ArticleCancer pathogenesis and therapy2025
Nomogram for predicting the risk and prognosis of lung metastasis of four subtypes of breast cancer: A population-based study from SEER.
Article in Cancer pathogenesis and therapy, 2025. 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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4 citing papers in PubMed.
- Machine learning-based prediction of survival in breast cancer patients with lung metastasis: a SEER-based study.Translational cancer research · 2026Article
- Advancements in Cancer Survival Prediction: A Systematic Review of Classical and Modern Approaches.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine · 2025Review
- Re: Nomogram for predicting the risk and prognosis of lung metastasis of four subtypes of breast cancer: A population-based study from SEER.Cancer pathogenesis and therapy · 2025Article
- Targeting Tn Antigen Suppresses Aberrant O-Glycosylation-Elicited Metastasis in Breast Cancer.Journal of cellular and molecular medicine · 2024Article
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Abstract
Background: Breast cancer (BC) is the most diagnosed cancer worldwide, and patients' survival decreases with metastasis. We conducted a retrospective study using data derived from the Surveillance, Epidemiology, and End Results (SEER) database and clinicopathological data to construct a clinical predictive model to predict the risk and prognosis of lung metastasis (LM) in patients with different subtypes of BC and validate its performance. Methods: A total of 1650 patients from the SEER database between 2011 and 2015 were enrolled in this study. Cox regression analysis was performed to identify prognostic factors for breast cancer lung metastasis (BCLM). A nomogram was constructed using the independent prognostic factors. The concordance index (C-index), area under the curve (AUC) value, calibration curve, and decision curve analysis (DCA) were used to test the prediction accuracy of the nomogram. External validation ( Results: Multivariate Cox regression analyses suggested that age, grade, surgery, chemotherapy, subtype, and liver, bone, and brain metastases were independent prognostic factors for overall survival (OS). Kaplan-Meier survival analysis showed that the median survival times of patients with human epidermal growth factor receptor 2 (HER2)-positive, luminal A, luminal B, and triple-negative BC were 25 (95% confidence interval [CI], 20-37), 27 (95% CI, 23-29), 35 (95% CI, 30-44), and 12 (95% CI, 11-14), respectively. The C-indexes of the nomogram for predicting OS of the SEER training, SEER validation, and clinical validation cohorts were 0.7, 0.6, and 0.6, respectively, and the calculated AUCs at 3 years were 0.765, 0.794, and 0.799, respectively. The calibration curve indicates that the nomogram possessed a high level of accuracy. Conclusions: Our nomogram demonstrates significant predictive value, indicating that molecular subtypes, brain metastasis, and liver metastasis are closely associated with the prognosis of patients with LM. This information can guide clinical practice.
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