positive result is equally likely among subjects in both the "diseased" and "control" groups; a value greater than 1 indicates that a positive result is more likely in the diseased group; and a value less than 1 indicates that a positive result is more likely in the control group. In certain preferred embodiments, markers and/or marker panels are preferably selected to exhibit an odds ratio of at least about 2 or more or about 0.5 or less, more preferably at least about 3 or more or about 0.33 or less, still more preferably at least about 4 or more or about 0.25 or less, even more preferably at least about 5 or more or about 0.2 or less, and most preferably at least about 10 or more or about 0.1 or less. The term "about" in this context refers to +/- 5% of a given measurement.

In the case of a hazard ratio, a value of 1 indicates that the relative risk of an endpoint (e.g., death) is equal in both the "diseased" and "control" groups; a value greater than 1 indicates that the risk is greater in the diseased group; and a value less than 1 indicates that the risk is greater in the control group. In certain preferred embodiments, markers and/or marker panels are preferably selected to exhibit a hazard ratio of at least about 1.1 or more or about 0.91 or less, more preferably at least about 1.25 or more or about 0.8 or less, still more preferably at least about 1.5 or more or about 0.67 or less, even more preferably at least about 2 or more or about 0.5 or less, and most preferably at least about 2.5 or more or about 0.4 or less. The term "about" in this context refers to +/5% of a given measurement.

The skilled artisan will understand that associating a prognostic indicator, with a prognostic risk of a future clinical outcome is a statistical analysis. For example, a marker level of greater than X may signal that a patient is more likely to suffer from an adverse outcome than patients with a level less than or equal to X, as determined by a level of statistical significance. Additionally, a change in marker concentration from baseline levels may be reflective of patient prognosis, and the degree of change in marker level may be related to the severity of adverse events. Statistical significance is often determined by comparing two or more populations, and determining a confidence interval and/or a p value. See, e.g., Dowdy and Warden, Statistics for Research, John Wiley & Sons, New York, 1983. Preferred confidence intervals of the invention are 90%, 95%, 97.5%, 98%, 99%, 99.5%, 99.9% and 99.99%, while preferred p values are 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001, and 0.0001.

In yet other embodiments, multiple determinations of prognostic markers can be made, and a temporal change in the marker can be used to determine a prognosis. For example, a marker concentration in a sample obtained from subject may be determined at an initial time, and again at a second time from a second sample obtained from subject. In such embodiments, an increase in the marker from the initial time to the second time may be indicative of a particular prognosis. Likewise, a decrease in the marker from the initial time to the second time may be indicative of a particular prognosis.

The term "sample" as used herein refers to a sample of bodily fluid obtained from a subject or patient for the purpose of prognosis, or evaluation of a subject of interest, such as a patient. Preferred test samples obtained from subject/ patient include blood, serum, plasma, cerebrospinal fluid, urine, saliva, sputum, and pleural effusions. In addition, one of skill in the art would realize that some test samples obtained from subject/ patient would be more readily analyzed following a fractionation or purification procedure, for example, separation of whole blood into serum or plasma components.

Thus, in a preferred embodiment of the invention the sample obtained from subject/ patient is selected from the group comprising a blood sample, a serum sample, a plasma sample, a cerebrospinal fluid sample, a saliva sample and a urine sample or an extract of any of the aforementioned samples. Preferably, the sample obtained from subject/ patient is a blood sample, most preferably a serum sample or a plasma sample.

The term "patient" as used herein refers to a living human or non-human organism that is receiving medical care or that should receive medical care due to a disease. This includes persons with no defined illness who are being investigated for signs of pathology. Thus, the methods and assays described herein are applicable in vitro to both human and veterinary disease.

The term "correlating," as used herein in reference to the use of prognostic markers, refers to comparing the presence or amount of the marker(s) in samples obtained from a patient to its presence or amount in persons known to suffer from, or known to be at risk of, a given condition; or in persons known to be free of a given condition. As discussed above, a marker level in a sample obtained from patient can be compared to a level known to be associated with a specific diagnosis. In preferred embodiments, a panel of marker levels is correlated to a global probability or a particular outcome.

The abbreviation ADM in the context of the present invention relates to adrenomedullin or fragments thereof or precursors or fragments thereof. A preferred fragment of a precursor of ADM is mid-regional proADM (MR-proADM). MR-proADM_24-71 (or MR-preproADM_45-92) is a particularly preferred marker peptide in the context of the present invention.

