ArticleTranslational cancer research2021
The construction and validation of the model for predicting the incidence and prognosis of brain metastasis in lung cancer patients.
Article in Translational cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Incidence of brain metastasis according to patient race and primary cancer origin: a systematic review.Journal of neuro-oncology · 2024Pooled it
- Development and validation of nomograms to predict brain metastasis-free survival in lung and breast cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Developing a predictive model and uncovering immune influences on prognosis for brain metastasis from lung carcinomas.Frontiers in oncology · 2025Article
- Extracranial metastasis sites correlate to the incidence risk of brain metastasis in stage IV non-small cell lung cancer: a population-based study.Journal of cancer research and clinical oncology · 2023Article
- Prediction of distant organ metastasis and overall survival of lung cancer patients: a SEER population-based cohort study.Frontiers in oncology · 2023Article
- Brain parenchymal and leptomeningeal metastasis in non-small cell lung cancer.Scientific reports · 2022Article
- A novel nomogram predicting cancer-specific survival in small cell lung cancer patients with brain metastasis.Translational cancer research · 2022Article
- Improved Survival With Surgical Treatment of Primary Lung Lesions in Non-Small Cell Lung Cancer With Brain Metastases: A Propensity-Matched Analysis of Surveillance, Epidemiology, and End Results Database.Frontiers in oncology · 2022Article
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBrain metastasis (BM) causes high morbidity and mortality rates in lung cancer (LC) patients. The present study aims to develop models for predicting the development and prognosis of BM using a large LC cohort.
methodsA total of 266,522 LC cases diagnosed between 2010 and 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) Program cohort. Risk factors for developing BM and prognosis were calculated by univariable and multivariable logistic and Cox regression analysis, respectively, and nomograms were constructed based on risk factors. Nomogram performance was evaluated with receiver operating characteristics (ROC) curve, or C-index and calibration curve.
resultsThe prevalence of BM was 13.33%. Associated factors for developing BM include: advanced age; Asian or Pacific Islander race; uninsured status; primary tumor site; higher T stage; higher N stage; poorly differentiated grade; the presence of lung, liver, and bone metastases; and adenocarcinoma histology. Median overall survival (OS) was 4 months; associated prognosis factors were similar to risk factors plus female gender, unmarried status, and surgery. The calibration curve showed good agreement between predicted and actual probability, and the AUC/C-index was 73.1% (95% CI: 72.6-73.6%) and 0.88 (95% CI: 0.87-0.89) for risk and prognosis predictive models, respectively.
conclusionsBM was highly developed in LC patients, and homogeneous and heterogeneous factors were found between risk and prognosis for BM. The nomogram showed good performance in predicting BM development and prognosis.
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