Assessing Surgical Benefits and Creating a Prognostic Model for Breast Cancer with Lung-only Metastasis: An Analysis of the National Cancer Database
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Abstract
AIM: The decision to perform surgery on breast cancer patients with lung-only metastasis is a subject of ongoing debate. Our investigation seeks to assess the survival rates following surgical intervention among individuals diagnosed with breast cancer experiencing isolated metastasis to the lungs. Additionally, we endeavor to devise a predictive nomogram aimed at forecasting the long-term survival.
METHODS: We analyzed patients diagnosed with primary lung metastases from breast cancer between 2010 and 2015, utilizing datasets obtained from the National Cancer Database (NCDB). We employed the Cox proportional hazards regression model and the Kaplan-Meier method to analyze survival data. Additionally, we constructed nomograms to forecast survival outcomes.
RESULTS: The study comprised 2403 patients, with 1058 (44.0%) undergoing breast-specific surgery and 1345 (56.0%) not receiving surgical treatment. The group that underwent surgical procedures exhibited a significantly enhanced overall survival (OS) compared to the non-surgery group (multivariate analysis: hazard ratio [HR] = 0.64; 95% confidence interval [CI], 0.54–0.75; p < 0.001). Surgical intervention consistently improved survival across nearly all patient subgroups. The research successfully established a predictive nomogram designed to calculate the likelihood of long-term survival, attaining a concordance index (C-index) of approximately 0.7 in both validation and training cohorts. By integrating multiple clinicopathological variables, the nomogram efficiently classified patients into categories reflecting different survival forecasts.
CONCLUSIONS: The findings of this investigation support the notion that surgical treatment can enhance the overall survival of patients with initial lung-only metastasis from breast cancer. The investigation further introduces a nomogram demonstrating reasonable accuracy in forecasting long-term survival of patients in this cohort.
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