Identifying optimal first-line interventions for advanced non-small cell lung carcinoma according to PD-L1 expression: a systematic review and network meta-analysis. (1st January 2020) - Liu, Jie; Li, Chengming; Seery, Samuel; Yu, Jinming; Meng, Xue
ABSTRACT: This network meta-analysis (NMA), based on one phase II and nine phase III studies, involving 6, 124 patients with metastatic NSCLC, indirectly compares Atezolizumab + Bevacizumab + chemotherapy (ABC), Atezolizumab + chemotherapy (AC), Pembrolizumab + chemotherapy (PC), Pembrolizumab alone, Bevacizumab + chemotherapy (BC) and chemotherapy alone. Each of these is recommended as front-line interventions, according to the US FDA and the European Medicines Agency (EMA) for advanced NSCLC without EGFR mutation or ALK rearrangement. Studies were identified through PubMed, EMBASE, the Cochrane Library, Medline, and abstracts found in oncology articles. Primary endpoints, i.e., progression-free survival (PFS) and overall survival (OS) with corresponding hazard ratios (HR), objective response rates (ORR) and adverse event (AEs) with odds risk (OR) were pooled according to frequentist network meta-analytical techniques. PD-L1 expression thresholds, as well as non-squamous/squamous were used to determine subgroups. Immunotherapy plus chemotherapy appeared superior to Pembrolizumab alone for PD-L1-high (i.e., TPS≥50%) NSCLC patients. BC might also be specifically recommended as an initial first-line treatment for PD-L1-high, non-squamous NSCLC patients, since BC was not inferior to Pembrolizumab alone. PC and ABC might be preferred for NSCLC patients with intermediate PD-L1 (1% ≤PD-L1, TPS<50%) expression. BC can also be tentatively recommended specifically for PD-L1-intermediate, non-squamous NSCLC patients. Combined immunotherapies can all be recommended for PD-L1-negative (i.e., TPS<1%) NSCLC patients, although especially the ABC combination for non-squamous NSCLC patients, which was superior to PC in regards of PFS. However, PC performed comparable to ABC in the whole population and in all subgroup save this one. More predictive biomarkers could be factored into further analyses to help identifying the most effective treatment regimens for specific patient groups.