All Times EDT
Keywords: adaptive, platform trial, bayesian, covid-19, long-term outcomes
REMAP-CAP is an adaptive platform trial exploring treatments for patients hospitalized with COVID-19 by randomizing patients within multiple treatment domains simultaneously. The platform has resulted in conclusions on the effectiveness of interventions including corticosteroids, immune modulators, convalescent plasma, and antiviral interventions. In addition to the primary outcome of organ support-free days through day 21, the platform collected long-term survival and quality-of-life (QoL) outcomes at six months. This poster will describe the pre-specified analysis plan, observed data, and results of the analysis of the effect of randomized treatments on long-term outcomes. We present a joint Bayesian mixture model for survival time through six months and EQ-5D QoL utility score in survivors to evaluate treatment effects on QoL outcomes while incorporating the competing risk of death. Finally, we explore whether treatment effects observed on shorter-term outcomes persist over long-term follow-up and across endpoints measuring survival and quality-of-life.