The association of efficacy with PD-1/PD-L1 inhibition and tumor mutational burden in advanced nonsmall cell lung cancer: A PRISMA-guided literature review and meta-analysis

PD-1/PD-L1抑制剂与晚期非小细胞肺癌肿瘤突变负荷的疗效相关性:PRISMA指导下的文献综述和荟萃分析

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Abstract

BACKGROUND: Tumor mutation burden (TMB) has been reported to emerge as an independent biomarker of response to identify patients who would achieve benefit from immune checkpoint inhibitors. However, it still remains controversy that whether TMB can be a robust biomarker of response to programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibition. We performed this meta-analysis to assess the relationship between TMB and the efficacy with PD-1/PD-L1 inhibition in advanced nonsmall cell lung cancer (NSCLC). METHODS: Following the recommendations of the PRISMA statement, electronic databases literature search was done on the published articles till March 2021, including Pubmed, Embase, and Cochrane library databases. Studies were selected that focused on comparing the efficacy of TMB-high group and TMB-low group in NSCLC patients received with immune checkpoint inhibitors. Meta-analysis Revman 5.3 software was utilized to calculate the pooled outcomes. RESULTS: A systematic literature search was conducted 8 articles, including 11 comparative articles. Findings of our studies shown that patients with TMB-high group was associated with better clinical outcomes than TMB-low group, including progression-free survival (odds ratio [OR], 0.38; 95% confidence interval [CI], 0.29-0.49; P < .00001), complete response (OR, 4.71; 95% CI, 2.32-9.57; P < .0001), durable clinical benefit (OR, 3.76; 95% CI, 2.38-5.96; P < .00001) and the objective response rate (OR, 3.14; 95% CI, 1.83-5.37; P < .0001). While, it failed to predict overall survival benefits (OR, 0.74; 95% CI, 0.45-1.20; P = .22). CONCLUSIONS: Our study found that NSCLC with high TMB who benefit from immunotherapy. The findings suggest that TMB could associated with a greater predictive power of response. Possibly a more TMB-oriented prediction model might gain more benefits from PD-1/PD-L1 inhibitors.

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