CIRCULATING TFPI-2 (TISSUE FACTOR PATHWAY INHIBITOR 2) IN THE ASSESSMENT OF ATRIAL FIBRILLATION AND ANTICOAGULATION THERAPY
20210181211 · 2021-06-17
Inventors
- Peter Kastner (Penzberg, DE)
- Andre Ziegler (Rotkreuz, CH)
- Ursula-Henrike Wienhues-Thelen (Penzberg, DE)
- Vinzent Rolny (Penzberg, DE)
- Manuel Dietrich (Mannheim, DE)
- Ulrich Schotten (GT Maastricht, DE)
Cpc classification
G01N2800/2871
PHYSICS
G01N2800/52
PHYSICS
International classification
Abstract
The present invention relates to a method for assessing atrial fibrillation in a subject, said method comprising the steps of determining the amount of TFPI-2 in a sample from the subject, and comparing the amount of TFPI-2 to a reference amount, whereby atrial fibrillation is to be assessed. Moreover, the present invention relates to methods for assessing anticoagulation therapy and to methods for predicting the risk of stroke of a subject. Said methods are based on the determination of the amount of TFPI-2 in a sample from the subject.
Claims
1. A method for assessing atrial fibrillation in a subject, comprising the steps of a) determining, in at least one sample from the subject, the amount of the biomarker TFPI-2 (Tissue Factor Pathway Inhibitor 2) and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 (Angiopoietin 2) and IGFBP7 (Insulin-like growth factor-binding protein 7), and b) comparing the amount of the biomarker TFPI-2 to a reference amount for TFPI-2 and, optionally, comparing the amount of the at least one further biomarker to a reference amount for said at least one further biomarker, whereby atrial fibrillation is to be assessed.
2. The method of claim 1, wherein the sample is a blood, serum or plasma sample.
3. The method according to claim 1, wherein an amount of TFPI-2 and, optionally, an amount of the at least one further biomarker above the reference amount is indicative for a subject suffering from atrial fibrillation and/or wherein an amount of TFPI-2 and, optionally, an amount of the at least one further biomarker below the reference amount is indicative for a subject not suffering from atrial fibrillation, or wherein the subject is suffering from atrial fibrillation, and wherein an amount of TFPI-2 and, optionally, an amount of the at least one further biomarker above the reference amount is indicative for a subject suffering from persistent atrial fibrillation and/or wherein an amount of TFPI-2 and, optionally, an amount of the at least one further biomarker below the reference amount is indicative for a subject suffering from paroxysmal atrial fibrillation.
4. The method of claim 1, wherein the assessment of atrial fibrillation is the prediction of the risk of stroke associated with atrial fibrillation, and wherein an amount of TFPI-2 and, optionally, an amount of the at least one further biomarker above the reference amount is indicative for a subject who is at risk of suffering from stroke associated with atrial fibrillation and/or wherein an amount of TFPI-2 and, optionally, an amount of the at least one further biomarker below the reference amount is indicative for a subject who is not at risk of suffering from stroke associated with atrial fibrillation.
5. A method for predicting the risk of stroke in a subject, comprising the steps of (a) determining, in at least one sample from the subject, the amount of the biomarker TFPI-2 (Tissue Factor Pathway Inhibitor 2) and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 (Angiopoietin 2) and IGFBP7 (Insulin-like growth factor-binding protein 7), and (b) assessing the clinical stroke risk score for said subject, and (c) predicting the risk of stroke based on the results of steps a) and b).
6. A method for assessing the efficacy of an anticoagulation therapy of a subject, comprising the steps of a) determining, in at least one sample from the subject, the amount of the biomarker TFPI-2 (Tissue Factor Pathway Inhibitor 2) and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 (Angiopoietin 2) and IGFBP7 (Insulin-like growth factor-binding protein 7), and a) comparing the amount of the biomarker TFPI-2 to a reference amount for TFPI-2 and, optionally, comparing the amount of the at least one further biomarker to a reference amount for said at least one further biomarker, whereby the efficacy of the anticoagulation therapy is to be assessed.
