A practical analysis procedure on generalizing comparative effectiveness in the randomized clinical trial to the real-world trial-eligible population

When evaluating the effectiveness of a drug, a randomized controlled trial (RCT) is often considered the gold standard due to its ability to balance effect modifiers through randomization. While RCT assures strong internal validity, its restricted external validity poses challenges in extending treatment effects to the broader real-world population due to possible heterogeneity in covariates. In this paper, we introduce a procedure to generalize the RCT findings to the real-world trial-eligible population based on the adaption of existing statistical methods. We utilized the augmented inversed probability of sampling weighting (AIPSW) estimator for the estimation and omitted variable bias framework to assess the robustness of the estimate against the assumption violation caused by potentially unmeasured confounders. We analyzed an RCT comparing the effectiveness of lowering hypertension between Songling Xuemaikang Capsule (SXC) — a traditional Chinese medicine (TCM), and Losartan as an illustration. Based on current evidence, the generalization results indicated that by adjusting covariates distribution shift, although SXC is less effective in lowering blood pressure than Losartan on week 2, there is no statistically significant difference among the trial-eligible population at weeks 4–8. In addition, sensitivity analysis further demonstrated that the generalization is robust against potential unmeasured confounders.