Prediction of overall survival in patients with Stage I esophageal cancer: A novel web‐based calculator. Issue 5 (14th July 2021)

• Record Type: Journal Article
• Authors: Yang, Zhuoxin; Yang, Fengwu; Yang, Miaofang; Qi, Ying; Jiang, Mingzuo; Xuan, Ji; Liu, Yu; Tao, Hui; Liu, Yuxiu; Wang, Fangyu
• Is Part Of: Journal of surgical oncology. Volume 124:Issue 5(2021)
• Page Start: 767
• Page End: 779
• Publication Date: 2021-07-14
• Subjects: esophageal cancer -- LASSO -- overall survival -- prediction model -- web‐based calculator; Cancer -- Surgery -- Periodicals; Neoplasms -- Periodicals; 616
• DOI: 10.1002/jso.26594
• Languages: English
• ISSNs: 0022-4790

Abstract

Abstract: Background and Aims: In this study, we aimed to develop a convenient web‐based calculator to predict the overall survival (OS) of patients with Stage I esophageal cancer (EC). Methods: Data of 1664 patients, between 2004 and 2015, were extracted from the Surveillance, Epidemiology, and End Results database. Least absolute shrinkage and selection operator regression was employed to sift variables; subsequently, Cox proportional hazards regression model was built. We applied the enhanced bootstrap validation to appraise the discrimination and calibration of the model. Clinical benefit was measured using decision curve analysis (DCA). Thereafter, a web‐based calculator based on the model, which could be used to predict the 1‐, 3‐, and 5‐year OS rates, was developed. Results: Race, age, histologic type, grade, N stage, and therapeutic methods were selected. C‐indices of the prediction model in the training and validation groups were 0.726 (95% confidence interval [CI], 0.679–0.773) and 0.724 (95% CI, 0.679–0.769), respectively. Calibration curves showed good agreement between the groups. The DCA demonstrated that the prediction model is clinically useful. Conclusions: The prediction model we developed showed a good performance in calculating the OS rates in patients with Stage I EC. The web‐based calculator is available at https://championship.shinyapps.io/dynnomapp/ .