7. A method for identifying a subject being eligible to the administration of at least one anticoagulation medicament or being eligible to an intensified anticoagulation therapy, comprising a) determining, in at least one sample from the subject, the amount of the biomarker TFPI-2 (Tissue Factor Pathway Inhibitor 2) and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 (Angiopoietin 2) and IGFBP7 (Insulin-like growth factor-binding protein 7), and b) comparing the amount of the biomarker TFPI-2 to a reference amount for TFPI-2 and, optionally, comparing the amount of the at least one further biomarker to a reference amount for said at least one further biomarker, whereby a subject being eligible to the administration of said at least one medicament or to an intensified anticoagulation therapy is identified.
8. The method of claim 7, wherein a subject who is eligible to an intensified anticoagulation therapy is eligible to an increase of the dosage of the currently administered anticoagulant, or to the replacement of a currently administered anticoagulant with a more effective anticoagulant.
9. A method for monitoring anticoagulation therapy, comprising the steps of (a) determining, in at first sample from the subject, the amount of the biomarker TFPI-2 (Tissue Factor Pathway Inhibitor 2) and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 (Angiopoietin 2) and IGFBP7 (Insulin-like growth factor-binding protein 7), (b) determining, in a second sample from the subject, the amount of the biomarker TFPI-2 (Tissue Factor Pathway Inhibitor 2) and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 (Angiopoietin 2) and IGFBP7 (Insulin-like growth factor-binding protein 7), wherein said second sample has been obtained after said first sample, (c) comparing the amount of TFPI-2 in the first sample to the amount of TFPI-2 in said second sample, and optionally comparing the amount of said at least one further biomarker in the first sample to the amount of said at least one further biomarker in said second sample, thereby monitoring anticoagulation therapy.
10. The method according to claim 5, wherein the subject suffers from atrial fibrillation.
11. A method of aiding in the assessment of atrial fibrillation, said method comprising the steps of: a) providing at least one sample from a subject, b) determining, in the at least one sample provided in step a), the amount of the biomarker TFPI-2 (Tissue Factor Pathway Inhibitor 2) and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 and IGFBP7 (Insulin-like growth factor-binding protein 7), and c) providing information on the determined amount of the biomarker TFPI-2 and optionally on the determined amount of the at least one further biomarker to a physician, thereby aiding in the assessment of atrial fibrillation.
12. A method for aiding in the assessment of atrial fibrillation, comprising: a) providing an assay for the biomarker TFPI-2 and, optionally, at least one further assay for a further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 and IGFBP7 (Insulin-like growth factor-binding protein 7), and b) providing instructions for using of assay results obtained or obtainable by said assay(s) in the assessment of atrial fibrillation.
13. A computer-implemented method for assessing atrial fibrillation, comprising a) receiving, at a processing unit, a value for the amount of TFPI-2, and, optionally at least one further value for the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 and IGFBP7 (Insulin-like growth factor-binding protein 7), wherein said amount of TFPI-2 and, optionally, the amount of the at least one further biomarker have been determined in a sample from a subject, b) comparing, by said processing unit, the value or values received in step (a) to a reference or to references, and c) assessing atrial fibrillation based in the comparison step b).
14. A kit comprising an agent which specifically binds to TFPI-2 and at least one further agent selected from the group consisting an agent which specifically binds to a natriuretic peptide, an agent which specifically binds to ESM-1, an agent which specifically binds Ang2 and an agent which specifically binds to IGFBP7.
15. In vitro use of i) the biomarker TFPI-2 and optionally of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 and IGFBP7 (Insulin-like growth factor-binding protein 7), and/or ii) at least one agent that specifically binds to TFPI-2, and, optionally, at least one further agent selected from the group consisting an agent which specifically binds to a natriuretic peptide, an agent which specifically binds to ESM-1, an agent which specifically binds to Ang2 and an agent which specifically binds to IGFBP7, for a) assessing atrial fibrillation, b) predicting the risk of stroke in a subject, c) improving the prediction accuracy of a clinical stroke risk score, for assessing the efficacy of an anticoagulation therapy of a subject, d) for identifying a subject being eligible to the administration of at least one anticoagulation medicament or being eligible to an intensified anticoagulation therapy, and/or e) monitoring anticoagulation therapy.
