Liu, Yu‐Lun
Mayo Clinic
The University of Texas Southwestern Medical Center
Citations 1
Federated target trial emulation for time-to-event outcomes via POLARIS: Pooled-equivalent One-shot Likelihood Aggregation for Real-world Inference in Survival
Wang, Tingyin, Lei, Yuqing , Li, Lu , Wang, Yudong, Wu, Yue, Chen, Siqi, Zhang, Bingyu, Feng, Jingna , Kong, Zifang, Wang, Chengrong, Zhou, Yujia, Amaro, Anastassia , Qiu, Jingmei, Lu, Yuan, Liu, M , Tao, Cui, Xu, Hua, Lu, Yiwen, Chen, Yi , Tang, Huilin , Zhang, Bingyu , Hu, Jie , Wang, Huiyuan, Liu, Yu‐Lun , Chen, Yong
No container title available | May 20, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Heterogeneous treatment effects (HTE) are key to precision medicine, but most real-world studies lack the scale and diversity needed to detect them. While multi-site analyses offer a potential solution, data-sharing constraints often prevent access to patient-level information across institutions. We introduce POLARIS, a federated framework for time-to-event target trial emulation. POLARIS converts each site’s weighted Cox risk function into a compact tensor shared once with the coordinating center, enabling lossless reproduction of pooled estimates without sharing patient-level data. We applied POLARIS across five U.S. health systems to study risk of gastrointestinal outcomes after GLP-1 receptor agonist (GLP-1RAs) initiation versus sodium-glucose cotransporter 2 inhibitors (SGLT2is) and dipeptidyl peptidase 4 inhibitors (DPP4is). Results showed that GLP-1RAs were consistently associated with higher risks of nausea and vomiting, particularly among men, individuals with higher baseline HbA1c (≥ 8.5%), and lipid therapy. POLARIS provides a scalable solution for distributed target trial emulation and fine-grained assessment of HTE across diverse health systems.