"Fragments" of the marker peptides relate to fragments of at least 12 amino acids in length, preferably at least six amino acid residues in length.

The term "level" in the context of the present invention relates to the concentration (preferably expressed as weight/volume; w/v) of marker peptides in a sample taken from a patient.

The term "outcome" herein relates for instance to the survival of the patient after a defined time, e.g. after 3 days, 5 days, 10 days, 14 days, 20 days, 3 weeks, 4 weeks, 30 days, 45 days, 60 days, 90 days, , preferably 30 days.

The term "functional outcome" in the context of the present invention relates to the degree of severity of the disease, i.e. the state of health the patient after a defined time, e.g. 3 days, 5 days, 10 days, 14 days, 20 days, 3 weeks, 4 weeks, 30 days, 45 days, 60 days, 90 days, preferably 30 days.

Determining (or measuring or detecting) the level of a marker peptide herein is performed using a detection method and/or a diagnostic assay as explained below.

As mentioned herein, an "assay" or "diagnostic assay" can be of any type applied in the field of diagnostics. Such an assay may be based on the binding of an analyte to be detected to one or more capture probes with a certain affinity. Concerning the interaction between capture molecules and target molecules or molecules of interest, the affinity constant is preferably greater than 10⁸ M^-1.

In the context of the present invention, "capture molecules" are molecules which may be used to bind target molecules or molecules of interest, i.e. analytes (i.e. in the context of the present invention the cardiovascular peptide(s)), from a sample. Capture molecules must thus be shaped adequately, both spatially and in terms of surface features, such as surface charge, hydrophobicity, hydrophilicity, presence or absence of lewis donors and/or acceptors, to specifically bind the target molecules or molecules of interest. Hereby, the binding may for instance be mediated by ionic, van-der-Waals, pi-pi, sigma-pi, hydrophobic or hydrogen bond interactions or a combination of two or more of the aforementioned interactions between the capture molecules and the target molecules or molecules of interest. In the context of the present invention, capture molecules may for instance be selected from the group comprising a nucleic acid molecule, a carbohydrate molecule, a RNA molecule, a protein, an antibody, a peptide or a glycoprotein. Preferably, the capture molecules are antibodies, including fragments thereof with sufficient affinity to a target or molecule of interest, and including recombinant antibodies or recombinant antibody fragments, as well as chemically and/or biochemically modified derivatives of said antibodies or fragments derived from the variant chain with a length of at least 12 amino acids thereof, preferably at least six amino acids thereof.

The preferred detection methods comprise immunoassays in various formats such as for instance radioimmunoassay (RIA), chemiluminescence- and fluorescence- immunoassays, Enzyme-linked immunoassays (ELISA), Luminex-based bead arrays, protein microarray assays, and rapid test formats such as for instance immunochromatographic strip tests.

The assays can be homogenous or heterogeneous assays, competitive and non-competitive sandwich assays. In a particularly preferred embodiment, the assay is in the form of a sandwich assay, which is a non-competitive immunoassay, wherein the molecule to be detected and/or quantified is bound to a first antibody and to a second antibody. The first antibody may be bound to a solid phase, e.g. a bead, a surface of a well or other container, a chip or a strip, and the second antibody is an antibody which is labeled, e.g. with a dye, with a radioisotope, or a reactive or catalytically active moiety. The amount of labeled antibody bound to the analyte is then measured by an appropriate method. The general composition and procedures involved with "sandwich assays" are well-established and known to the skilled person. (The Immunoassay Handbook, Ed. David Wild, Elsevier LTD, Oxford; 3rd ed. (May 2005), ISBN-13: 978-0080445267; Hultschig C et al., Curr Opin Chem Biol. 2006 Feb;10(1):4-10. PMID: 16376134).

In a particularly preferred embodiment the assay comprises two capture molecules, preferably antibodies which are both present as dispersions in a liquid reaction mixture, wherein a first labeling component is attached to the first capture molecule, wherein said first labeling component is part of a labeling system based on fluorescence- or chemiluminescence-quenching or amplification, and a second labeling component of said marking system is attached to the second capture molecule, so that upon binding of both capture molecules to the analyte a measurable signal is generated that allows for the detection of the formed sandwich complexes in the solution comprising the sample.

Even more preferred, said labeling system comprises rare earth cryptates or rare earth chelates in combination with a fluorescence dye or chemiluminescence dye, in particular a dye of the cyanine type.

