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There is an increasing interest in the use of win ratio with composite time-to-event due to its flexibility in combining component endpoints. Exploring this flexibility further, one interesting question is in assessing the impact when there is a difference in treatment effect in the component endpoints. For example, the active treatment may prolong the time to occurrence of the negative event such as death or ventilation; meanwhile, the treatment effect may also shorten the time to achieving positive events, such as recovery or improvement. Notably, this portrays a situation where the treatment effect on time to recovery is in a different direction of benefit compared to the time to ventilation or death. Under such circumstances, if a single endpoint is used, the benefit gained for other individual outcomes is not counted and is diminished. As consequence, the study may need a larger sample size to detect a significant effect of treatment. Such a scenario can be handled by win ratio in a novel way by ranking component events, which is different from the usual composite endpoint approach such as time-to-first event. To evaluate how the different directions of treatment effect on component endpoints will impact the win ratio analysis, we use a Clayton copula-based bivariate survival simulation to investigate the correlation of component time-to-event. Through simulation, we found that compared to the marginal model using single endpoints, the win ratio analysis on composite endpoint performs better, especially when the correlation between two events is weak. Then, we applied the methodology to an infectious disease progression simulated study motivated by COVID-19. The application demonstrates that the win ratio approach offers advantages in empirical power compared to the traditional Cox proportional hazard approach when there is a difference in treatment effect in the marginal events., (© 2022 John Wiley & Sons Ltd.)

Aims: Data regarding patients with chronic heart failure (HF) and reduced ejection fraction (HFrEF) following a worsening HF event (WHFE) are largely driven by findings from elderly patients. Younger patients are not well studied. The aim of this study was to evaluate treatment patterns and clinical outcomes in commercially insured chronic HFrEF patients <65 years old during 1-year periods before and after a WHFE., Methods and Results: A retrospective claims analysis was performed using the IBM® MarketScan® Commercial Database on HFrEF patients aged <65 years during the year before and after a WHFE, defined as HF hospitalization or outpatient intravenous diuretic use. Treatment patterns, rehospitalizations, health care resource utilization, and costs were assessed. A total of 4460 HFrEF patients with WHFE were included. Guideline-recommended HF therapy was initially underutilized, increased pre-WHFE, and peaked 0-3 months post-WHFE. The proportions of patients using dual and triple therapy were 31.5% and 9.8% pre-WHFE, 41.5% and 17.4% 0-3 months post-WHFE, and 34.6% and 13.9% 10-12 months post-WHFE, respectively. Within 30 and 90 days after a WHFE, 12% and 23% of patients had HF-related and 16% and 30% had all-cause rehospitalizations, respectively. HF-related and all-cause hospitalizations and outpatient visits peaked 0-3 months post-WHFE, whereas emergency department visits peaked 0-3 months pre-WHFE., Conclusions: Use of HF medications increased pre-WHFE but decreased post-WHFE, despite recurrent hospitalizations. These findings suggest that age and insurance status may not totally explain the suboptimal treatment of HFrEF patients before and after a WHFE. Reasons for these trends need further study., (© 2021 European Society of Cardiology.)