Abstract

Win statistics offer a new approach to the analysis of outcomes in clinical trials, allowing the combination of time-to-event and longitudinal measurements and taking into account the clinical importance of the components of composite outcomes, as well as their relative timing. We examined this approach in a post hoc analysis of two trials that compared dapagliflozin to placebo in patients with heart failure and reduced ejection fraction (DAPA-HF) and mildly reduced or preserved ejection fraction (DELIVER). The effect of dapagliflozin on a hierarchical composite kidney outcome was assessed, including the following: (1) all-cause mortality; (2) end-stage kidney disease; (3) a decline in estimated glomerular filtration rate (eGFR) of ≥57%; (4) a decline in eGFR of ≥50%; (5) a decline in eGFR of ≥40%; and (6) participant-level eGFR slope. For this outcome, the win ratio was 1.10 (95% confidence interval (CI) = 1.06–1.15) in the combined dataset, 1.08 (95% CI = 1.01–1.16) in the DAPA-HF trial and 1.12 (95% CI = 1.05–1.18) in the DELIVER trial; that is, dapagliflozin was superior to placebo in both trials. The benefits of treatment were consistent in participants with and without baseline kidney disease, and with and without type 2 diabetes. In heart failure trials, win statistics may provide the statistical power to evaluate the effect of treatments on kidney as well as cardiovascular outcomes.