Real-world single-center data analysis of dual immunotherapy in advanced NSCLC: Efficacy, survival, and adverse events

We collected 96 patients who received dual immunotherapy between January 2019 and June 2024, in a 1:1:1 ratio based on PD-L1 expression levels of negative (<1%), medium (1% ≤ PD-L1 ≤ 49%), and high (PD-L1 ≥ 50%). This study evaluates the efficacy and safety of dual immunotherapy in patients with advanced NSCLC, stratified by PD-L1 expression levels. Among the 96 patients, the objective response rate (ORR) was 37.5%, disease control rate (DCR) was 67.8%. In the multivariate analysis of PFS, PD-L1 ≥ 50% (HR = 0.40, 95% CI: 0.22-0.74) was identified as a protective factor for PFS, while PS Score ≥ 2 (HR = 2.74, 95% CI: 1.11-6.77) and stage IV tumors (HR = 2.05, 95% CI: 1.02-4.12) were risk factors. In the multivariate analysis of OS, PD-L1 between 1% and 49% (HR = 0.51, 95% CI: 0.28-0.90) and PD-L1 ≥ 50% (HR = 0.31, 95% CI: 0.17-0.57) were protective factors, with no risk factors detected. The incidence of adverse events was 77.1%, with a 34.3% incidence of grade 3-4 immune-related adverse events. And PD-L1 ≥ 50% group adverse events incidence more common, with an overall incidence of 87.5% and a grade 3-4 incidence of 40.6%. Patients with high PD-L1 expression (≥50%) demonstrated improved progression-free survival (PFS, HR = 0.40) and overall survival (OS, HR = 0.31) but experienced a higher incidence of severe adverse events (40.6%).

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Publication Details

Journal
Human Vaccines & Immunotherapeutics
Published
2025-08-04
DOI
https://doi.org/10.1080/21645515.2025.2542068
Citations
1
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
1.05

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article

Real-world single-center data analysis of dual immunotherapy in advanced NSCLC: Efficacy, survival, and adverse events

Ping Sun, Qingqing Yang, Chengzhi Zhou, Yang Luan et al.
1 citations
Human Vaccines & Immunotherapeutics
Cancer Immunotherapy and Biomarkers
1.05
article

Real-world single-center data analysis of dual immunotherapy in advanced NSCLC: Efficacy, survival, and adverse events

Ping Sun, Qingqing Yang, Chengzhi Zhou, Yang Luan, Changchun Wang, Baodan Yu, Xiaohong Xie, Gang Yang, Jianqing Hao, Xinqing Lin, Tao Luan, Shuaiying Wang, Nanshan Zhong, Yunhui Zhang, Hai Lu
article en
1 citations

Abstract

We collected 96 patients who received dual immunotherapy between January 2019 and June 2024, in a 1:1:1 ratio based on PD-L1 expression levels of negative (<1%), medium (1% ≤ PD-L1 ≤ 49%), and high (PD-L1 ≥ 50%). This study evaluates the efficacy and safety of dual immunotherapy in patients with advanced NSCLC, stratified by PD-L1 expression levels. Among the 96 patients, the objective response rate (ORR) was 37.5%, disease control rate (DCR) was 67.8%. In the multivariate analysis of PFS, PD-L1 ≥ 50% (HR = 0.40, 95% CI: 0.22-0.74) was identified as a protective factor for PFS, while PS Score ≥ 2 (HR = 2.74, 95% CI: 1.11-6.77) and stage IV tumors (HR = 2.05, 95% CI: 1.02-4.12) were risk factors. In the multivariate analysis of OS, PD-L1 between 1% and 49% (HR = 0.51, 95% CI: 0.28-0.90) and PD-L1 ≥ 50% (HR = 0.31, 95% CI: 0.17-0.57) were protective factors, with no risk factors detected. The incidence of adverse events was 77.1%, with a 34.3% incidence of grade 3-4 immune-related adverse events. And PD-L1 ≥ 50% group adverse events incidence more common, with an overall incidence of 87.5% and a grade 3-4 incidence of 40.6%. Patients with high PD-L1 expression (≥50%) demonstrated improved progression-free survival (PFS, HR = 0.40) and overall survival (OS, HR = 0.31) but experienced a higher incidence of severe adverse events (40.6%).

Human Vaccines & ImmunotherapeuticsVol. 21(1)
Kunming University of Science and Technology (CN), First Affiliated Hospital of Guangzhou Medical University (CN), Zhejiang Cancer Hospital (CN), Guangzhou Medical University (CN)
Beijing Xisike Clinical Oncology Research Foundation, National Key Research and Development Program of China
Openalex Percentile: Top 19%
Cancer Immunotherapy and Biomarkers
1.05
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