In the context of the present invention, fluorescence based assays comprise the use of dyes, which may for instance be selected from the group comprising FAM (5-or 6-carboxyfluorescein), VIC, NED, Fluorescein, Fluoresceinisothiocyanate (FITC), IRD-700/800, Cyanine dyes, auch as CY3, CY5, CY3.5, CY5.5, Cy7, Xanthen, 6-Carboxy-2',4',7',4,7-hexachlorofluorescein (HEX), TET, 6-Carboxy-4',5'-dichloro-2',7'-dimethodyfluorescein (JOE), N,N,N',N'-Tetramethyl-6-carboxyrhodamine (TAMRA), 6-Carboxy-X-rhodamine (ROX), 5-Carboxyrhodamine-6G (R6G5), 6-carboxyrhodamine-6G (RG6), Rhodamine, Rhodamine Green, Rhodamine Red, Rhodamine 110, BODIPY dyes, such as BODIPY TMR, Oregon Green, Coumarines such as Umbelliferone, Benzimides, such as Hoechst 33258; Phenanthridines, such as Texas Red, Yakima Yellow, Alexa Fluor, PET, Ethidiumbromide, Acridinium dyes, Carbazol dyes, Phenoxazine dyes, Porphyrine dyes, Polymethin dyes, and the like.

In the context of the present invention, chemiluminescence based assays comprise the use of dyes, based on the physical principles described for chemiluminescent materials in Kirk-Othmer, Encyclopedia of chemical technology, 4th ed., executive editor, J. I. Kroschwitz; editor, M. Howe-Grant, John Wiley & Sons, 1993, vol.15, p. 518-562, including citations on pages 551-562. Preferred chemiluminescent dyes are acridiniumesters.

The levels, i.e. the concentrations, of the one or more marker peptides (or fragments thereof or precursors or fragments thereof) in the sample obtained from the patient are attributed to the short-term prognosis of an outcome for the patient. For instance, concentrations of the marker peptide above a certain threshold value are indicative for an adverse outcome or an elevated risk for the patient. Such threshold values are preferably in the range of from about 0.5 to 5.0 pmol/l, more preferably 1.0 to 2.5 pmol/l, most preferably 1.985 nmol/l for MR-proADM.

In another embodiment of the invention, the risk and/or outcome for a patient is determined by relating the patient's individual level of marker peptide to certain percentiles (e.g. 97.5^th percentile) of a healthy population.

Kaplan-Meier estimators may be used for the assessment or prediction of the outcome or risk (e.g. morbidity) of a patient.

The teaching of the present invention is derived from a comparative study among adrenomedullin (ADM) or fragments thereof or its precursor or fragments thereof, and troponin, and the brain natriuretic peptide (BNP) or fragments thereof or its precursor or fragments thereof regarding its prognostic values in shortness of breath (SoB) and acute heart failure (AHF) patients.

The amino acid sequence of the precursor peptide of Adrenomedulin (pre-pro-Adrenomedullin) is given in SEQ ID NO:1. Pro-Adrenomedullin relates to amino acid residues 22 to 185 of the sequence of pre-pro-Adrenomedullin. The amino acid sequence of pro-Adrenomedullin (pro-ADM) is given in SEQ ID NO:2. The pro-ADM N-terminal 20 peptide (PAMP) relates to amino acid residues 22-41 of pre-proADM. The amino acid sequence of PAMP is given in SEQ ID NO:3. MR-pro-Adrenomedullin (MR-pro-ADM) relates to amino acid residues 45-92 of pre-pro-ADM. The amino acid sequence of MR-pro-ADM is provided in SEQ ID NO:4. The amino acid sequence of mature Adrenomedullin (ADM) is given in SEQ ID NO:5.

The sequence of the 134 amino acid precursor peptide of brain natriuretic peptide (pre-pro-BNP) is given in SEQ ID NO:6 . Pro-BNP relates to amino acid residues 27 to 134 of pro-pro-BNP. The sequence of pro-BNP is shown in SEQ ID NO:7. Pro-BNP is cleaved into N-terminal pro-BNP (NT-pro-BNP) and mature BNP. NT-pro-BNP comprises the amino acid residues 27 to 102 and its sequence is shown in SEQ ID NO:8. The SEQ ID NO:9 shows the sequence of BNP comprising the amino acid residues 103 to 134 of the pre-pro-BNP peptide.

