Optimizing immunotherapy for advanced gastric and gastroesophageal junction cancer: A modelling cost-effectiveness study.

Abstract

e23113 Background: The optimal use of programmed death-ligand 1 (PD-L1) expression to guide immunotherapy in advanced gastric or gastroesophageal junction cancer (GC/GEJC) remains uncertain. The inconsistencies in PD-L1 scoring methods (combined positive score (CPS) or tumor area positivity (TAP)) at various thresholds (1% vs. 1, 5% vs. 5, and 10% vs. 10) complicate clinical decision-making. This study evaluated the effectiveness and cost-effectiveness of CPS and TAP scoring methods across PD-L1 cut-off thresholds in GC/GEJC immunotherapy. Methods: This study developed a microsimulation model by using reconstructed patient-level data from the RATIONALE-305 and ORIENT-16 trials to simulate outcomes for six PD-L1 guided strategies using either sintilimab or tislelizumab, combined with chemotherapy. Primary endpoints included progression-free survival (PFS) and overall survival (OS). Costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) were calculated from the perspective of the Chinese healthcare system. Results: For sintilimab-based strategies, CPS-5 and CPS-10 guided strategies showed statistically significant improvements in OS over TAP-5% and TAP-10% guided strategies, while CPS-1 guided strategies showed statistically significant improvements in PFS versus TAP-1% guided strategies. CPS-10 guided strategy was optimal for sintilimab with an ICER of $21,904/QALY. For tislelizumab-based strategies, no significant differences in OS or PFS were observed across scoring methods, with TAP-10% showing cost-effectiveness. Sensitivity analysis underscored the robustness of results, confirming TAP-10% as cost-effective for tislelizumab and CPS-10 for sintilimab. Conclusions: A 10 or 10% PD-L1 cut-off is the most cost-effective threshold for both sintilimab- and tislelizumab-based strategies. CPS is preferred for sintilimab and TAP for tislelizumab, highlighting the need for tailored PD-L1 scoring methods for different therapies to optimize both clinical and economic outcomes.