Dynamic Predictive Models With Visualized Machine Learning for Assessing Chondrosarcoma Overall Survival.

ABSTRACT: Chondrosarcoma is a malignant bone tumor with a low incidence rate. Accurate risk evaluation is crucial for chondrosarcoma treatment. Due to the limited reliability of existing predictive models, we intended to develop a credible predictor for clinical chondrosarcoma based on the Surveillance, Epidemiology, and End Results data and four Chinese medical institutes. Three algorithms (Best Subset Regression, Univariate and Cox regression, and Least Absolute Shrinkage and Selector Operator) were used for the joint training. A nomogram predictor including eight variables-age, sex, grade, T, N, M, surgery, and chemotherapy-is constructed. The predictor provides good performance in discrimination and calibration, with area under the curve ≥0.8 in the receiver operating characteristic curves of bo

SUBMITTER: Li W 

PROVIDER: S-EPMC9351692 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature