Abstract 1347P
Background
This study investigated the efficacy and safety of cross-line immunotherapy in patients with advanced primary lung cancer and constructed and validated a prognostic nomogram model.
Methods
A retrospective analysis was performed on patients with advanced lung cancer who underwent immunotherapy rechallenge from June 2018 to June 2023 at nine cancer centers in mainland China. Survival analysis was performed using the Kaplan–Meier method. Univariate and multivariate regression analysis of prognostic effects were performed using Cox proportional hazard models. A nomogram model was constructed to predict the overall survival (OS) of patients receiving immunotherapy rechallenge.
Results
A total of 263 eligible lung cancer patients were enrolled. The median follow-up time was 29·2 months, median progression-free survival (PFS)R 3·7 months (95% CI: 3.0-4.4), median overall survival (OS)R 21·1 months (95% CI 18.5-23.7), objective response rate (ORR) 14·1%, and disease control rate (DCR) 68·5%. Patients with PFS ≥6 months at initial immunotherapy showed greater benefits for rechallenge PFS than patients with PFS <6 months(4·7 vs. 3·4, HR=0·738, 95% CI: 0·574–0·948, P=0·017), whereas patients with the best response to initial immunotherapy of complete response (CR)/partial response (PR) showed greater benefits for OS than patients who was stable disease (SD)/ progressive disease (PD) (25·1 vs. 19·1 months, HR=0·663, 95% CI: 0·480–0·916, P=0·013). An initial clinical stage of IIIB/C, number of metastases <2, line number of initial immunotherapy ≤2, best response to initial immunotherapy of CR/PR, and discontinuation due to immunotoxicity may be factors contributing to the benefits of restarting immunotherapy. The nomogram model we estiblished can predict patient survival with high accuracy.
Conclusions
ICI rechallenge therapy is a safe and feasible regimen after recurrence, especially in patients with relatively low tumor burden, long PFS at initial immunotherapy, and good tumor regression. We also constructed and validated a nomogram model for survival prediction and guidance of treatment decision making.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The author.
Funding
This research was supported by Guangdong Association of Clinical Trials (GACT)/Chinese Thoracic Oncology Group (CTONG) and Guangdong Provincial Key Lab of Translational Medicine in Lung Cancer (Grant No. YC20210105) and 2022CSCO key program (Y-2021AST/zd-0119).
Disclosure
The author has declared no conflicts of interest.
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Abstract