Application of nomograms in the prediction of overall survival and cancer-specific survival in patients with T1 high-grade bladder cancer.

To predict survival outcomes for individual patients with clinical T1 high-grade (T1HG) bladder cancer (BC), data from the Surveillance Epidemiology and End Results (SEER) database were analyzed in the present study. The data of 6,980 cases of T1HG BC between 2004 and 2014 were obtained from the SEER database. Uni- and multivariate Cox analyses were performed to identify significant prognostic factors. Subsequently, prognostic nomograms for predicting 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) rates were constructed based on the SEER database. Clinical information from the SEER database was divided into internal and external groups and used to validate the nomograms. In addition, calibration plot diagrams and concordance indices (C-indices) were used to verify the predictive performance of the nomogram. A total of 6,980 patients were randomly allocated to the training cohort (n=4,886) or the validation cohort (n=2094). Univariate and multivariate Cox analyses indicated that age, ethnicity, tumor size, marital status, radiation and surgical status were independent prognostic factors. These characteristics were used to establish nomograms. The C-indices for OS and CSS rate predictions for the training cohort were 0.707 (95% CI, 0.693-0.721) and 0.700 (95% CI, 0.679-0.721), respectively. Internal and external calibration plot diagrams exhibited an excellent consistency between actual survival rates and nomogram predictions, particularly for 3- and 5-year OS and CSS. The significant prognostic factors in patients with T1HG BC were age, ethnicity, marital status, tumor size, status of surgery and use of radiation. In the present study, a nomogram was developed that may serve as an effective and convenient evaluation tool to help surgeons perform individualized survival evaluations and mortality risk determination for patients with T1HG BC.

Experimental and therapeutic medicine. 2019 Sep 06 [Epub]

Fucai Tang, Zhaohui He, Zechao Lu, Weijia Wu, Yiwen Chen, Genggeng Wei, Yangzhou Liu

Department of Urology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong 518033, P.R. China., The First Clinical College of Guangzhou Medical University, Guangzhou, Guangdong 510230, P.R. China., Deparement of Urology, Longgang District Central Hospital, Shenzhen, Guangdong 518100, P.R. China., Department of Urology, Hongkong University-Shenzhen Hospital, Shenzhen, Guangdong 518053, P.R. China., Department of Urology, Minimally Invasive Surgery Center, Guangdong Provincial Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510230, P.R. China.