Impact of differences between interim and post-interim analysis populations on outcomes of a group sequential trial: Example of the MOVe-OUT study

Abstract

Background

Pre-specified interim analyses allow for more timely evaluation of efficacy or futility, potentially accelerating decision-making on an investigational intervention. In such an analysis, the randomized, double-blind MOVe-OUT trial demonstrated superiority of molnupiravir over placebo for outpatient treatment of COVID-19 in high-risk patients. In the full analysis population, the point estimate of the treatment difference in the primary endpoint was notably lower than at the interim analysis. We conducted a comprehensive assessment to investigate this unexpected difference in treatment effect size, with the goal of informing future clinical research evaluating treatments for rapidly evolving infectious diseases.

Methods

The modified intention-to-treat population of the MOVe-OUT trial was divided into an interim analysis cohort (i.e. all participants included in the interim analysis; prospectively defined) and a post-interim analysis cohort (i.e. all remaining participants; retrospectively defined). Baseline characteristics (including many well-established prognostic factors for disease progression), clinical outcomes, and virologic outcomes were retrospectively evaluated. The impact of changes in baseline characteristics over time was explored using logistic regression modeling and simulations.

Results

Baseline characteristics were well-balanced between arms overall. However, between- and within-arm differences in known prognostic baseline factors (e.g. comorbidities, SARS-CoV-2 viral load, and anti-SARS-CoV-2 antibody status) were observed for the interim and post-interim analysis cohorts. For the individual factors, these differences were generally minor and otherwise not notable; as the trial progressed, however, these shifts in combination increasingly favored the placebo arm across most of the evaluated factors in the post-interim cohort. Model-based simulations confirmed that the reduction in effect size could be accounted for by these longitudinal trends toward a lower-risk study population among placebo participants. Infectivity and viral load data confirmed that molnupiravir’s antiviral activity was consistent across both cohorts, which were heavily dominated by different viral clades (reflecting the rapid SARS-CoV-2 evolution).

Discussion

The cumulative effect of randomly occurring minor differences in prognostic baseline characteristics within and between arms over time, rather than virologic factors such as reduced activity of molnupiravir against evolving variants, likely impacted the observed outcomes. Our results have broader implications for group sequential trials seeking to evaluate treatments for rapidly emerging pathogens. During dynamic epidemic or pandemic conditions, adaptive trials should be designed and interpreted especially carefully, considering that they will likely rapidly enroll a large post-interim overrun population and that even small longitudinal shifts across multiple baseline variables can disproportionately impact prespecified efficacy outcomes at different timepoints. Shifts in prognostic factors may introduce additional variability that can be difficult to disentangle from temporal trends in epidemiology (e.g. evolutionary changes in the causative pathogen) or disease management.

(ClinicalTrials.gov: NCT04575597.)