ArticleOncology letters2025
Construction of a nomogram to guide prophylactic cranial irradiation in extensive‑stage small cell lung cancer.
Article in Oncology letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- BraMARS: An Interpretable Histopathology-Driven Deep Learning Model for Brain Metastasis Risk Stratification in Surgically Resected Limited-Stage SCLC.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Development and validation of a prognosis model for patients with brain-metastasis non-small cell lung cancer by machine-learning.Translational cancer research · 2025Article
- Interpretable Machine Learning for Survival Prediction in Small Cell Lung Cancer Patients With Brain Metastases: A Population-Based Study With External Validation.Cancer control : journal of the Moffitt Cancer CenterArticle
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patients with extensive-stage small cell lung cancer (ES-SCLC) have a high risk of brain metastasis (BM). However, to the best of our knowledge, the risk factors for BM remain unclear. The present study aimed to investigate the risk factors and establish a prediction model for BM in patients with ES-SCLC. A total of 156 patients with ES-SCLC who had no BM and achieved a partial or complete response between January 2020 and March 2023 were included. Patients were randomly divided into training (n=109) and validation (n=47) cohorts. Factors associated with BM were assessed in the training cohort. Univariate and Cox multivariate analyses were performed to evaluate patients with ES-SCLC. Cox multivariate analysis identified oligometastasis [hazard ratio (HR), 0.35; 95% CI, 0.14-0.85; P=0.021], sex (HR, 2.48; 95% CI, 1.05-5.85; P=0.038) and baseline adrenal metastasis (HR, 2.85; 95% CI, 1.54-5.21; P<0.001) as independent risk factors for BM. A nomogram model was constructed to predict intracranial progression-free survival (iPFS). The areas under the receiver operating characteristic curves for the 9-, 12- and 18-month iPFS in the training cohort were 0.77, 0.74 and 0.75, respectively. The nomogram prediction and actual validation cohorts demonstrated good agreement. Among the high-risk factors for BM, the overall survival analysis demonstrated that non-oligometastasis and baseline adrenal metastasis were unfavorable prognostic factors. The present nomogram may aid risk assessment for BM in patients with ES-SCLC and guide prophylactic cranial irradiation.
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