• SEQ ID NO:1 (amino acid sequence of pre-pro-ADM):
• SEQ ID NO:2 (amino acid sequence of pro-ADM):
• SEQ ID NO:3 (amino acid sequence of pro-ADM N20):
  1 ARLDVASEFR KKWNKWALSR
• SEQ ID NO:4 (amino acid sequence of MR-pro-ADM):
  1 ELRMSSSYPT GLADVKAGPA QTLIRPQDMK GASRSPEDSS PDAARIRV
• SEQ ID NO:5 (amino acid sequence of ADM):
• SEQ ID NO:6 (amino acid sequence of pre-pro-BNP) :
• SEQ ID NO:7 (amino acid sequence of pro-BNP) :
• SEQ ID NO:8 (amino acid sequence of NT-pro-BNP):
• SEQ ID NO:9 (amino acid sequence of BNP) :
  1 SPKMVQGSGC FGRKMDRISS SSGLGCKVLR RH

• Fig. 1: Survival rates plotted for the four quartiles of MR-proADM levels in AHF patients.
• Fig. 2: Survival rates plotted for the four quartiles of MR-proADM levels in AHF patients, quartiles 1 to 3 have been combined.
• Fig. 3: Survival rates plotted for the four quartiles ofBNP levels in AHF patients.
• Fig. 4: Survival rates plotted for the four quartiles of BNP levels in AHF patients, quartiles 1 to 3 have been combined.
• Fig. 5: Survival rates plotted for the four quartiles of NT-proBNP levels in AHF patients.
• Fig. 6: Survival rates plotted for the four quartiles of NT-proBNP levels in AHF patients, quartiles 1 to 3 have been combined.
• Fig. 7: Area under the curve (AUC) from ROC plots for the markers BNP, NT-proBNP and MR-proADM on different days.
• Fig. 8: ROC plot for the markers BNP, NT-proBNP and MR-proADM.
• Fig. 9: Survival (cumulative survival depending on the day) in patients with and without AHF plotted for MR-proADM above and below the threshold of 1.985 pmol/L.
• Fig. 10: Summary of patients.
• Fig. 11: SEQ ID NO:1 (amino acid sequence of pre-pro-ADM)
• Fig. 12: SEQ ID NO:2 (amino acid sequence of pro-ADM)
• Fig. 13: SEQ ID NO:3 (amino acid sequence of pro-ADM N20)
• Fig. 14: SEQ ID NO:4 (amino acid sequence of MR-proADM)
• Fig. 15: SEQ ID NO:5 (amino acid sequence of ADM)
• Fig. 16: SEQ ID NO:6 (amino acid sequence of pre-pro-BNP)
• Fig. 17: SEQ ID NO:7 (amino acid sequence of pro-BNP)
• Fig. 18: SEQ ID NO:8 (amino acid sequence of NT-pro-BNP)
• Fig. 19: SEQ ID NO:9 (amino acid sequence of BNP)

Characteristics Breathing Not Properly BACH TOTAL ENROLLMENT 1,586 1,641 Age 64 +/-17 64 +/- 17 Sex Male (%) 56 52 Sex Female (%) 44 48 History (%) CHF 33 36 AMI 27 19 COPD 41 30 Diabetes 25 29 Variable Non-AHF AHF p Mean SD Mean SD Heart Rate (bpm) 93 22 89 25 0.005 Temperature (C) 36.8 0.7 36.7 0.7 0.039 Systolic BP (mmHg) 140 27 143 32 0.027 Diastolic BP (mmHg) 80 16 83 19 <0.001 BMI (kg/m2) 30 9 29 8 0.035

Also see Fig. 10 for summary of patients.

• Patients included who presented to emergency department (ED) with SoB not from trauma, or obvious myocardial infarction (MI), and not on dialysis.
• After consenting, MD assessment of probability of heart failure and/or pneumonia.
• Two independent cardiologists agreed on final diagnosis following discharge.
• Follow-up for up to 90 days for survival; Outcome "All cause mortality within 90 days".

