ArticleFrontiers in oncology2023
Risk factors and a new nomogram for predicting brain metastasis from lung cancer: a retrospective study.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- The immune microenvironment of the central nervous system and neuromodulation: new perspectives in lung cancer brain metastases research.Frontiers in immunology · 2026Review
- Predictors of brain metastases in patients with oligometastatic solid tumours treated with stereotactic body radiation therapy.Journal of neuro-oncology · 2025Article
- Developing a predictive model and uncovering immune influences on prognosis for brain metastasis from lung carcinomas.Frontiers in oncology · 2025Article
- Development and validation of a machine-learning model for the risk of potentially inappropriate medications in elderly stroke patients.Frontiers in pharmacology · 2025Article
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
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Abstract
Objective: This study aims to establish and validate a new nomogram for predicting brain metastasis from lung cancer by integrating data. Methods: 266 patients diagnosed as lung cancer between 2016 and 2018 were collected from Guangdong Academy of Medical Sciences. The first 70% of patients were designated as the primary cohort and the remaining patients were identified as the internal validation cohort. Univariate and multivariable logistics regression were applied to analyze the risk factors. Independent risk factors were used to construct nomogram. C-index was used to evaluate the prediction effect of nomogram.100 patients diagnosed as lung cancer between 2018 and 2019 were collected for external validation cohorts. The evaluation of nomogram was carried out through the distinction and calibration in the internal validation cohort and external validation cohort. Results: 166 patients were diagnosed with brain metastasis among the 266 patients. The gender, pathological type (PAT), leukocyte count (LCC) and Fibrinogen stage (FibS) were independent risk factors of brain metastasis. A novel nomogram has been developed in this study showed an effective discriminative ability to predict the probability of lung cancer patients with brain metastasis, the C-index was 0.811. Conclusion: Our research provides a novel model that can be used for predicting brain metastasis of lung cancer patients, thus providing more credible evidence for clinical decision-making.
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