ReviewCancer innovation2024
Prognostic nomograms for young breast cancer: A retrospective study based on the SEER and METABRIC databases.
Review in Cancer innovation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Global patterns and risk factors of breast cancer in women under 35: a population-based study.Breast (Edinburgh, Scotland) · 2026Article
- Personalized survival prediction in young Asian American breast cancer.Gland surgery · 2026Article
- Gene driven analytical learning model for accurate breast cancer diagnosis.Scientific reports · 2026Article
- Development and validation of a nomogram prediction model for thyroid dysfunction in patients with type 2 diabetes mellitus.Scientific reports · 2026Article
- Clinicopathological characteristics and prognostic analysis of multifocal/multicentric breast cancer.Scientific reports · 2025Article
- A nomogram for predicting overall survival in young triple-negative breast cancer patients: a population-based study.Discover oncology · 2025Article
- Nomogram establishment for gastrointestinal bleeding prediction in ICU patients with traumatic brain injury based on the MIMIC-IV database.Frontiers in medicine · 2025Article
- Prognostic nomograms for young breast cancer: A retrospective study based on the SEER and METABRIC databases.Cancer innovation · 2024Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Young breast cancer (YBC) is a subset of breast cancer that is often more aggressive, but less is known about its prognosis. In this study, we aimed to generate nomograms to predict the overall survival (OS) and breast cancer-specific survival (BCSS) of YBC patients. Methods: Data of women diagnosed with YBC between 2010 and 2020 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly allocated into a training cohort ( Results: We constructed nomograms incorporating 10 prognostic factors for OS and BCSS. These nomograms demonstrated strong predictive accuracy for OS and BCSS in the training cohort, with C-indexes of 0.806 and 0.813, respectively. The calibration curves verified that the nomograms have good prediction accuracy. Decision curve analysis demonstrated their practical clinical value for predicting YBC patient survival rates. Additionally, we provided dynamic nomograms to improve the operability of the results. The risk stratification ability assessment also showed that the OS and BCSS rates of the low-risk group were significantly better than those of the high-risk group. Conclusions: Here, we generated and validated more comprehensive and accurate OS and BCSS nomograms than models previously developed for YBC. These nomograms can help clinicians evaluate patient prognosis and make clinical decisions.
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