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Prognostic Role of Soluble Programmed Death Ligand 1 in Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis

Guixiang Liao, Zhihong Zhao, Yuting Qian, Xiean Ling, Shanyi Chen, Xianming Li, Feng‐Ming Kong

2021Frontiers in Oncology25 citationsDOIOpen Access PDF

Abstract

Objective The objective of this study was to explore whether soluble programmed death ligand 1 (sPD-L1) is a potential prognostic biomarker in patients with non-small cell lung cancer (NSCLC). Methods A comprehensive search of electronic databases was carried out. Original studies with inclusion of sPD-L1, progression-free survival, and overall survival in NSCLC were eligible. The primary endpoints were overall survival and progression-free survival. Hazard ratios (HRs) and 95% confidence intervals (CIs) were applied for data analysis. Results Eight studies involving 710 patients with NSCLC were included in the analysis. A pooled data analysis revealed that high levels of sPD-L1 were correlated with poorer overall survival (HR = 2.34; 95% CI = 1.82–3.00; P < 0.001) and progression-free survival (HR = 2.35; 95% CI = 1.62–3.40, P < 0.001). A subgroup analysis revealed that high levels of sPD-L1 were correlated with poor overall survival in patients treated with immunotherapy (HR = 2.40; 95% CI = 1.79–3.22; P < 0.001). Conclusion This pooled analysis of published data suggests that sPD-L1 may serve as a readily available biomarker for survival in NSCLC patients treated with ICI based treatment. Prospective studies with well-designed standard assessment methods should be conducted to validate the prognostic role of sPD-L1 in NSCLC. Systematic Review Registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021283177 .

Topics & Concepts

MedicineHazard ratioMeta-analysisLung cancerInternal medicineOncologyBiomarkerSubgroup analysisConfidence intervalSurvival analysisImmunotherapynon-small cell lung cancer (NSCLC)Proportional hazards modelCancerBiologyBiochemistryA549 cellLung Cancer Research StudiesLung Cancer Treatments and MutationsCancer Immunotherapy and Biomarkers