Gabriele Sorce1,2, Rocco Simone Flammia3,4, Benedikt Hoeh3,5, Francesco Chierigo3,6, Benedikt Horlemann3, Christoph Würnschimmel3,7, Zhe Tian3, Markus Graefen7, Carlo Terrone6, Michele Gallucci4, Felix K H Chun5, Fred Saad3, Shahrokh F Shariat8,9,10,11,12,13, Francesco Montorsi14, Alberto Briganti14, Pierre I Karakiewicz3. 1. Department of Urology and Division of Experimental Oncology, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. sorce.gabriele@hsr.it. 2. Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montréal Health Center, Montréal, Québec, Canada. sorce.gabriele@hsr.it. 3. Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montréal Health Center, Montréal, Québec, Canada. 4. Department of Maternal-Child and Urological Sciences, Sapienza University Rome, Policlinico Umberto I Hospital, Rome, Italy. 5. Department of Urology, University Hospital Frankfurt, Frankfurt am Main, Germany. 6. Department of Surgical and Diagnostic Integrated Sciences (DISC), University of Genova, Genova, Italy. 7. Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany. 8. Departments of Urology, Weill Cornell Medical College, New York, NY, USA. 9. Department of Urology, University of Texas Southwestern, Dallas, TX, USA. 10. Department of Urology, Second Faculty of Medicine, Charles University, Prag, Czech Republic. 11. Institute for Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University, Moscow, Russia. 12. Division of Urology, Department of Special Surgery, Jordan University Hospital, The University of Jordan, Amman, Jordan. 13. Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria. 14. Department of Urology and Division of Experimental Oncology, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy.
Abstract
PURPOSE: Data about optimal management of plasmacytoid (PCV) bladder cancer patients are extremely scarce and limited by sample size. We focused on PCV bladder cancer patients to explore the effect of radical cystectomy (RC) and chemotherapy in non-metastatic (T 2-4N0-3M0), as well as in metastatic (TanyNanyM1) subgroups. METHODS: Using the Surveillance, Epidemiology and End Results database (2000-2016), we identified 332 PCV patients with muscle-invasive disease or higher (≥ T2N0M0). Kaplan-Meier plots and Cox regression models addressed cancer-specific mortality (CSM). RESULTS: In 332 PCV patients, median age was 68 years (Interquartile range [IQR]:58-76). Of those, 252 were non-metastatic patients (76%) vs 80 were metastatic patients (24%), at presentation. Of non-metastatic patients, 142 (56%) underwent RC and 131 (52%) underwent chemotherapy. Chemotherapy did not improve CSM in non-metastatic PCV. Conversely, RC was associated with lower CSM (hazard ratio [HR]: 0.51, p = 0.002). Median CSM-free survival was 48 vs 38 months for RC treated vs RC not treated. Of metastatic patients, 22 (28%) underwent RC and 42 (52%) underwent chemotherapy. Both chemotherapy and RC improved CSM in metastatic PCV. Median CSM-free survival was 12 vs 7 months for RC treated vs RC not treated (HR: 0.27, p < 0.001). Median CSM-free survival was 11 vs 4 months for chemotherapy exposed vs chemotherapy naïve (HR: 0.32, p = 0.002). CONCLUSIONS: Although RC resulted in lower CSM, chemotherapy failed to show that effect in non-metastatic PCV patients. Conversely, both chemotherapy and RC resulted in statistically significantly lower CSM in metastatic PCV patients.
PURPOSE: Data about optimal management of plasmacytoid (PCV) bladder cancer patients are extremely scarce and limited by sample size. We focused on PCV bladder cancer patients to explore the effect of radical cystectomy (RC) and chemotherapy in non-metastatic (T 2-4N0-3M0), as well as in metastatic (TanyNanyM1) subgroups. METHODS: Using the Surveillance, Epidemiology and End Results database (2000-2016), we identified 332 PCV patients with muscle-invasive disease or higher (≥ T2N0M0). Kaplan-Meier plots and Cox regression models addressed cancer-specific mortality (CSM). RESULTS: In 332 PCV patients, median age was 68 years (Interquartile range [IQR]:58-76). Of those, 252 were non-metastatic patients (76%) vs 80 were metastatic patients (24%), at presentation. Of non-metastatic patients, 142 (56%) underwent RC and 131 (52%) underwent chemotherapy. Chemotherapy did not improve CSM in non-metastatic PCV. Conversely, RC was associated with lower CSM (hazard ratio [HR]: 0.51, p = 0.002). Median CSM-free survival was 48 vs 38 months for RC treated vs RC not treated. Of metastatic patients, 22 (28%) underwent RC and 42 (52%) underwent chemotherapy. Both chemotherapy and RC improved CSM in metastatic PCV. Median CSM-free survival was 12 vs 7 months for RC treated vs RC not treated (HR: 0.27, p < 0.001). Median CSM-free survival was 11 vs 4 months for chemotherapy exposed vs chemotherapy naïve (HR: 0.32, p = 0.002). CONCLUSIONS: Although RC resulted in lower CSM, chemotherapy failed to show that effect in non-metastatic PCV patients. Conversely, both chemotherapy and RC resulted in statistically significantly lower CSM in metastatic PCV patients.
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