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

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 pati...

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Detalles Bibliográficos
Autores principales: Liu, Hao, Li, Yu, Qu, Yi-Dan, Zhao, Jun-Jiang, Zheng, Zi-Wen, Jiao, Xue-Long, Zhang, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7942048/
https://www.ncbi.nlm.nih.gov/pubmed/33728300
http://dx.doi.org/10.12998/wjcc.v9.i7.1563
Descripción
Sumario: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%CI 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.