ArticleBMC women's health2024
Development of prognostic models for HER2-positive metastatic breast cancer in females: a retrospective population-based study.
Article in BMC women's health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Prognostic model for pulmonary metastasis in patients with HER2-positive breast cancer: a population-based study.Breast cancer (Tokyo, Japan) · 2026Article
- Development and validation of explainable machine learning models for the prediction of survival in patients with M1 breast cancer.Gland surgery · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundThis study aimed to construct, evaluate, and validate nomograms for breast cancer-specific survival (BCSS) and overall survival (OS) prediction in patients with HER2- overexpressing (HER2+) metastatic breast cancer (MBC).
methodsThe Surveillance, Epidemiology, and End Results (SEER) database was used to select female patients diagnosed with HER2 + MBC between 2010 and 2015. These patients were distributed into training and validation groups (7:3 ratio). Variables were screened using univariate and multivariate Cox regression analyses, and BCSS and OS nomograms were constructed to determine one-, three-, and five-year survival probabilities. The nomograms were evaluated and validated using the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis. Stratification was evaluated using Kaplan-Meier curves and log-rank tests based on optimal total score cut-off values. We published web-based versions of these nomograms for clinical use.
resultsA total of 2,151 eligible patients were randomized into training (n = 1,505) and validation (n = 646) groups. Independent prognostic factors of BCSS and OS included: age; marital status; race; oestrogen receptor status; surgery; chemotherapy; and bone, brain, liver, and lung metastases. The C-indices for the BCSS and OS training groups were 0.707 and 0.702, respectively. The ROC, calibration, and decision curves demonstrated the strength of the nomograms. According to cut-off values, patients were categorized into low-, intermediate-, and high-risk groups, with significant differences in survival outcomes between them.
conclusionWe constructed predictive nomograms and stratified risk to assess the prognosis of patients with HER2 + MBC, which could help inform therapeutic decisions.
trial registrationNot applicable.
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