Abstract 16789: Modeling the Optimal Strategy of Natriuretic Peptide Testing for Heart Failure Prevention in Diabetes: A Pooled Cohort Analysis

Abstract

Introduction: N-terminal pro-B-type natriuretic peptide (NT-proBNP) is associated with heart failure (HF) risk and measurement is recommended in diabetes. Incorporation of NT-proBNP with WATCH-DM, a HF risk score validated in diabetes, improved HF risk prediction in low-risk individuals (score <13). Whether WATCH-DM can improve the yield of NT-proBNP testing and inform allocation of SGLT2 inhibitors is unknown. Methods: Adults with diabetes and free of HF at baseline from ARIC, CHS, CRIC, DHS, FOS, and MESA cohorts were included. Participants without cardiovascular disease (CVD) were stratified into high- vs. low-risk categories based on 4 approaches: 1) WATCH-DM (score ≥ vs. <13); 2) NT-proBNP (≥ vs. <125 pg/mL); 3) WATCH-DM plus NT-proBNP (both high vs. not); 4) WATCH-DM-based NT-proBNP (if score <13, measure NT-proBNP) (either high vs. not). Five-year cumulative incidence rates of HF, number needed to treat (NNT 5 ) and number needed to screen (NNS 5 ) were estimated based on pooled treatment effects of SGLT2 inhibitors. Results: The study included 6,410 participants (47.5% women, 35.1% Black, 20.5% with CVD) with 428 (6.7%) incident HF events over 5-year follow-up. The 5-year risk of HF was 12.3% among participants with CVD and comparable to those without CVD identified as high-risk based on all 4 approaches ( Figure ). Among participants without CVD, WATCH-DM-based NT-proBNP identified 46% of participants as high-risk and accounted for 80% of HF events. The NNT 5 with an SGLT2 inhibitor to prevent 1 HF event in participants with CVD was 25 and similar to the primary prevention population identified as high-risk ( Figure ). The NNS 5 was lowest in the WATCH-DM-based NT-proBNP strategy ( Figure ). Conclusions: Selective NT-proBNP assessment based on a validated clinical risk score for HF improved the yield of testing and may represent an efficient approach to risk stratification and allocation of therapies among individuals with diabetes.