Diagnostic Accuracy: MR-proADM 73.5% vs BNP 60.8% (p<0.001) vs NT-proBNP 63.6% (p<0.001) Predictor (univariate) Chi² Statistic p c index log MR-proADM 31.0 <0.001 0.669 log BNP 7.1 0.008 0.596 log NT-proBNP 17.1 <0.001 0.654 Chi² Statistic p adding MR-proADM to BNP 23.9 <0.0001 adding MR-proADM to NT-proBNP 15.3 <0.0001 adding BNP to MR-proADM 0.0 0.906 adding NT-proBNP to MR-proADM 1.1 0.291

Predictor (multivariable) HR 95% CI p log MR-proADM 14.0 5.0-39.4 <0.001 log BNP 1.0 0.5-2.0 0.906 Predictor (multivariable) HR 95% CI p log MR-proADM 10.4 3.3-32.7 <0.001 log NT-proBNP 1.4 0.7-2.6 0.295

Troponin values were available in 511 of 568 HF patients in 107 (20.9%) patients they were elevated. Predictor (multivariable) HR 95% CI p log MR-proADM 8.5 2.7-26.5 <0.001 log BNP 0.9 0.5-1.9 0.812 Elevated Tn 2.6 1.5-4.5 <0.001 Predictor (multivariable) HR 95% CI p log MR-proADM 7.5 2.1-26.4 <0.001 log NT-proBNP 1.1 0.6-2.2 0.295 Elevated Tn 2.6 1.5-4.4 <0.001

Clinical lab Troponin values (TnI or TnT) were judged as elevated if above the local normal range.

Risk is great in the highest quartile of MR-proADM, see Fig. 1 and 2 and tables 9 and 10. Quartile HR 95% CI p 1st 1 reference 2nd 0.8 0.3-2.0 0.640 3rd 1.1 0.5-2.5 0.822 4th 3.2 1.6-6.4 0.001 Quartile HR 95% CI p 1 st-3rd 1 reference 4th 3.3 2.0-5.4 <0.001

Risk is great in the highest quartile of BNP, see Fig. 3 and 4 and tables 11 and 12. Quartile HR 95% CI p 1st 1 reference 2nd 1.9 0.9-4.3 0.116 3rd 1.2 0.5-2.9 0.668 4th 3.2 1.5-6.7 0.003 Quartile HR 95% CI p 1 st-3rd 1 reference 4th 2.3 1.4-3.8 <0.001

Risk is great in the highest quartile of NT-proBNP, see Fig. 5 and 6 and tables 13 and 14. Quartile HR 95% CI p 1 st 1 reference 2nd 1.7 0.7-4.4 0.247 3rd 2.5 1.0-6.0 0.043 4th 4.3 1.9-9.9 <0.001 Quartile HR 95% CI p 1 st-3rd 1 reference 4th 2.5 1.5-4.1 <0.001

MR-proADM predicts short term (30 day) survival exceptionally well, see Fig. 7 and table 15. AUC 30 days 90 days MR-proADM 0.739 0.674 NT-proBNP 0.641 0.664 BNP 0.555 0.606

Predictor (univariate) Chi² Statistic p c index log MR-proADM 129.5 <0.0001 0.755 log BNP 60.1 <0.0001 0.691 log NT-proBNP 83.7 <0.0001 0.721 Chi² Statistic p adding MR-proADM to BNP 69.4 <0.0001 adding MR-proADM to NT-proBNP 46.6 <0.0001 adding BNP to MR-proADM 0.1 0.731 adding NT-proBNP to MR-proADM 1.5 0.229

A corresponding ROC plot is shown in Fig. 8.

Elevated MR-proADM is strongly prognostic in patients with and without AHF - even more so in non-AHF than in AHF (interaction p=0.005). See appended Fig. 9 and tables 18 and 19. AHF patients AUC (90 days) optimal cut point from ROC MR-proADM 0.674 1.985 pmol/l Diagnosis MR-proADM HR 95% CI p Non-AHF low < 1.985 1 reference high ≥ 1.985 8.6 5.1-14.4 <0.001 AHF low < 1.985 1.7 1.1-2.7 0.027 high ≥ 1.985 5.7 3.6-8.9 <0.001

• MR-proADM is a strong prognosticator in patients with AHF and in patients presenting with SoB.
• MR-proADM is superior to BNP or NT-proBNP for predicting 90-day mortality, both in AHF as well as in all ED pts with SoB.
• MR-proADM is particularly strong in predicting short-term prognosis within 4 weeks after assessment.
• All these results are unaffected by adjustment for Troponin.
• MR-proADM can significantly improve risk stratification over BNP or NT-proBNP.
• Assessment of MR-proADM can help to identify patients who should "move to the front of the line" of medical care.

• <110> B.R.A.H.M.S AG
• <120> Prognosis and risk assessment in patients suffering from heart failure by determining the level of ADM and BNP
• <130> B60408PCT
• <150> 08168816.0
  <151> 2008-11-11
• <160> 9
• <170> PatentIn version 3.3
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