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Nomogram for predicting overall survival time of patients with stage IV colorectal cancer

BACKGROUND: Prognosis varies among stage IV colorectal cancer (CRC). Our study aimed to build a robust prognostic nomogram for predicting overall survival (OS) of patients with stage IV CRC in order to provide evidence for individualized treatment. METHOD: We collected the information of 16,283 pati...

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Detalles Bibliográficos
Autores principales: Lv, Min-Yi, Chen, Xi-Jie, Chen, Jun-Guo, Zhang, Bin, Lin, Yan-Yun, Huang, Tian-Ze, He, De-Gao, Wang, Kai, Chi, Zeng-Jie, Hu, Jian-Cong, He, Xiao-Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9731212/
https://www.ncbi.nlm.nih.gov/pubmed/36518985
http://dx.doi.org/10.1093/gastro/goac072
Descripción
Sumario:BACKGROUND: Prognosis varies among stage IV colorectal cancer (CRC). Our study aimed to build a robust prognostic nomogram for predicting overall survival (OS) of patients with stage IV CRC in order to provide evidence for individualized treatment. METHOD: We collected the information of 16,283 patients with stage IV CRC in the Surveillance, Epidemiology, and End Results (SEER) database and then randomized these patients in a ratio of 7:3 into a training cohort and an internal validation cohort. In addition, 501 patients in the Sixth Affiliated Hospital of Sun Yat-sen University (Guangzhou, China) database were selected and used as an external validation cohort. Univariate and multivariate Cox analyses were used to screen out significant variables for nomogram establishment. The nomogram model was assessed using time-dependent receiver-operating characteristic curve (time-dependent ROC), concordance index (C-index), calibration curve, and decision curve analysis. Survival curves were plotted using the Kaplan–Meier method. RESULT: The C-index of the nomogram for OS in the training, internal validation, and external validation cohorts were 0.737, 0.727, and 0.655, respectively. ROC analysis and calibration curves pronounced robust discriminative ability of the model. Further, we divided the patients into a high-risk group and a low-risk group according to the nomogram. Corresponding Kaplan–Meier curves showed that the prediction of the nomogram was consistent with the actual practice. Additionally, model comparisons and decision curve analysis proved that the nomogram for predicting prognosis was significantly superior to the tumor-node-metastasis (TNM) staging system. CONCLUSIONS: We constructed a nomogram to predict OS of the stage IV CRC and externally validate its generalization, which was superior to the TNM staging system.