Prognostic Value of Programmed Death Ligand-1 Expression in Solid Tumors Irrespective of Immunotherapy Exposure: A Systematic Review and Meta-Analysis.

Abstract

The programmed cell death-1/programmed cell death ligand-1 (PD-L1) pathway, which plays a crucial role in cancer immune surveillance, is the target of several approved immunotherapeutic agents and is used as a predictive biomarker in some solid tumors. However, its use as a prognostic marker (i.e., regardless of therapy used) is not established clearly with available data demonstrating inconsistent prognostic impact of PD-L1 expression in solid tumors. We conducted a systematic literature search of electronic databases and identified publications exploring the effect of PD-L1 expression on overall survival and/or disease-free survival. Hazard ratios were pooled in a meta-analysis using generic inverse-variance and random-effects modeling. We used the Deeks method to explore subgroup differences based on disease site, stage of disease, and method of PD-L1 quantification. One hundred and eighty-six studies met the inclusion criteria. Programmed cell death ligand-1 expression was associated with worse overall survival (hazard ratio 1.33, 95% confidence interval 1.26-1.39; p < 0.001). There was significant heterogeneity between disease sites (subgroup p = 0.002) with pancreatic, hepatocellular, and genitourinary cancers associated with the highest magnitude of adverse outcomes. Programmed cell death ligand-1 was also associated with worse overall disease-free survival (hazard ratio 1.19, 95% confidence interval 1.09-1.30; p < 0.001). Stage of disease did not significantly affect the results (subgroup p = 0.52), nor did the method of quantification via immunohistochemistry or messenger RNA (subgroup p = 0.70). High expression of PD-L1 is associated with worse survival in solid tumors albeit with significant heterogeneity among tumor types. The effect is consistent in early-stage and metastatic disease and is not sensitive to method of PD-L1 quantification. These data can provide additional information for the counseling of patients with cancer about prognosis.