16. The method of claim 7, wherein the replacement of the currently administered anticoagulant with a more effective anticoagulant comprises the replacement of a currently administered vitamin K antagonist with an oral anticoagulant
17. The method of claim 16, wherein the vitamin K antagonist is selected from the group consisting of warfarin and dicumarol.
18. The method of claim 16, wherein the more effective anticoagulant is selected from the group consisting of dabigatran, rivaroxaban and apixaban.
Description
[0383] The figures show:
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EXAMPLES
[0390] The invention will be merely illustrated by the following Examples. The said Examples shall, whatsoever, not be construed in a manner limiting the scope of the invention.
Example 1: Differential Expression of TFPI-2 in Cardiac Tissue of AF Patients
[0391] Differential TFPI-2 expression levels have been determined in myocardial tissue samples from the right atrial appendage of n=38 patients.
[0392] RNAseq Analyses
[0393] Atrial tissue was sampled during open chest surgery because of CABG or valve surgery. Evidence of AF or SR (controls) was generated during surgery with simultaneous EndoEpicardial High Density Activation Mapping. Patients with AF and controls were matched with regard to gender, age and comorbidities.
[0394] Atrial tissue samples were prepared for [0395] AF patients; n=9 patients [0396] control patients in SR; n=29 patients.
[0397] Differential expression of TFPI-2 was determined in RNAseq analyses applying the algorithms RSEM and DESEQ2.
[0398] As shown in
[0399] The fold change in expression (FC) was 1.221.
[0400] The altered expression of TFPI-2 was determined in the damaged end organ, the atrial tissue. TFPI-2 mRNA levels were compared to results of high density mapping of the atrial tissue. Elevated TFPI-2 mRNA levels were detected in atrial tissue samples with conduction disturbances as characterized by electrical mapping. Conductance disturbances may be caused by fat infiltration or by interstitial fibrosis. The observed differential expression of TFPI-2 in atrial tissue of patients suffering from atrial fibrillation supports, that TFPI-2 is released in the circulation from the myocardium, in particular from the right atrial appendage and elevated serum/plasma titers assist the detection of episodes of AF.
[0401] It is concluded, that TFPI-2 is released from the heart into the blood and may aid the detection of AF episodes and predict the risk of developing AF related stroke.
Example 2: Assessment of AF with Circulating TFPI-2
[0402] The MAPPING study related to patients undergoing open chest surgery. Samples were obtained before anesthesia and surgery. Patients were electrophysiologically characterized using high-density epicardial mapping with multi-electrode arrays (high density mapping). Circulating TFPI-2 levels have been determined in 12 patients with paroxysmal atrial fibrillation, 16 patients with persistent atrial fibrillation and 30 controls, matched to best possible (on age, gender, comorbidities). TFPI-2 was determined in samples of the MAPPING study.
[0403] Measurements were performed in 30 patients with sinus rhythm (SR), in 12 patients with paroxysmal arterial fibrillation (parAF) and in 16 persistent arterial fibrillation (persAF).
[0404]
[0405] The Beat AF study related to baseline samples of AF patients followed for stroke outcome for 6 years.
[0406]
Example 3: Prediction of Stroke
[0407] Analysis Approach
[0408] The ability of circulating TFPI-2 to predict the risk for the occurrence of stroke was assessed in a prospective, multicentric registry of patients with documented atrial fibrillation (Conen D., Forum Med Suisse 2012; 12:860-862). TFPI-2 was measured using a stratified case cohost design as described in Borgan (2000).
[0409] For each of the 70 patients which experienced a stroke during follow up (“events”), 1 matched control was selected. Controls were matched based on the demographic and clinical information of age, sex, history of hypertension, atrial fibrillation type and history of heart failure (CHF history).
