NT-proBNP by Itself Predicts Death and Cardiovascular Events in High-Risk Patients With Type 2 Diabetes Mellitus

Abstract

Background NT-proBNP (N-terminal pro-B-type natriuretic peptide) improves the discriminatory ability of risk-prediction models in type 2 diabetes mellitus (T2DM) but is not yet used in clinical practice. We assessed the discriminatory strength of NT-proBNP by itself for death and cardiovascular events in high-risk patients with T2DM. Methods and Results Cox proportional hazards were used to create a base model formed by 20 variables. The discriminatory ability of the base model was compared with that of NT-proBNP alone and with NT-proBNP added, using C-statistics. We studied 5509 patients (with complete data) of 8561 patients with T2DM and cardiovascular and/or chronic kidney disease who were enrolled in the ALTITUDE (Aliskiren in Type 2 Diabetes Using Cardiorenal Endpoints) trial. During a median 2.6-year follow-up period, 469 patients died and 768 had a cardiovascular composite outcome (cardiovascular death, resuscitated cardiac arrest, nonfatal myocardial infarction, stroke, or heart failure hospitalization). NT-proBNP alone was as discriminatory as the base model for predicting death (C-statistic, 0.745 versus 0.744, P=0.95) and the cardiovascular composite outcome (C-statistic, 0.723 versus 0.731, P=0.37). When NT-proBNP was added, it increased the predictive ability of the base model for death (C-statistic, 0.779 versus 0.744, P<0.001) and for cardiovascular composite outcome (C-statistic, 0.763 versus 0.731, P<0.001). Conclusions In high-risk patients with T2DM, NT-proBNP by itself demonstrated discriminatory ability similar to a multivariable model in predicting both death and cardiovascular events and should be considered for risk stratification. Registration URL: https://www.clini​caltr​ials.gov; Unique identifier: NCT00549757.

Keywords: cardiovascular diseases; diabetes complications; diabetes mellitus; proportional hazards models; pro‐B-type natriuretic peptide; type 2.

Conflict of interest statement

Malachias serves on the advisory board and receives speaker fees from Biolab Sanus and Libbs, Brazil. Jhund receives speaker fees from Novartis and AstraZeneca; serves on the advisory boards of Novartis and Cytokinetics; receives research funding from Boehringer Ingelheim; and has been remunerated for time working on the DAPA‐HF, PARADIGM‐HF and PARAGON‐HF trials by the University of Glasgow. Wijkman is supported by grants from the Fulbright Commission, the Swedish Heart Association, the Swedish Society of Medicine, and Region Östergötland, Sweden; has served on advisory boards or lectured for MSD, Lilly, Novo Nordisk, and Sanofi; has organized a professional regional meeting sponsored by Lilly, Rubin Medical, Sanofi, Novartis and Novo Nordisk. Bentley‐Lewis is consultant to the TIMI (Thrombolysis in Myocardial Infarction) Study Group and Novo Nordisk. Chaturvedi serves as a data safety monitoring committee member for a trial sponsored by AstraZeneca. Desai receives research grants from Alnylam, AstraZeneca, and Novartis and consulting fees from Abbott, Alnylam, AstraZeneca, Amgen, Biofourmis, Boston Scientific, Boehringer‐Ingelheim, Corvidia, DalCor Pharma, Merck, Novartis, Relypsa, and Regeneron. Prescott is an employee of Novartis Pharmaceuticals. Solomon has received research grants from Alnylam, Amgen, AstraZeneca, Bellerophon, Bayer, BMS, Celladon, Cytokinetics, Eidos, Gilead, GSK, Ionis, Lone Star Heart, Mesoblast, MyoKardia, NIH/NHLBI, Novartis, Sanofi Pasteur, and Theracos and has consulted for Akros, Alnylam, Amgen, Arena, AstraZeneca, Bayer, BMS, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi‐Sankyo, Gilead, GSK, Ironwood, Merck, Myokardia, Novartis, Roche, Takeda, Theracos, Quantum Genetics, Cardurion, AoBiome, Janssen, Cardiac Dimensions, Tenaya, Dinaqor, Tremeau. De Zeeuw serves on advisory boards and/or speaker for Bayer, Boehringer Ingelheim, Fresenius, Mundipharma, Mitsubishi‐Tanabe; steering committees and/or speaker for AbbVie and Janssen; and data safety and monitoring committees for Bayer. McMurray receives fees (all fees listed paid to Glasgow University) for serving on a steering committee from Bayer, fees for serving on a steering committee, fees for serving on an end point committee, and travel support from Cardiorentis, fees for serving on a steering committee and travel support from Amgen, fees for serving on a steering committee and travel support from Oxford University/Bayer, fees for serving as principal investigator of a trial and travel support from Theracos, fees for serving on a steering committee and travel support from AbbVie, fees for serving on a steering committee from DalCor, fees for serving on a data safety monitoring committee from Pfizer, fees for serving on a data safety monitoring committee from Merck, fees for serving on an executive committee, fees for serving as co‐principal investigator of a trial, fees for serving on a steering committee, fees for serving on an executive committee, travel support, and advisory board fees from Novartis, fees for serving as co‐principal investigator for a trial, fees for serving on a steering committee, and travel support from GlaxoSmithKline, fees for serving on a steering committee from Bristol‐Myers Squibb, fees for serving on a steering committee, fees for serving on an endpoint adjudication committee, and travel support from Vifor‐Fresenius. Pfeffer receives research support from Novartis; serves as a consultant for AstraZeneca, Corvidia, DalCor, GlaxoSmithKline, Jazz, MyoKardia, Novartis, Novo Nordisk, Pharmascience, Sanofi, and Takeda; and has equity in DalCor. The remaining authors have no disclosures to report.

Figures

Figure 1. Death prediction models by deciles of predicted risk/deciles of NT‐proBNP.

NT‐proBNP indicates N‐terminal pro‐B‐type natriuretic peptide; and py, person/years. Base Model: formed by high sensitivity cardiac troponin, age, albumin, history of heart failure, heart rate, history of stroke, HbA1c, smoking, left ventricular hypertrophy on ECG, Q wave on ECG, history of atrial fibrillation, any bundle branch block on ECG, urine albumin‐to‐creatinine ratio, systolic blood pressure, sex, history of coronary heart disease, low density lipoprotein cholesterol, estimated glomerular filtration rate, insulin use, and diastolic blood pressure, in decreasing order of χ2; v=variables. Error bars represent 95% CIs.

Figure 2. Cardiovascular composite outcome prediction models by deciles of predicted risk/deciles of NT‐proBNP.

NT‐proBNP indicates N‐terminal pro‐B‐type natriuretic peptide; and py, person/years. Base Model: formed by high sensitivity cardiac troponin, history of heart failure, age, albumin, low density lipoprotein cholesterol, history of atrial fibrillation, history of stroke, systolic blood pressure, HbA1c, smoking, history of coronary heart disease, sex, urine albumin‐to‐creatinine ratio, any bundle branch block on ECG, diastolic blood pressure, insulin use, Q wave on ECG, heart rate, left ventricular hypertrophy on ECG, and estimated glomerular filtration rate, in decreasing order of χ2; v=variables. Error bars represent 95% CIs.