医学
内科学
肺癌
荟萃分析
危险系数
优势比
入射(几何)
肿瘤科
临床终点
人口
观察研究
置信区间
随机对照试验
非小细胞肺癌
不利影响
物理
光学
环境卫生
A549电池
作者
Bartłomiej Tomasik,Michał Bieńkowski,Marcin Braun,Sanjay Popat,Rafał Dziadziuszko
出处
期刊:Lung Cancer
[Elsevier]
日期:2021-08-01
卷期号:158: 97-106
被引量:33
标识
DOI:10.1016/j.lungcan.2021.06.004
摘要
BackgroundImmune checkpoint inhibitors (ICIs) are standard of care in advanced non-small cell lung cancer (NSCLC), however their status in patients with poor performance status (PS) is poorly defined. We aimed to evaluate the efficacy and safety of ICIs in NSCLC patients with PS ≥ 2.MethodsWe conducted a systematic review and meta-analysis of interventional and observational studies, which reported efficacy and safety data on ICIs in PS ≥ 2 comparing to PS ≤ 1 NSCLC patients. Efficacy endpoints included: Objective Response Rate (ORR), Disease-Control Rate (DCR), Overall Survival (OS), Progression-Free Survival (PFS). Safety endpoint was the incidence of severe (grade≥3) Adverse Events (AE). Random-effects model was applied for meta-analysis. Heterogeneity was assessed using I2. The review is registered on PROSPERO (CRD42020162668).FindingsSixty-seven studies (n = 26,442 patients) were included. In PS ≥ 2 vs. PS ≤ 1 patients, the pooled odds ratios were: for ORR 0.46 (95 %CI: 0.39−0.54, I2:0 %); for DCR 0.39 (95 %CI: 0.33−0.48, I2:50 %) and for AEs 1.12 (95 %CI: 0.84–1.48, I2:39 %). The pooled hazard ratio for PFS was 2.17 (95 %CI: 1.96–2.39, I2:65 %) and for OS was 2.76 (95 %CI: 2.43–3.14, I2:76 %). The safety profile was comparable regardless of the PS status.InterpretationPatients with impaired PS status are, on average, twice less likely to achieve a response when exposed to ICIs when compared with representative PS ≤ 1 population. For lung cancer patients treated with ICIs, the impaired PS is not only prognostic, but also predictive for response, while the safety profile is not affected. Prospective randomized studies are indispensable to determine whether poor PS patients derive benefit from ICIs.
科研通智能强力驱动
Strongly Powered by AbleSci AI