Prognostic Risk Stratification of Patients with Urothelial Carcinoma of the Urinary Bladder who Developed Recurrence after Radical Cystectomy
Nakagawa T, Hara T, Kawahara T, Ogata Y, Nakanishi H, Komiyama M, Arai E, Kanai Y, Fujimoto H. J Urol. 2012 Oct 30. pii: S0022-5347(12)05353-0. doi: 10.1016/j.juro.2012.10.065. [Epub ahead of print]

Source

Department of Urology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan. Electronic address: tohru-tky@umin.ac.jp.

Abstract

PURPOSE:

To identify the clinicopathological variables predicting post-recurrence overall survival (OS) in patients with urothelial carcinoma (UC) of the urinary bladder who developed recurrence after radical cystectomy (RC).

MATERIALS AND METHODS:

Data from 114 patients treated with RC for UC of the urinary bladder and who subsequently developed remote metastasis and/or local recurrence were retrospectively collected. The Kaplan-Meier method with the log-rank test and multivariable Cox regression models addressed OS after recurrence.

RESULTS:

During follow-up, 99 of the 114 patients died. The median survival time for the 114 patients was 11.2 months. The 1- and 3-year OS were 48.0% and 12.1%, respectively. On multivariable analyses, independent predictors of poorer OS included time to recurrence (TTR) of <1 year, presence of symptoms on recurrence, two or more metastatic organs on recurrence, high serum C-reactive protein (CRP) level, high lactate dehydrogenase level, no post-recurrence platinum-based chemotherapy, and no metastasectomy. Based on the four variables (TTR, symptoms, number of metastatic organs, and CRP), a risk model predicting post-recurrence OS was constructed that classified patients into three groups with significantly different OS (p < 0.0001).

CONCLUSIONS:

Our data confirmed that recurrent UC after RC is a highly aggressive, lethal disease. Seven clinicopathological factors were identified that predicted post-recurrence OS. Our risk model based on the four variables would be useful to provide relevant prognostic information to patients and physicians and to better stratify patients in clinical trials.