All Lines Is the Right Approach: Selecting Patient Lines of Therapy for an External Comparator Arm

To identify the best method for selecting index dates when constructing external comparator arms (ECAs) from real-world data for comparison with single-arm trials (SATs).

We evaluated four approaches for index date selection-first eligible line, last eligible line, random eligible line, and all eligible lines-using causal inference reasoning, numerical examples and a simulation study. Simulations modeled survival across multiple lines of therapy under scenarios with varying eligibility patterns and treatment effects. Overall survival (OS) estimates comparing SAT and ECA populations were obtained using stratified Cox models and propensity-weighted Cox models, adjusted for line of therapy and patient state.

Including all eligible lines produced unbiased OS estimates across scenarios. Selecting the last eligible line introduced substantial bias, while random selection led to moderate bias.

Using all eligible lines of therapy for each patient when constructing ECAs minimizes bias and preserves the SAT target population. Alternative methods can lead to biased estimates or, in the case of the first eligible line method, require changes to the clinical question that may shrink the SAT population. We recommend adopting the all eligible lines method with variance correction and adjustment for line of therapy to ensure valid comparative effectiveness analyses.