Predictive value of tumor mutation burden (TMB) with targeted next-generation sequencing in immunocheckpoint inhibitors for non-small cell lung cancer (NSCLC)

Background: To evaluate the clinical predictive value of tumor mutation burden (TMB) for immune checkpoint inhibitor (ICI) therapy in patients with non-small cell lung cancer (NSCLC). Method: As of 15 February 2020, PubMed, PMC and EMBASE databases as well as the American society of clinical oncology (ASCO) and European society of medical oncology (ESMO) databases were searched. The Mantel-Haenszel or inverse variance weighted fixed-effects model (I(2) ≤ 50%) or random-effects model (I(2) > 50%) were used to evaluate OR and its 95% CI of objective response rate (ORR) and disease control rate (DCR) , as well as HR and its 95% CI of progression-free survival (PFS) and overall survival (OS). In addition, we did publication bias, heterogeneity analysis, sensitivity analysis and subgroup analysis. And quality of the studies included and the level of evidence for outcome measures were evaluated. Results: 14 studies involving 2872 patients were included. The ORR (OR 3.52, 95%CI 2.32-5.35, p < 0.00001), DCR (OR 3.26, 95%CI 1.91-5.55, p < 0.0001), PFS (HR 0.81, 95%CI 0.74-0.89, p < 0.00001) and OS (HR 0.83, 95%CI 0.74-0.94, p = 0.002) of ICI therapy in the high TMB group were all superior to those in the low TMB group. Conclusions: TMB is a promising biomarker, which can predict the efficacy of ICI therapy in advanced NSCLC patients, included ORR, DCR, PFS and OS.