Construction of a competing risk model for disease-free survival of patients with non-muscle invasive bladder cancer / 现代泌尿外科杂志
Journal of Modern Urology
; (12): 487-492, 2023.
Article
in Zh
| WPRIM
| ID: wpr-1006044
Responsible library:
WPRO
ABSTRACT
【Objective】 To construct an easy-to-use individual survival prognostic tool based on competing risk analyses to predict the risk of 1-, 2- and 3- year recurrence for patients with non-muscle invasive bladder cancer (NMIBC). 【Methods】 The follow-up data of 419 NMIBC patients were obtained. The patients were randomly divided into training cohort (n=293) and validation cohort (n=126). The variables included age at diagnosis, sex, history of smoking, tumor number, tumor size, histolo-gic grade, pathological stage, and bladder perfusion drug. The cumulative incidence function (CIF) of recurrence was estimated using all variables in the training cohort and potential prognostic variables were determined with Gray’s test. The Fine-Gray subdistribution proportional hazard approach was used as a multivariate competitive risk analysis to identify independent pro-gnostic variables. A competing risk nomogram was developed to predict the recurrence. The performance of the competing risk model was evaluated with the area under the receiver operating characteristic curve (AUC), calibration curve, and Brier score. 【Results】 Five independent prognostic factors including age, number of tumors, tumor size, histologic grade and pathological stage were used to construct the competing risk model. In the validation cohort, the AUC of 1-, 2- and 3- year recurrence were 0.895 (95%CI: 0.831-0.959), 0.861(95%CI: 0.774-0.948) and 0.827(95%CI: 0.721-0.934), respectively, indicating that the model had a high predictive performance. 【Conclusion】 We successfully constructed a competing risk model to predict the risk of 1-, 2- and 3-year recurrence for NMIBC patients. It may help clinicians to improve the postoperative management of patients.
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Index:
WPRIM
Language:
Zh
Journal:
Journal of Modern Urology
Year:
2023
Type:
Article