Augmented two-stage estimation for treatment switching in oncology trials: Leveraging external data for improved precision.

ABSTRACT: Randomized controlled trials in oncology often allow control group participants to switch to experimental treatments, a practice that, while often ethically necessary, complicates the accurate estimation of long-term treatment effects. When switching rates are high or sample sizes are limited, commonly used methods for treatment switching adjustment (such as the rank-preserving structural failure time model, inverse probability of censoring weights, and two-stage estimation) may produce imprecise estimates. Real-world data can be used to develop an external control arm for the randomized controlled trial, although this approach ignores evidence from trial subjects who did not switch and ignores evidence from the data obtained prior to switching for those subjects who did. This article intr

SUBMITTER: Campbell H 

PROVIDER: S-EPMC12669390 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature