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

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).

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.

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.

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.

Urologic oncology. 2018 Mar 02 [Epub ahead of print]

David D Andrea, Mohammad Abufaraj, Martin Susani, Robin Ristl, Beat Foerster, Shoji Kimura, Andrea Mari, Francesco Soria, Alberto Briganti, Pierre I Karakiewicz, Killian M Gust, Morgan Rouprêt, Shahrokh F Shariat

Department of Urology, Medical University of Vienna, Vienna, Austria., Department of Urology, Medical University of Vienna, Vienna, Austria; Division of Urology, Department of Special Surgery, Jordan University Hospital, The University of Jordan, Amman, Jordan., Department of Pathology, Medical University of Vienna, Vienna, Austria., Institute for Medical Statistic, Center for Medical Statistics, Informatics and Intelligent Systems (CEMSIIS), Medical University of Vienna, Vienna, Austria., Department of Urology, Medical University of Vienna, Vienna, Austria; Department of Urology, Kantonsspital Winterthur, Winterthur, Switzerland., Department of Urology, Medical University of Vienna, Vienna, Austria; Department of Urology, Jikei University School of Medicine, Tokyo, Japan., Department of Urology, Urological Research Institute, Vita-Salute University, San Raffaele Scientific Institute, Milan, Italy., Department of Urology, University of Montreal, Montreal, Canada., Department of Urology, Pitié-Salpétrière, Assistance-Publique Hôpitaux de Paris and Faculté de Médecine Pierre et Marie Curie, University Paris VI, Paris, France., 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: .