Comparison of two‐stage and joint TGI‐OS modeling using data from six atezolizumab clinical studies in patients with metastatic non‐small cell lung cancer

Abstract

AbstractTwo‐stage and joint modeling approaches are the two main approaches to investigate the link between longitudinal tumor size data and overall survival (OS) and anticipate clinical trial outcome. We here used a large database composed of one phase II and five phase III clinical trials evaluating atezolizumab (an immunotherapy) in monotherapy or in combination with chemotherapies in 3699 patients with non‐small cell lung cancer to evaluate the differences between both approaches in terms of parameter estimates, magnitude of covariate effects, and ability to predict OS. Although the two‐stage approach may underestimate the magnitude of the impact of tumor growth rate (KG) on OS compared to joint modeling approach (hazard ratios [HRs] of 0.42–2.52 vs. 0.25–2.85, respectively, for individual KG varying from the 5th and 95th percentiles), this difference did not lead into poorer performance of the two‐stage approach to describe the OS distribution in the six clinical studies. Overall, two‐stage and joint modeling approaches accurately predicted OS HR with a median (range) difference with the observed OS HR of 0.02 (0.01–0.18) and 0.03 (0.00–0.19), in all cases considered, respectively (e.g., for IMpower150: 0.80 [0.66–0.95] vs. 0.82 [0.70–0.95], respectively, whereas the observed OS HR was 0.80). In our setting, the two‐stage approach accurately predicted the benefit of atezolizumab on OS. Further work is needed to verify if similar results are achieved using phase Ib or phase II clinical trials where the number of patients and measurements is limited as well as in other cancer indications.