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ORIGINAL RESEARCH article

Front. Immunol.

Sec. Cancer Immunity and Immunotherapy

Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1643591

This article is part of the Research TopicImmune Predictive and Prognostic Biomarkers in Immuno-Oncology: Refining the Immunological Landscape of CancerView all 44 articles

Development and Validation of a Novel Nomogram for Predicting Outcomes in Advanced Lung Cancer Patients Treated Beyond Progression with Immune Checkpoint Inhibitors

Provisionally accepted
Tianwei  LuoTianwei Luo1Haiyun  GengHaiyun Geng2Genwang  WangGenwang Wang3Ying  ZhaoYing Zhao4Ning  HanNing Han2Ting  OuyangTing Ouyang1Ao  ChenAo Chen5Xiufeng  LiuXiufeng Liu2*Chao  ChenChao Chen2*Mi  YangMi Yang1*
  • 1Department of Oncology, Nanjing Drum Tower Hospital, Nanjing Drum Tower Hospital Clinical College, Nanjing University of Chinese Medicine, Nanjing, China
  • 2Department of Oncology, Jinling Hospital, Medical School of Nanjing University, Nanjing, China
  • 3Department of Medical Administration, Jinling Hospital, Medical School of Nanjing University, Nanjing, China
  • 4Department of Radiology, Jinling Hospital, Nanjing medical university, Nanjing, China
  • 5Department of Oncology, Jinling Hospital, Nanjing medical university, Nanjing, China

The final, formatted version of the article will be published soon.

Background Standardized management of lung cancer (LC) progressing post-immunotherapy remains challenging, with debated clinical benefits of treatment beyond progression (TBP). We evaluated the efficacy of continued immune checkpoint inhibitors (ICIs) and developed a pharmacologically guided nomogram to optimize TBP decision-making. Methods This retrospective analysis of 153 LC patients undergoing post-progression ICIs continuation identified significant predictors via the least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis. A nomogram predicting overall survival (OS) and progression-free survival (PFS) was constructed and validated using time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Results Treatment regimen, Eastern Cooperative Oncology Group (ECOG) performance status, efficacy evaluation, lymph node metastasis, and liver metastasis independently predicted OS, while liver metastasis and efficacy evaluation influenced PFS. The nomogram demonstrated robust discrimination (OS C-index=0.700; PFS C-index=0.599) with area under the curve (AUC) values of 0.786/0.777/0.705 (OS) and 0.621/0.638/0.630 (PFS) at 6/12/24 months. DCA confirmed the clinical utility of the OS nomogram. Patients were stratified into high-and low-risk groups based on optimal cutoff values, and risk stratification revealed significant survival differences (p<0.01). Conclusion This validated nomogram provides a clinically actionable tool to identify patients benefiting from sustained ICIs exposure, enabling pharmacologically informed TBP strategies while minimizing futile drug exposure. Future prospective multicenter studies should validate utility across diverse pharmacogenomic populations.

Keywords: Lung cancer (LC), Immunotherapy, Immune checkpoint inhibitors (ICIs), treatment beyond progression (TBP), Nomogram prognostic model

Received: 09 Jun 2025; Accepted: 08 Oct 2025.

Copyright: © 2025 Luo, Geng, Wang, Zhao, Han, Ouyang, Chen, Liu, Chen and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Xiufeng Liu, njjloncologylxf@163.com
Chao Chen, njjloncologycc@163.com
Mi Yang, fingyoung@126.com

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