Efficacy and safety of immune checkpoint inhibitors in elderly patients with advanced non-small cell lung cancer: a systematic review and meta-analysis

Background Immune checkpoint inhibitors (ICIs) are the preferred treatments for advanced non-small cell lung cancer (NSCLC) without targetable oncogene alterations. However, evidence in the elderly population (aged >= 65 years) remains limited. Methods We searched PubMed, Embase, Cochrane Library, Web of Science, and Scopus databases for eligible publications until September 30, 2024. The primary outcome of interest was overall survival (OS). A random-effects model was used for the statistical analysis. Findings A total of 35 phase 3 randomized controlled trials (RCTs) involving 9788 patients and 64 real-world studies involving 37,111 patients were included. Results from phase 3 RCTs revealed that ICIs significantly improved OS (hazard ratio [HR] = 0.78, 95% confidence interval [CI]: 0.74-0.82) and progression-free survival (PFS) (HR = 0.67, 95% CI: 0.60-0.75) compared to chemotherapy. The association between ICIs and improved OS was independent of patient characteristics (race and histological type) or treatment-related factors (ICI drug type, treatment mode, and treatment line). However, significantly prolonged OS was not observed in subgroups of aged >= 75 years and PD-L1 < 1%. In real-world studies, the pooled median OS of ICIs were 11.8 months (95% CI: 11.2-12.4); Eastern Cooperative Oncology Group (EOCG) score, histological type, PD-L1 status, with immune-related adverse events (irAEs), and treatment mode were predictive for OS; rates of irAEs and discontinuation were numerically higher for combination therapy vs. monotherapy. Interpretation ICIs are associated with a significant improvement in OS and PFS compared to chemotherapy in elderly patients with advanced NSCLC. Nevertheless, some patient characteristics such as aged >= 75 years, ECOG score >= 2, and PD-L1 < 1% seem to have a negative impact on the efficacy of ICIs, while these findings require further validation in large RCTs. Copyright (c) 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).