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ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Molecular Targets and Therapeutics
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1554242
This article is part of the Research Topic Renewed Insight into Cancer Mechanism and Therapy View all 15 articles
Developing a predictive model and uncovering immune influences on prognosis for brain metastasis from lung carcinomas
Provisionally accepted- 1 Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
- 2 Department of Emergency, General Hospital of Tibet Military Command, Lhasa, China
- 3 Physical Examination Center, Western Theater General Hospital, Chengdu, Sichuan Province, China
- 4 Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
Objective: Primary lung carcinomas (LCs) often metastasize to the brain, resulting in a grim prognosis for affected individuals. This population-based study aimed to investigate their survival period and immune status, while also establishing a predictive model.Methods: The records of 86,763 primary LCs from the Surveillance, Epidemiology, and End Results (SEER) database were extracted, including 15,180 cases with brain metastasis (BM) and 71,583 without BM. Univariate and multivariate Cox regression were employed to construct a prediction model.Multiple machine learning methods were applied to validate the model. Flow cytometry and ELISA were used to explore the immune status in a real-world cohort.Results: The research findings revealed a 17.49% prevalence of BM from LCs, with a median survival of 8 months, compared with 16 months for their counterparts (p <0.001). A nomogram was developed to predict survival at 1, 3, and 5 years on the basis of these variables, with the time-dependent area under the curve (AUC) of 0.857, 0.814, and 0.786, respectively. Moreover, several machine learning approaches have further verified the reliability of this model's performance. Flow cytometry and ELISA analysis suggested the prediction model was related the immune status.Conclusions: BM from LCs have an inferior prognosis. Considering the substantial impact of these factors, the nomogram model is a valuable tool for guiding clinical decision-making in managing patients with this condition.
Keywords: Lung carcinoma, brain metastasis, prognosis, Model, immunology
Received: 01 Jan 2025; Accepted: 14 Feb 2025.
Copyright: © 2025 Wang, Peng, Li, Gao and Chang. 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:
Tao Chang, Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
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