ArticleAnnals of translational medicine2021
A nomogram for predicting brain metastasis in patients with de novo stage IV breast cancer.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- External validation of a nomogram for de novo bone metastasis in breast cancer: a single-center Mexican cohort.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Individualized prediction of brain metastasis risk in patients with breast cancer.Journal of neuro-oncology · 2026Article
- Development and validation of a prognostic model for stage IV breast cancer based on primary tumor resection with machine learning methods: retrospective cohort study.Frontiers in endocrinology · 2026Article
- Estimating the risk of brain metastasis for patients newly diagnosed with cancer.Communications medicine · 2024Article
- Development and external validation of a prediction model for brain metastases in patients with metastatic breast cancer.Journal of cancer research and clinical oncology · 2023Article
- Novel models by machine learning to predict prognosis of breast cancer brain metastases.Journal of translational medicine · 2023Article
- HER2-low breast cancer could be associated with an increased risk of brain metastasis.International journal of clinical oncology · 2022Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBrain metastasis (BM) is a very serious event in patients with breast cancer. The aim of this study was to establish a nomogram to predict the risk of BM in patients with
methodsWe gathered female patients diagnosed with de novo stage IV breast cancer between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. After randomly allocating the patients to the training set and verification set, we used univariate and multivariate logistic regression to analyze the relationship between BM and clinicopathological features. Finally, we developed a nomogram which was validated by the analysis of calibration curve and receiver operating characteristic curve.
resultsOf 7,154 patients with
conclusionsOur study developed a nomogram to predict BM for de novo stage IV breast cancer, thus helping clinicians to identify patients at high-risk of BM and implement early preventive interventions to improve their prognoses.
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