Work

Prognostic nomograms for hormone receptor-positive breast cancer with lung metastasis: a SEER-based study with external validation

Year: 2026

Type: preprint

Abstract: Background Validated prognostic tools for breast cancer with lung metastasis (BCLM) are lacking, and most existing models have not been temporally validated for contemporary patients. Using large-scale data from the Surveillance, Epidemiology, and End Results (SEER) registry, this study developed a nomogram to predict survival in hormone receptor-positive (HR+) BCLM patients and validated it across multiple cohorts, including a temporal validation cohort of recently diagnosed patients. Methods Among 8,850 HR+ BCLM records initially identified from the SEER database (2010–2021), 4,425 patients met the final eligibility criteria. Patients diagnosed from 2010 to 2017 (n = 2,706) were randomly divided into a training cohort (n = 1,894) and an internal validation cohort (n = 812) at a 7:3 ratio; patients diagnosed from 2018 to 2021 (n = 1,719) were assigned to a temporal validation cohort to assess model performance in contemporary practice. An external validation cohort (n = 374) was obtained from Guangxi Medical University Cancer Hospital to independently validate the models' generalizability. Independent predictors of overall survival (OS) and breast cancer-specific survival (BCSS) were identified using multivariate Cox regression analysis. Based on these predictors, two 3‑year prognostic nomograms were constructed for OS and BCSS, and their predictive performance was evaluated at 1‑, 2‑, and 3‑year time points. The models were evaluated using receiver operating characteristic (ROC) curves, calibration plots, Harrell's concordance index (C-index), and decision curve analysis (DCA). Results Eleven clinicopathological variables were incorporated into the final multivariable models, with individual category‑specific associations varying between OS and BCSS. In the training cohort, the C‑index was 0.655 (95% CI: 0.637–0.673) for OS and 0.662 (95% CI: 0.644–0.680) for BCSS. In the internal validation cohort, the corresponding values were 0.648 (95% CI: 0.621–0.675) and 0.657 (95% CI: 0.630–0.684). The temporal validation cohort (2018–2021) showed numerically higher C‑index values than the other cohorts: 0.681 (95% CI: 0.663–0.699) for OS and 0.686 (95% CI: 0.667–0.704) for BCSS, suggesting that the models maintains acceptable discriminative performance in contemporary patients. The external validation cohort produced C‑index values of 0.657 (95% CI: 0.613–0.686) for OS and 0.652 (95% CI: 0.611–0.683) for BCSS. ROC curves, calibration plots, and DCA further supported the predictive performance and potential clinical utility of the nomograms across all cohorts. Conclusion The validated nomograms demonstrated acceptable predictive performance for HR+ BCLM patients across temporal and external validation cohorts, supporting individualized prognostic assessment for patients with HR-positive breast cancer and lung metastasis.

Source: Research Square

DOI: 10.21203/rs.3.rs-10377468/v1