Evaluating treatment efficacy in hospitalized COVID-19 patients, with applications to Adaptive COVID-19 Treatment Trials

Abstract

<h3>Background</h3><p>The current endpoints for therapeutic trials of hospitalized COVID-19 patients capture only part of the clinical course of a patient and have limited statistical power and robustness.</p><h3>Methods</h3><p>We specify proportional odds models for repeated measures of clinical status, with a common odds ratio of lower severity over time. We also specify the proportional hazards model for time to each level of improvement or deterioration of clinical status, with a common hazard ratio for overall treatment benefit. We apply these methods to Adaptive COVID-19 Treatment Trials.</p><h3>Results</h3><p>For remdesivir versus placebo, the common odds ratio was 1.48 (95% confidence interval (CI) = 1.23–1.79; p < 0.001), and the common hazard ratio was 1.27 (95% CI = 1.09–1.47; p = 0.002). For baricitinib plus remdesivir versus remdesivir alone, the common odds ratio was 1.32 (95% CI = 1.10–1.57; p = 0.002), and the common hazard ratio was 1.30 (95% CI = 1.13–1.49; p < 0.001). For interferon beta-1a plus remdesivir versus remdesivir alone, the common odds ratio was 0.95 (95% CI = 0.79–1.14; p = 0.56), and the common hazard ratio was 0.98 (95% CI = 0.85–1.12; p = 0.74).</p><h3>Conclusions</h3><p>The proposed methods comprehensively characterize the treatment effects on the entire clinical course of a hospitalized COVID-19 patient.</p>