Cosimo De Nunzio1, Riccardo Lombardo2, Giorgia Tema2, Hassan Alkhatatbeh3, Giorgio Gandaglia4, Alberto Briganti4, Andrea Tubaro2. 1. Department of Urology, "Sant'Andrea" Hospital, "La Sapienza" University, Rome, Italy. Electronic address: cosimodenunzio@virgilio.it. 2. Department of Urology, "Sant'Andrea" Hospital, "La Sapienza" University, Rome, Italy. 3. Department of Urology, The Hashemite University, Az-Zarqa, Jordan. 4. Department of Urology, Universita Vita-Salute San Raffaele, Milan, Italy.
Abstract
OBJECTIVES: The aim of our study was to analyze the performance of 5 different risk calculators for prostate cancer diagnosis: Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC), European Randomized Study of Screening for Prostate Cancer Risk Calculator (ERSP-RC), Karakiewicz nomogram, Chun nomogram, and Kawakami Nomogram. METHODS: From 2008 onwards, we consecutively enrolled, at a single institution in Italy, men undergoing 12-core transrectal ultrasound-guided prostate needle biopsy. Demographic, clinical, and pathological data were collected. The risk of prostate cancer (PCa) was calculated according to the PCPT-RC, ERSPC-RC, Karakiewicz, Kawakami, and Chun nomograms. Calibration and discrimination were assessed using calibration plots and receiver operator characteristic analysis. Additionally, decision curve analyses (DCA) were used to assess the net benefit associated with the adoption of each model. RESULTS: Overall, 1,100 patients were evaluated, 39% presented PCa and out of them 26% presented high-grade PCa (defined as Gleason ≥ 4 + 3). All the models showed good discrimination capacities for PCa on receiver operator characteristic analysis (area under the curve: 0.59-0.72) On calibration curves the ERSCP, the PCPT and the Chun nomogram underestimated the risk of PC while the Kawakami overestimated it. At DCA, the net benefit associated with the use of the models in the prediction of cancer was observed when the threshold probability was between 40% and 60%. CONCLUSION: In a cohort of Italian men undergoing prostate biopsy, the performance accuracy of these calculators for the prediction prostate cancer is suboptimal. According to our experience the use of these calculator in clinical practice should be encouraged. Although integration with new serum/urine markers or magnetic resonance imaging results is warranted.
OBJECTIVES: The aim of our study was to analyze the performance of 5 different risk calculators for prostate cancer diagnosis: Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC), European Randomized Study of Screening for Prostate Cancer Risk Calculator (ERSP-RC), Karakiewicz nomogram, Chun nomogram, and Kawakami Nomogram. METHODS: From 2008 onwards, we consecutively enrolled, at a single institution in Italy, men undergoing 12-core transrectal ultrasound-guided prostate needle biopsy. Demographic, clinical, and pathological data were collected. The risk of prostate cancer (PCa) was calculated according to the PCPT-RC, ERSPC-RC, Karakiewicz, Kawakami, and Chun nomograms. Calibration and discrimination were assessed using calibration plots and receiver operator characteristic analysis. Additionally, decision curve analyses (DCA) were used to assess the net benefit associated with the adoption of each model. RESULTS: Overall, 1,100 patients were evaluated, 39% presented PCa and out of them 26% presented high-grade PCa (defined as Gleason ≥ 4 + 3). All the models showed good discrimination capacities for PCa on receiver operator characteristic analysis (area under the curve: 0.59-0.72) On calibration curves the ERSCP, the PCPT and the Chun nomogram underestimated the risk of PC while the Kawakami overestimated it. At DCA, the net benefit associated with the use of the models in the prediction of cancer was observed when the threshold probability was between 40% and 60%. CONCLUSION: In a cohort of Italian men undergoing prostate biopsy, the performance accuracy of these calculators for the prediction prostate cancer is suboptimal. According to our experience the use of these calculator in clinical practice should be encouraged. Although integration with new serum/urine markers or magnetic resonance imaging results is warranted.
Authors: Jan Chandra Engel; Thorgerdur Palsdottir; Donna Ankerst; Sebastiaan Remmers; Ashkan Mortezavi; Venkatesh Chellappa; Lars Egevad; Henrik Grönberg; Martin Eklund; Tobias Nordström Journal: Eur Urol Open Sci Date: 2022-05-19
Authors: Cosimo De Nunzio; Jamil Ghahhari; Riccardo Lombardo; Giorgio Ivan Russo; Ana Albano; Antonio Franco; Valeria Baldassarri; Antonio Nacchia; Juan Lopez; Pilar Luque; Maria Jose Ribal; Antonio Alcaraz; Andrea Tubaro Journal: World J Urol Date: 2021-06-26 Impact factor: 4.226