[0410] TFPI-2, NTproBNP, ESM-1, Ang-2, IGFBP-7 results were available for 67 patients with an event and 66 patients without an event.
[0411] TFPI-2 was measured using the Olink platform therefor no absolute concentration values are available and can be reported. Results will be reported on an arbitrary signal scale (NPX). NTproBNP, Ang-2 and IGFBP-7 were measured using the Elecsys platform and ESM-1 was measured using an Elisa microtiter plate.
[0412] In order to quantify the univariate prognostic value of TFPI-2 proportional hazard models were used with the outcome stroke.
[0413] The univariate prognostic performance of TFPI-2 was assessed by two different incorporations of the prognostic information given by TFPI-2.
[0414] The first proportional hazard model included TFPI-2 binarized at the median (221 NPX) and therefore comparing the risk of patients with TFPI-2 below or equal to the median versus patient with TFPI-2 above the median.
[0415] The second proportional hazard model included the original TFPI-2 levels but transformed to a log 2 scale. The log 2 transformation was performed in order to enable a better model calibration.
[0416] Because the estimates from a naïve proportional hazard model on the case control cohort would be biased (due to the altered proportion of cases to controls) a weighted proportional hazard model was used. Weights are based on the inverse probability for each patient to be selected for the case control cohort as described in Mark (2006). In order to get estimates for the absolute survival rates in the two groups based on the dichotomized baseline TFPI-2 measurement (<=221 NPX vs >221 NPX) a weighted version of the Kaplan-Meier plot was created as described in Mark (2006).
[0417] In order to assess if the prognostic value of TFPI-2 is independent from known clinical and demographic risk factors a weighted proportional cox model including in addition the variables age, sex, CHF history, history of hypertension, Stroke/TIA/Thromboembolism history, vascular disease history and diabetes history was calculated.
[0418] In order to assess the ability of TFPI-2 to improve existing risk scores for the prognosis of stroke the CHADS.sub.2 the CHA.sub.2DS.sub.2-VASc and the ABC score were extended by TFPI-2 (log 2 transformed). Extension was done by creating a portioned hazard model including TFPI-2 and the respective risk score as independent variables. NTproBNP, ESM-1, Ang-2 and IGFBP-7 were assessed for the ability to improve the CHA.sub.2DS.sub.2-VASc score.
[0419] The c-indices of the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc and ABC score were compared to the c-indices of these extended models. For the calculation of the c-index in the case-cohort setting a weighted version of the c-index was used as proposed in Ganna (2011).
[0420] Results
[0421] Table 1 shows the results of the two univariate weighted proportional hazard models including the binarized or the log 2 transformed TFPI-2. The association between the risk for experiencing a stroke with the baseline value of TFPI-2 is highly significant in both models. The hazard ration for the binarized TFPI-2 implies a 2.36-fold higher risk for a stroke in the patient group with baseline TFPI-2>=221 NPX versus the patient group with baseline TFPI2<221 NPX. The results of the proportional hazard model including TFPI-2 as log 2 transformed linear risk predictor suggest the log 2 transformed values TFPI-2 are proportional to the risk for experiencing a stroke. The hazard ratio of 2.52 can be interpreted in a way that a 2-fold increase of TFPI-2 is associated with 2.52 increase of risk for a stroke.
[0422] In this context it is interesting to note that TFPI-2 level correlate with the intake of certain oral anticoagulants (OAKs).
TABLE-US-00001 TABLE 1 Results result of the univariate weighted proportional hazard model including the binarized and log2 transformed TFPI-2. Hazard Ratio (HR) 95%-CI HR P-Value TFPI-2 log2 2.5153 1.2558-5.0380 0.0093 Baseline TFPI-2 >= 221 2.3612 1.2007-4.6433 0.0128 NPX vs TFPI-2 < 221 NPX
[0423] Table 2 shows the results of a proportional hazard model including TFPI-2 (log 2 transformed) in the combination with clinical and demographic variables. It clearly shows that the prognostic effect of TFPI-2 stays stable if adjusting for the prognostic effect of relevant clinical and demographic variables.
