Systematic Evaluation of Data and Trial Fitness for Oncology Trial Emulation: Empirical Findings from the CARE Initiative

Clinical Pharmacology & Therapeutics

Jun 04, 2026
Oncology
Manuscript

Natalie Levy, Paige Sheridan, Ulka Campbell, David Lenis, Inish O'Doherty, Adina Estrin, Nileesa Gautam, Monica Iyer, Sarah McDonald, Andrew Belli, Gillis Carrigan, K. Arnold Chan, James Chen, Victoria Chia, Neil Dhopeshwarkar, Joy Eckert, Laura Fernandes, Joel Greshock, Rachele Hendricks‐Sturrup, Jenny Huang, XiaoLong Jiao, Sajan Khosla, Orsolya Lunacsek, Lynn McRoy, Yanina Natanzon, Osayi Ovbiosa, Nelson Pace, Simone Pinheiro, Megan Rees, Jennifer Rider, Mothaffar Fahed Rimawi, Travis Robinson, Carla Rodriguez‐Watson, Chithra Sangli, Khaled Sarsour, Sebastian Schneeweiss, Mark Shapiro, Mark Stewart, Aliki Taylor, C. K. Wang, Shirley Wang, Yiduo Zhang, Ann Madsen

Abstract
The Coalition to Advance Real-World Evidence through Randomized Controlled Trial Emulation (CARE) Initiative seeks to advance understanding of when real-world data (RWD) can generate valid treatment effectiveness estimates by emulating completed oncology randomized controlled trials (RCTs). A prerequisite for meaningful RCT emulation insights is the identification and use of RWD with sufficient fitness to satisfy RCT-specific data elements. We conducted a systematic, multi-stage feasibility assessment of six commercially available US electronic health record-based RWD sources across 23 candidate oncology RCTs. Each potential RCT-RWD combination was first screened for availability of the RCT indication, outcomes, and sample size ≥ 1.5-times enrollment for each trial arm. Combinations passing this screen underwent more detailed evaluation of RCT design elements including eligibility criteria, outcomes, and potential confounders. Each data element was rated with respect to availability, missingness, and validity. Final feasibility determination was informed by ratings of essential element capture and refined sample size estimates. Of 54 candidate RCT-RWD combinations assessed, nine advanced to detailed feasibility assessment and three were selected for emulation protocol development. Fit-for-emulation constraints included complex eligibility criteria, biomarker requirements, performance status requirements, and outcome ascertainment. These findings highlight the importance of systematic feasibility evaluation before conducting emulations and may inform data selection for future RWD studies in oncology. Data fitness for oncology RCT emulation could be improved by linking high-quality, oncology-specific RWD sources to broader EHR and claims data sources or through customized data abstraction.