Model-Based Meta-Analysis of Objective Response Rate and Survival Endpoints to Compare PD-1 and PD-L1 Treatment Outcomes in Non-Small Cell Lung Cancer

This study used model-based meta-analysis (MBMA) to assess how well objective response rate (ORR) predicts longer-term outcomes such as progression-free survival (PFS) and overall survival (OS) in patients with metastatic non-small-cell lung cancer (mNSCLC) treated with PD-1 or PD-L1 inhibitors. The authors analyzed data from 114 clinical studies, applying advanced statistical models to link short-term responses (ORR) with survival outcomes, while accounting for treatment type and clinical covariates such as PD-L1 expression and patient characteristics. They found that ORR is a meaningful predictor of both PFS and OS across treatments. The models were then used to simulate head-to-head comparisons between PD-1 and PD-L1 inhibitors, which showed trends favoring PD-1 agents numerically, although differences were not statistically significant. Overall, this work supports using early ORR data to inform late-stage trial design and decision making, enabling more evidence-based comparisons and reducing uncertainty when planning oncology development strategies.