Prognosis prediction model for patients with breast cancer with bone metastasis: based on a population database

Background: Prognosis prediction for breast cancer bone metastasis ( BCBM) patients is related to the development of further treatment options, and the judgment of prognosis is often not determined by one factor, which requires a comprehensive assessment of the patient's condition. Methods: Through the search of the National Cancer Institute database, BCBM patients registered between January 1, 2010 and December 31, 2015 were selected as research goals. All patients were randomly assigned to the model establishment group and validation group at a ratio of 7:3. Log- rank test and multivariate cox regression analysis are used to evaluate each prognostic factor. Selecting the prognostic factor of log-rank test P<0.001 to plot Kaplan-Meier survival curves and use the model establishment group to draw nomgrams. Concordance index ( C- index), Receiver Operating Characteristic (ROC) curve and calibration plot are used for internal and external verification. Results: A total of 13,773 BCBM patients were included in this article, 9,644 BCBM patients were assigned to the model establishment group and 4,129 BCBM patients were assigned to the validation group. Two nomgrams for predicting OS and BCRS are plotted, with C-index of 0.716 and 0.735, respectively. The ROC curve and the calibration plot drawn using the model establishment group and validation group confirm the prediction accuracy of the two nomgrams. Conclusions: The final nomograms obtained satisfactory results after a series of internal and external verifications, verifying the accuracy of their predictions. Other samples are needed in the future for more comprehensive external validation of the model, but at this stage, this model will help physicians and patients to have a more accurate judgment of the prognosis.