TABLE-US-00002 TABLE 2 Multivariate proportional hazard model including TFPI-2 and relevant clinical and demographic variables. Hazard Ratio (HR) 95%-CI HR P-Value History hypertension 1.3471 0.5923-3.0639 0.4773 Age 1.0272 0.9814-1.075 0.2488 History 1.9457 0.7698-4.9179 0.1594 Stroke/TIA/embolism Sex = male 1.2565 0.4547-3.4722 0.6598 History CHF 0.6667 0.2718-1.6355 0.3759 History vascular 1.4862 0.5658-3.9041 0.4214 disease TFPI-2 (log2 2.7248 1.0987-6.7577 0.0305 transformed)
[0424] Table 3 shows the results of the weighted proportional hazard model combining the CHADS.sub.2 score with TFPI-2 (log 2 transformed). Also in this model TFPI-2 can add prognostic information to the CHADS.sub.2 score.
TABLE-US-00003 TABLE 3 Weighted proportional hazard model combining the CHADS.sub.2 score with TFPI-2 (log2 transformed) Hazard Ratio (HR) 95%-CI HR P-Value CHADS.sub.2 score 1.4450 1.1286-1.8502 0.0035 TFPI-2 (log2 2.5818 1.3275-5.0212 0.0052 transformed)
[0425] Table 4 shows the results of the weighted proportional hazard model combining the CHA.sub.2DS.sub.2-VASc score with TFPI-2 (log 2 transformed). Also in this model TFPI-2 can add prognostic information to the CHA.sub.2DS.sub.2-VASc score.
TABLE-US-00004 TABLE 4 Weighted proportional hazard model combining the CHA.sub.2DS.sub.2-VASc score with TFPI-2 (log2 transformed) Hazard Ratio (HR) 95%-CI HR P-Value CHA.sub.2DS.sub.2-VASc 1.3950 1.0784-1.8046 0.0112 score TFPI-2 (log2 2.2217 1.1047-4.4683 0.0251 transformed)
[0426] Table 5 shows the results of the weighted proportional hazard model combining the ABC score with TFPI-2 (log 2 transformed). Also in this model TFPI-2 can add prognostic information to the risk score.
TABLE-US-00005 TABLE 5 Weighted proportional hazard model combining the ABC score with TFPI-2 (log2 transformed) Hazard Ratio (HR) 95%-CI HR P-Value ABC score 1.1209 1.0004-1.256 0.0493 TFPI-2 (log2 2.1272 0.7548-2.1272 0.0413 transformed)
[0427] Table 6 shows the estimated c-indexes of TFPI-2 alone, of the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc, the ABC score and of the weighted proportional hazard model combining the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc, the ABC score with TFPI-2 (log 2) on the case cohort selection. It can be seen that the addition of TFPI-2 improves the c-index of all three risk models. The improvements are 0.0646, 0.0432 and 0.0671 for the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc, the ABC score respectively.
[0428] Table 6 shows the estimated c-indexes of NTproBNP alone, of ESM-1 alone, of Ang-2 alone, of IGFBP-7 alone, of the CHA.sub.2DS.sub.2-VASc score and of the weighted proportional hazard model combining the CHA.sub.2DS.sub.2-VASc score with NTproBNP (log 2), with ESM-1 (log 2), with ANG-2 (log 2), with IGFBP-7 (log 2) on the case cohort selection. It can be seen that the addition of all biomarkers improve the c-index of the CHA.sub.2DS.sub.2-VASc score. The improvements of the the CHA.sub.2DS.sub.2-VASc score are 0.002, 0.064, 0.036 and 0.006 for NTproBNP, ESM-1, Ang-2, IGFBP-7 respectively.
