Luigi Nocera1,2, Claudia Collà Ruvolo3,4, Lara F Stolzenbach3,5, Marina Deuker3,6, Zhe Tian3, Giorgio Gandaglia7, Nicola Fossati7, Firas Abdollah8, Nazareno Suardi9, Vincenzo Mirone4, Markus Graefen5, Felix K Chun6, Fred Saad3, Francesco Montorsi7, Alberto Briganti7, Pierre I Karakiewicz3. 1. Unit of Cancer Prognostics and Health Outcomes, Division of Urology, University of Montreal Health Center, Montreal, QC, Canada - nocera.luigi@hsr.it. 2. Division of Experimental Oncology, Unit of Urology, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy - nocera.luigi@hsr.it. 3. Unit of Cancer Prognostics and Health Outcomes, Division of Urology, University of Montreal Health Center, Montreal, QC, Canada. 4. Department of Urology, University of Naples Federico II, Naples, Italy. 5. Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany. 6. Department of Urology, University Hospital Frankfurt, Frankfurt am Main, Germany. 7. Division of Experimental Oncology, Unit of Urology, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy. 8. Center for Outcomes Research, Analytics, and Evaluation, Vattikuti Urology Institute, Henry Ford Health System, Detroit, MI, USA. 9. Department of Urology, IRCCS San Martino University Hospital, University of Genoa, Genoa, Italy.
Abstract
BACKGROUND: Intermediate risk prostate cancer (IR PCa) may exhibit a wide array of phenotypes, from favorable to unfavorable. NCCN criteria help distinguishing between favorable versus unfavorable subgroups. We studied and attempted to improve this classification. METHODS: Within the SEER database 2010-2016, we identified 19,193 IR PCa patients treated with radical prostatectomy. A multivariable logistic regression model predicting unfavorable IR PCa was developed and externally validated, in addition to a head-to-head comparison with NCCN IR PCa stratification. RESULTS: Model development (development cohort N.=13,436: 3585 unfavorable versus 9851 favorable) rested on age, PSA, clinical T stage, biopsy Gleason Grade Group (GGG) and percentage of positive cores. All were independent predictors of unfavorable IR PCa. In external validation cohort (N.=5757: 1652 unfavorable versus 4105 favorable), NCCN stratification was 61.8% accurate in discriminating between favorable versus unfavorable, compared to 67.6% for nomogram, which exhibited excellent calibration, less pronounced departures from ideal prediction and greater net-benefit in decision curve analyses (DCA) than NCCN stratification. The optimal nomogram cutoff misclassified 312 of 1976 patients (15.8%) versus 598 of 2877 (20.8%) for NCCN stratification. Of NCCN misclassified patients, 90.0% harbored pT3-4 stages versus 84.6% of nomogram. CONCLUSIONS: The newly developed, externally validated nomogram discriminates better between favorable versus unfavorable IR PCa, according to overall accuracy, calibration, DCA, and actual numbers and stage distribution of misclassified patients.
BACKGROUND: Intermediate risk prostate cancer (IR PCa) may exhibit a wide array of phenotypes, from favorable to unfavorable. NCCN criteria help distinguishing between favorable versus unfavorable subgroups. We studied and attempted to improve this classification. METHODS: Within the SEER database 2010-2016, we identified 19,193 IR PCa patients treated with radical prostatectomy. A multivariable logistic regression model predicting unfavorable IR PCa was developed and externally validated, in addition to a head-to-head comparison with NCCN IR PCa stratification. RESULTS: Model development (development cohort N.=13,436: 3585 unfavorable versus 9851 favorable) rested on age, PSA, clinical T stage, biopsy Gleason Grade Group (GGG) and percentage of positive cores. All were independent predictors of unfavorable IR PCa. In external validation cohort (N.=5757: 1652 unfavorable versus 4105 favorable), NCCN stratification was 61.8% accurate in discriminating between favorable versus unfavorable, compared to 67.6% for nomogram, which exhibited excellent calibration, less pronounced departures from ideal prediction and greater net-benefit in decision curve analyses (DCA) than NCCN stratification. The optimal nomogram cutoff misclassified 312 of 1976 patients (15.8%) versus 598 of 2877 (20.8%) for NCCN stratification. Of NCCN misclassified patients, 90.0% harbored pT3-4 stages versus 84.6% of nomogram. CONCLUSIONS: The newly developed, externally validated nomogram discriminates better between favorable versus unfavorable IR PCa, according to overall accuracy, calibration, DCA, and actual numbers and stage distribution of misclassified patients.
Authors: Luigi Nocera; Mike Wenzel; Claudia Collà Ruvolo; Christoph Würnschimmel; Zhe Tian; Giorgio Gandaglia; Nicola Fossati; Felix K H Chun; Vincenzo Mirone; Markus Graefen; Fred Saad; Shahrokh F Shariat; Francesco Montorsi; Alberto Briganti; Pierre I Karakiewicz Journal: World J Urol Date: 2021-08-26 Impact factor: 4.226
Authors: Rebecca De Lorenzo; Cristiano Magnaghi; Elena Cinel; Giordano Vitali; Sabina Martinenghi; Mario G Mazza; Luigi Nocera; Marta Cilla; Sarah Damanti; Nicola Compagnone; Marica Ferrante; Caterina Conte; Francesco Benedetti; Fabio Ciceri; Patrizia Rovere-Querini Journal: Front Med (Lausanne) Date: 2022-02-23