Statistical method improves treatment effect estimation in oncology trials, indicating enhanced power and accurate confidence intervals.
In oncology trials, patients in both the control and experimental arms can receive different subsequent anti-cancer therapies (SATs) after discontinuing their randomized study drugs, a phenomenon commonly referred to as treatment switching. SATs may have the potential to extend overall survival (OS) in patients treated with the control and experimental drugs. Without recovering the information from the SATs, the statistical power of the clinical trials could be drastically reduced, thus making it difficult or impossible to meet the efficacy objective. This article presents a novel statistical method for imputing the post-switching survival time multiple times to derive the point estimate of the true hazard ratio (HR) of OS between the experimental and control drugs and the associated 95% confidence interval (CI). The proposed method provides an effective solution for recovering lost information in the OS caused by SATs. It also offers an efficient way to evaluate the true causal treatment effect, potentially increasing the statistical power. Additionally, this method can be used for patients with a crossover from a placebo to an experimental treatment in placebo-controlled trials. Simulation studies demonstrated that the proposed method performed well and reliably, and applications to oncology trials using the simulated data are provided.
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Jianbo Xu (2025) studied this question.
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