TABLE-US-00006 TABLE 6 C-indexes of TFPI-2, NTproBNP, ESM-1, Ang-2, IGFBP-7, the CHA.sub.2DS.sub.2-VASc score and the combination of the CHA.sub.2DS.sub.2-VASc score with TFPI-2, NTproBNP, ESM-1, Ang-2, IGFBP-7 and C-indexes of the CHADS.sub.2 and ABC score and their combination with TFPI-2. C-Index TFPI-2 univariate 0.682 CHADS.sub.2 0.650 CHADS.sub.2 + TFPI-2 0.715 CHA.sub.2DS.sub.2-VASc 0.674 CHA.sub.2DS.sub.2-VASc + TFPI-2 0.717 ABC score 0.648 ABC score + TFPI-2 0.716 NTproBNP univariate 0.651 CHA.sub.2DS.sub.2-VASc + NTproBNP 0.676 ESM-1 univariate 0.708 CHA.sub.2DS.sub.2-VASc + ESM-1 0.738 Ang-2 univariate 0.696 CHA.sub.2DS.sub.2-VASc + Ang-2 0.710 IGFBP-7 univariate 0.652 CHA.sub.2DS.sub.2-VASc + IGFBP-7 0.680
Example 4: Biomarker Measurements
[0429] TFPI-2 was measured in a commercially available 0-link multi-marker panel for Tissue factor inhibitor-2 (TFPI-2); Proximity Extension Assay from O-link, Sweden.
Example 5: Prediction of Stroke
[0430] Analysis Approach
[0431] The ability of circulating TFPI-2 to predict the risk for the occurrence of stroke was verified (in reference to example 3) in a prospective, multicentric registry of patients with documented atrial fibrillation (Conen D., Swiss Med Wkly. 2017 Jul. 10; 147:w14467). TFPI-2 was measured using a stratified case cohort design as described in Borgan (2000).
[0432] For each of the 68 patients (status April 2019) which experienced a stroke during follow up (“events”), 1 matched control was randomly selected out of 2319 patients without an event.
[0433] TFPI-2, results were available for 62 patients with an event and 61 patients without an event.
[0434] TFPI-2 was measured using the Olink platform therefor no absolute concentration values are available and can be reported. Results will be reported on an arbitrary signal scale (NPX). Please note that therefor no comparison are possible to example 3 in terms of concentration and distribution of the biomarker (e.g. median).
[0435] In order to quantify the univariate prognostic value of TFPI-2 proportional hazard models were used with the outcome stroke.
[0436] The univariate prognostic performance of TFPI-2 was assessed by two different incorporations of the prognostic information given by TFPI-2.
[0437] The first proportional hazard model included TFPI-2 binarized at the median (748 NPX) and therefore comparing the risk of patients with TFPI-2 below or equal to the median versus patient with TFPI-2 above the median.
[0438] The second proportional hazard model included the original TFPI-2 levels but transformed to a log 2 scale. The log 2 transformation was performed in order to enable a better model calibration.
[0439] Because the estimates from a naïve proportional hazard model on the case control cohort would be biased (due to the altered proportion of cases to controls) a weighted proportional hazard model was used. Weights are based on the inverse probability for each patient to be selected for the case control cohort as described in Mark (2006).
[0440] In order to get estimates for the absolute survival rates in the two groups based on the dichotomized baseline TFPI-2 measurement (<=748 NPX vs >748 NPX) a weighted version of the Kaplan-Meier plot was created as described in Mark (2006).
[0441] In order to assess if the prognostic value of TFPI-2 is independent from known clinical and demographic risk factors a weighted proportional cox model including in addition the variables age, and history of Stroke/TIA/Thromboembolism was calculated. These were the only significant clinical risk predictors on the whole cohort (including all controls).
[0442] In order to assess the ability of TFPI-2 to improve existing risk scores for the prognosis of stroke the CHADS.sub.2 the CHA.sub.2DS.sub.2-VASc and the ABC score were extended by TFPI-2 (log 2 transformed). Extension was done by creating a portioned hazard model including TFPI-2 and the respective risk score as independent variables.
