Identifying surrogate markers in real‐world comparative effectiveness research. (5th September 2022)

• Record Type: Journal Article
• Authors: Han, Larry; Wang, Xuan; Cai, Tianxi
• Is Part Of: Statistics in medicine. Volume 41:Number 26(2022)
• Page Start: 5290
• Page End: 5304
• Publication Date: 2022-09-05
• Subjects: comparative effectiveness research -- double robustness -- inflammatory bowel disease -- proportion of treatment effect explained -- semi‐nonparametric estimation -- surrogate marker; Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.9569
• Languages: English
• ISSNs: 0277-6715

Abstract

Abstract : In comparative effectiveness research (CER), leveraging short‐term surrogates to infer treatment effects on long‐term outcomes can guide policymakers evaluating new treatments. Numerous statistical procedures for identifying surrogates have been proposed for randomized clinical trials (RCTs), but no methods currently exist to evaluate the proportion of treatment effect (PTE) explained by surrogates in real‐world data (RWD), which have become increasingly common. To address this knowledge gap, we propose inverse probability weighted (IPW) and doubly robust (DR) estimators of an optimal transformation of the surrogate and the corresponding PTE measure. We demonstrate that the proposed estimators are consistent and asymptotically normal, and the DR estimator is consistent when either the propensity score model or outcome regression model is correctly specified. Our proposed estimators are evaluated through extensive simulation studies. In two RWD settings, we show that our method can identify and validate surrogate markers for inflammatory bowel disease (IBD).