Overcoming UNDERPOWERING: Trial simulations and a global rank endpoint to optimize clinical trials in children with heart disease

Abstract Background Randomized controlled trials (RCTs) in children with heart disease are challenging and therefore infrequently performed. We sought to improve feasibility of perioperative RCTs for this patient cohort using data from a large, multi-center clinical registry. We evaluated potential enrollment and endpoint frequencies for various inclusion cohorts and developed a novel global rank trial endpoint. We then performed trial simulations to evaluate power gains with the global rank endpoint, and with use of planned covariate adjustment as an analytic strategy. Methods Data from the Society of Thoracic Surgery-Congenital Heart Surgery Database (STS-CHSD, 2011–2016) were used to support development of a consensus-based global rank endpoint and for trial simulations. For Monte Carlo trial simulations (n = 50,000/outcome), we varied the odds of outcomes for treatment vs placebo and evaluated power based on the proportion of trial datasets with a significant outcome (P  Results The STS-CHSD study cohort included 35,967 infant index cardiopulmonary bypass operations from 103 STS-CHSD centers, including 11,411 (32%) neonatal cases, and 12,243 (34%) high complexity (STAT Mortality Category ≥4) cases. In trial simulations, study power was 21% for a mortality only endpoint, 47% for a morbidity and mortality composite, and 78% for the global rank endpoint. With covariate adjustment, power increased to 94%. Planned covariate adjustment was preferable to restricting to higher risk cohorts despite higher event rates in these cohorts. Conclusion Trial simulations can inform trial design. Our findings, including the newly developed global rank endpoint, may be informative for future perioperative trials in children with heart disease.