[0443] The c-indices of the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc and ABC score were compared to the c-indices of these extended models. For the calculation of the c-index in the case-cohort setting a weighted version of the c-index was used as proposed in Ganna (2011).
[0444] Results
[0445] Table 7 shows the results of the two univariate weighted proportional hazard models including the binarized or the log 2 transformed TFPI-2. The association between the risk for experiencing a stroke with the baseline value of TFPI-2 is highly significant in both models. The hazard ration for the binarized TFPI-2 implies a 2.04-fold higher risk for a stroke in the patient group with baseline TFPI-2>=748 NPX versus the patient group with baseline TFPI2<748 NPX. The results of the proportional hazard model including TFPI-2 as log 2 transformed linear risk predictor suggest the log 2 transformed values TFPI-2 are proportional to the risk for experiencing a stroke. The hazard ratio of 2.54 can be interpreted in a way that a 2-fold increase of TFPI-2 is associated with 2.54 increase of risk for a stroke.
TABLE-US-00007 TABLE 7 Results result of the univariate weighted proportional hazard model including the binarized and log2 transformed TFPI-2. Hazard Ratio (HR) 95%-CI HR P-Value TFPI-2 log2 2.5445 1.2078-5.3606 0.0140 Baseline TFPI-2 >= 748 2.0365 0.9639-4.3030 0.0624 NPX vs TFPI-2 < 748 NPX
[0446] Table 8 shows the results of a proportional hazard model including TFPI-2 (log 2 transformed) in the combination with clinical and demographic variables. It clearly shows that the prognostic effect of TFPI-2 stays stable if adjusting for the prognostic effect of relevant clinical and demographic variables.
TABLE-US-00008 TABLE 8 Multivariate proportional hazard model including TFPI-2 and relevant clinical and demographic variables. Hazard Ratio (HR) 95%-CI HR P-Value Age 1.1347 1.0632-1.2110 0.2488 History 6.7040 2.5049-17.9425 0.1594 Stroke/TIA/embolism TFPI-2 (log2 2.7248 1.1610-6.7540 0.0305 transformed)
[0447] Table 9 shows the results of the weighted proportional hazard model combining the CHADS.sub.2 score with TFPI-2 (log 2 transformed). Also in this model TFPI-2 can add prognostic information to the CHADS.sub.2 score.
TABLE-US-00009 TABLE 9 Weighted proportional hazard model combining the CHADS.sub.2 score with TFPI-2 (log2 transformed) Hazard Ratio (HR) 95%-CI HR P-Value CHADS.sub.2 score 1.4175 0.9690-2.0737 0.0722 TFPI-2 (log2 2.7709 1.2504-6.1405 0.0121 transformed)
[0448] Table 10 shows the results of the weighted proportional hazard model combining the CHA.sub.2DS.sub.2-VASc score with TFPI-2 (log 2 transformed). Also in this model TFPI-2 can add prognostic information to the CHA.sub.2DS.sub.2-VASc score.
TABLE-US-00010 TABLE 10 Weighted proportional hazard model combining the CHA.sub.2DS.sub.2-VASc score with TFPI-2 (log2 transformed) Hazard Ratio (HR) 95%-CI HR P-Value CHA.sub.2DS.sub.2-VASc 1.3497 0.9496-1.9185 0.0946 score TFPI-2 (log2 2.4365 1.1391-5.2114 0.0217 transformed)
[0449] Table 11 shows the results of the weighted proportional hazard model combining the ABC score with TFPI-2 (log 2 transformed). Also in this model TFPI-2 can add prognostic information to the risk score.
TABLE-US-00011 TABLE 11 Weighted proportional hazard model combining the ABC score with TFPI-2 (log2 transformed) Hazard Ratio (HR) 95%-CI HR P-Value ABC score 1.2692 1.0818-1.4892 0.0035 TFPI-2 (log2 1.9093 0.8658-4.2106 0.1090 transformed)
[0450] Table 12 shows the estimated c-indexes of TFPI-2 alone, of the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc, the ABC score and of the weighted proportional hazard model combining the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc, the ABC score with TFPI-2 (log 2) on the case cohort selection. It can be seen that the addition of TFPI-2 improves the c-index of all three risk models. The improvements are 0.057, 0.047 and 0.022 for the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc, the ABC score respectively.
