在常规实践中,接受抗 PD-(L)1 单药治疗的晚期非小细胞肺癌患者中,非常高的 PD-L1 表达可作为总生存期的预后指标。

Very high PD-L1 expression as a prognostic indicator of overall survival among patients with advanced non-small cell lung cancer receiving anti-PD-(L)1 monotherapies in routine practice.

机构信息

Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Division of Hematology and Oncology, Department of Medicine, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA.

出版信息

Pharmacoepidemiol Drug Saf. 2022 Oct;31(10):1121-1126. doi: 10.1002/pds.5487. Epub 2022 Jun 22.

Abstract

PURPOSE

Programmed death or ligand-1 (PD-(L)1) pathway inhibitors confer improved survival as the first-line treatment for advanced non-small cell lung cancer (aNSCLC) in patients with PD-L1 expression (PD-L1 + e ≥ 50%) compared to platinum-doublet chemotherapy and have become a standard therapy. Some recent evidence suggests that among aNSCLC patients with PD-L1 + e of ≥50% receiving pembrolizumab monotherapy, very high levels of PD-L1 + e (≥90%) may be associated with better outcomes. We sought to assess whether very high PD-L1 + e (≥90%) compared to high PD-L1 + e (50%-89%) is associated with an overall survival benefit in aNSCLC patients receiving anti-PD-(L)1 monotherapies.

METHODS

We conducted a single-site retrospective cohort study of aNSCLC patients who initiated PD-(L)1 inhibitor monotherapy as the first-line treatment from October 24, 2016, to August 25, 2021, and had a PD-L1 + e ≥ 50%. The primary outcome was overall survival, measured from the start of the first-line PD-(L)1 inhibitor monotherapy (index date) to date of death or last confirmed activity prior to the cohort exit date. Propensity score-based inverse probability weighting (IPW) was used to control for confounding in Kaplan-Meier curves and Cox proportional hazard regression analysis.

RESULTS

One hundred sixty-six patients with aNSCLC receiving PD-(L)1 inhibitor monotherapy met inclusion criteria. 54% were female, 90% received pembrolizumab, median age was 68 years, 70% had non-squamous cell carcinoma, 94% had a history of smoking, 29% had a KRAS mutation, and 37% had very high PD-L1 + e. Unweighted covariates at cohort entry were similar between groups (absolute standardized mean differences [SMDs] <0.1) except for race (SMD = 0.2); age at therapy initiation (SMD = 0.13); smoking status (SMD = 0.13), and BRAF mutation status (SMD = 0.11). After weighting, baseline covariates were well balanced (all absolute SMDs <0.1). In the weighted analysis, having a very high PD-L1 + e was associated with lower mortality (weighted hazard ratio 0.57, 95% CI 0.36-0.90) and longer median survival: 3.85 versus 1.49 years.

CONCLUSIONS

Very high PD-L1 + e (≥90%) was associated with an overall survival benefit over high PD-L1 + e (50%-89%) in patients receiving the first-line PD-(L)1 inhibitor monotherapy in a model controlling for potential confounders. These findings should be confirmed in a larger real-world data set.

摘要

目的

程序性死亡受体-1(PD-1)/配体 1(PD-L1)通路抑制剂作为 PD-L1 表达(PD-L1+e≥50%)的晚期非小细胞肺癌(aNSCLC)患者的一线治疗药物,与铂类双联化疗相比,可改善患者的生存,现已成为标准疗法。最近的一些证据表明,在接受 pembrolizumab 单药治疗的 PD-L1+e≥50%的 aNSCLC 患者中,非常高的 PD-L1+e(≥90%)可能与更好的结局相关。我们试图评估在接受抗 PD-(L)1 单药治疗的 aNSCLC 患者中,非常高的 PD-L1+e(≥90%)与高 PD-L1+e(50%-89%)相比,是否与总生存获益相关。

方法

我们进行了一项单中心回顾性队列研究,纳入了自 2016 年 10 月 24 日至 2021 年 8 月 25 日期间开始接受 PD-(L)1 抑制剂单药作为一线治疗的 PD-L1+e≥50%的 aNSCLC 患者。主要结局是总生存,从一线 PD-(L)1 抑制剂单药治疗开始(索引日期)到死亡或队列退出日期前最后一次确认的疾病进展或死亡日期。使用倾向评分逆概率加权(IPW)法在 Kaplan-Meier 曲线和 Cox 比例风险回归分析中控制混杂因素。

结果

166 例接受 PD-(L)1 抑制剂单药治疗的 aNSCLC 患者符合纳入标准。其中 54%为女性,90%接受 pembrolizumab 治疗,中位年龄为 68 岁,70%为非鳞状细胞癌,94%有吸烟史,29%有 KRAS 突变,37%有非常高的 PD-L1+e。队列入组时未经加权的协变量在组间相似(绝对标准化均数差[SMD]<0.1),除种族(SMD=0.2)、治疗起始时的年龄(SMD=0.13)、吸烟状态(SMD=0.13)和 BRAF 突变状态(SMD=0.11)外。加权后,基线协变量得到很好的平衡(所有绝对 SMD<0.1)。在加权分析中,非常高的 PD-L1+e 与较低的死亡率(加权风险比 0.57,95%CI 0.36-0.90)和更长的中位生存时间相关:3.85 年与 1.49 年。

结论

在控制潜在混杂因素的模型中,与高 PD-L1+e(50%-89%)相比,非常高的 PD-L1+e(≥90%)与接受一线 PD-(L)1 抑制剂单药治疗的患者的总生存获益相关。这些发现应在更大的真实世界数据集得到证实。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索