Evaluating treatment efficacy in hospitalized COVID-19 patients, with applications to Adaptive COVID-19 Treatment Trials
Dan-Yu Lin, Jianqiao Wang, Yu Gu, Donglin Zeng- Pharmacology
- General Medicine
Background
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.
Methods
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.
Results
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).
Conclusions
The proposed methods comprehensively characterize the treatment effects on the entire clinical course of a hospitalized COVID-19 patient.