TABLE-US-00012 TABLE 12 C-indexes of TFPI-2, the CHA.sub.2DS.sub.2-VASc score and the combination of the CHA.sub.2DS.sub.2-VASc score with TFPI-2 and C-indexes of the CHADS.sub.2 and ABC score and their combination with TFPI-2. C-Index TFPI-2 univariate 0.608 CHADS.sub.2 0.573 CHADS.sub.2 + TFPI-2 0.630 CHA.sub.2DS.sub.2-VASc 0.577 CHA.sub.2DS.sub.2-VASc + TFPI-2 0.624 ABC score 0.680 ABC score + TFPI-2 0.702
Example 6: Case Studies
[0451] There is growing interest in knowing and reducing the ischemic stroke risk also in patients without atrial fibrillation (Yao X et al, Am Heart J. 2018; 199:137-143). For example, predicting the stroke risk is essential to establish optimum treatment strategies by identifying and including these patients at high stroke risk into drug studies with oral anticoagulation.
[0452] The CHA2DS2-VASc score, for example, predicts incidence of ischemic stroke also in patients without atrial fibrillation, but with a lower absolute event rate (Mitchell L B et al, Heart. 2014; 100:1524-30). (Therefore, it is less clear, if and at what CHA2DS2-VASc score these patients without atrial fibrillation should receive oral anticoagulation (OAC) and at which dose, so that biomarkers such as TFPI2 help to assess the need for therapy and effectiveness of OAC.
[0453] A 76 year old female patient with hypertension and no history of atrial fibrillation presents in sinus rhythm. TFPI2 is determined in an EDTA plasma sample obtained from the patient. The clinical information of the CHA2DS2-VASc score (advanced age and hypertension) indicate a certain stroke risk, and in addition the TFPI2 value is above a reference value. The elevated TFPI2 titers is indicative of high risk to experience a stroke. As consequence the patient is admitted to an anticoagulation therapy.
[0454] A 65 year old male patient without a history of atrial fibrillation requests a checkup at the doctor's office. The presents in sinus rhythm, however structural heart disease is diagnosed. Because of the history of stroke and high overall CHA2DS2-VASc score, the patient already receives oral anticoagulation therapy (at low dose). In order to determine the current risk of stroke and to conclude on eventual therapy change, TFPI2 is measured in a serum sample obtained from the patient. The observed TFPI2 value is above a reference value. The elevated TFPI2 titers and other risk parameters (history of stroke) are indicative of a high residual stroke risk that is higher than the bleeding risk (assessed with other clinical information). As consequence the dosage of the anticoagulation therapy is increased.
[0455] A 68 year old obese female patient with Diabetes Mellitus and heart failure with reduced ejection fraction presents with acute symptoms of shortness of breath. In prior visits, the patient has no history of atrial fibrillation. According to a high overall CHA2DS2-VASc risk score, the physician decided to start oral anticoagulation (low dose) even in the absence of AFib. The TFPI2 level was determined before and after onset of anticoagulation. The patient now is wondering whether the anticoagulation therapy is effective and still necessary. In order to specify the current risk of stroke, TFPI2 is determined in an EDTA sample obtained from the patient. The observed TFPI2 value is below a reference value and lower as compared to the treatment start. The reduced TFPI2 titers are indicative of an effective anticoagulation therapy. As consequence the anticoagulation therapy is maintained.
[0456] Summary: The studies underlying the present invention show that TFPI-2 can be used to diagnose AF, to classify AF, to assess the AF severity, to guide therapy (with objectives to therapy intensification/reduction), to predict disease outcome (risk prediction, e.g. stroke), therapy monitoring, therapy stratification (selection of therapy options).