Accurate prediction of progression to muscle-invasive disease in patients with pT1G3 bladder cancer: A clinical decision-making tool.

Urol Oncol

Department of Urology, Medical University of Vienna, Vienna, Austria; Department of Urology and Andrology, Karl Landsteiner Institute, Vienna, Austria; Department of Urology, University of Texas Southwestern Medical Centre, Dallas, TX; Department of Urology, Weill Cornell Medical College, New York, NY. Electronic address:

Published: May 2018

Purpose: To improve current prognostic models for the selection of patients with T1G3 urothelial bladder cancer who are more likely to fail intravesical therapy and progress to muscle-invasive bladder cancer (MIBC).

Materials And Methods: We performed a retrospective analysis of 1,289 patients with pT1G3 urothelial bladder cancer who were treated with transurethral resection of the bladder (TURB) and adjuvant intravesical bacillus-Calmette-Guérin (BCG). Random-split sample data and competing-risk regression were used to identify the independent impact of lymphovascular invasion (LVI) and variant histology (VH) on progression to MIBC. We developed a nomogram for predicting patient-specific probability of disease progression at 2 and 5 years after TURB. Decision curve analysis (DCA) was performed to evaluate the clinical benefit associated with the use of our nomogram.

Results: In the development cohort, within a median follow-up of 51.6 months (IQR: 19.3-92.5), disease progression occurred in 89 patients (13.8%). A total of 84 (13%) patients were found to have VH and 57 (8.8%) with LVI at TURB. Both factors were independently associated with disease progression on multivariable competing-risk analysis (HR: 4.4; 95% CI: 2.8-6.9; P<0.001 and HR: 3.5; 95% CI: 2.1-5.8; P<0.001, respectively). DCA showed superior net benefits for the nomogram within a threshold probability of progression between 5% and 55%. Limitations are inherent to the retrospective design.

Conclusions: We demonstrated the clinical value of the integration of LVI and VH in a prognostic model for the prediction of MIBC. Indeed, our tool provides superior individualized risk estimation of progression facilitating decision-making regarding early RC.

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Source
http://dx.doi.org/10.1016/j.urolonc.2018.01.018DOI Listing

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