Construction of a clinical survival prognostic model for middle-aged and elderly patients with stage III rectal adenocarcinoma

paythelady.612 shared this article with you from Inoreader Construction of a clinical survival prognostic model for middle-aged and elderly patients with stage III rectal adenocarcinoma Μέσω pubmed: "world j clin cases"... World J Clin Cases. 2021 Mar 6;9(7):1563-1579. doi: 10.12998/wjcc.v9.i7.1563. ABSTRACT BACKGROUND: Nomograms for prognosis prediction in colorectal cancer patients are few, and prognostic indicators differ with age. AIM: To construct a new nomogram survival prediction tool for middle-aged and elderly patients with stage III rectal adenocarcinoma. METHODS: A total of 2773 eligible patients were divided into the training cohort (70%) and the validation cohort (30%). Optimal cutoff values were calculated using the X-tile software for continuous variables. Univariate and multivariate Cox proportional hazards regression analyses were used to determine overall survival (OS) and cancer-specific survival (CSS)-related prognostic factors. Two nomograms were successfully constructed. The discriminant and predictive ability and clinical usefulness of the model were also assessed by multiple methods of analysis. RESULTS: The 95%C I in the training group was 0.719 (0.690-0.749) and 0.733 (0.702-0.74), while that in the validation group was 0.739 (0.696-0.782) and 0.750 (0.701-0.800) for the OS and CSS nomogram prediction models, respectively. In the validation group, the AUC of the three-year survival rate was 0.762 and 0.770, while the AUC of the five-year survival rate was 0.722 and 0.744 for the OS and CSS nomograms, respectively. The nomogram distinguishes all-cause mortality from cancer-specific mortality in patients with different risk grades. The time-dependent AUC and decision curve analysis showed that the nomogram had good clinical predictive ability and decision efficacy and was significantly better than the tumor-node-metastases staging system. CONCLUSION: The survival prediction model constructed in this study is helpful in evaluating the prognosis of patients and can aid physicians in clinical diagnosis and treatment. PMID:33728300 | PMC:PMC7942048 | DOI:10.12998/wjcc.v9.i7.1563 View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.