Dynamic Predictive Models With Visualized Machine Learning for Assessing Chondrosarcoma Overall Survival - Li, Wenle; Wang, Gui; Wu, Rilige; Dong, Shengtao; Wang, Haosheng; Xu, Chan; Wang, Bing; Li, Wanying; Hu, Zhaohui; Chen, Qi; Yin, Chengliang (Frontiers in Oncology, 2022)
Chondrosarcoma is a malignant bone tumor with low incidence rate. Accurate risk evaluation is crucial for chondrosarcoma treatment. Due to the limited reliability of the existing predictive models, we intended to develop a credible predictor for clinical chondrosarcoma based on SEER data and four Chinese medical institutes. Three algorithms (BSR, UCOX and LASSO) were used for training. A normogram 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 AUC ≥ 0.8 in ROC curves of both internal and external validation. Specially, the predictor had very good clinical utility in terms of net benefit to patients at the 3 and 5 year points in both North America and China. A convenient web calculator based on the prediction model is available at https://drwenle029.shinyapps.io/CHSSapp, which is free and open to all clinicians.