Anna-Lena Petersmann1, Sebastiaan Remmers2, Tilman Klein1, Panagiota Manava3, Clemens Huettenbrink1, Sascha A Pahernik1, Florian A Distler4. 1. Department of Urology, Paracelsus Medical University Nuremberg, Prof. Ernst Nathan Str. 1, 90419, Nuremberg, Germany. 2. Department of Urology, Erasmus University Medical Centre, Rotterdam, The Netherlands. 3. Institute of Radiology and Nuclear Medicine, Paracelsus Medical University Nuremberg, Nuremberg, Germany. 4. Department of Urology, Paracelsus Medical University Nuremberg, Prof. Ernst Nathan Str. 1, 90419, Nuremberg, Germany. distlerflorian@arcor.de.
Abstract
BACKGROUND: The diagnosis of (significant) prostate cancer ((s)PC) is impeded by overdiagnosis and unnecessary biopsy. Risk calculators (RC) have been developed to mitigate these issues. Contemporary RCs integrate clinical characteristics with mpMRI findings. OBJECTIVE: To validate two of these models-the MRI-ERSPC-RC-3/4 and the risk model of van Leeuwen. METHODS: 265 men with clinical suspicion of PC were enrolled. Every patient received a prebiopsy mpMRI, which was reported according to PI-RADS v2.1, followed by MRI/TRUS fusion-biopsy. Cancers with ISUP grade ≥ 2 were classified as sPC. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Statistical analysis was performed by comparing discrimination, calibration, and clinical utility RESULTS: There was no significant difference in discrimination between the RCs. The MRI-ERSPC-RC-3/4-RC showed a nearly ideal calibration-slope (0.94; 95% CI 0.68-1.20) than the van Leeuwen model (0.70; 95% CI 0.52-0.88). Within a threshold range up to 9% for a sPC, the MRI-ERSPC-RC-3/4-RC shows a greater net benefit than the van Leeuwen model. From 10 to 15%, the van Leeuwen model showed a higher net benefit compared to the MRI-ERSP-3/4-RC. For a risk threshold of 15%, the van Leeuwen model would avoid 24% vs. 14% compared to the MRI-ERSPC-RC-3/4 model; 6% vs. 5% sPC would be overlooked, respectively. CONCLUSION: Both risk models supply accurate results and reduce the number of biopsies and basically no sPC were overlooked. The van Leeuwen model suggests a better balance between unnecessary biopsies and overlooked sPC at thresholds range of 10-15%. The MRI-ERSPC-RC-3/4 risk model provides better overall calibration.
BACKGROUND: The diagnosis of (significant) prostate cancer ((s)PC) is impeded by overdiagnosis and unnecessary biopsy. Risk calculators (RC) have been developed to mitigate these issues. Contemporary RCs integrate clinical characteristics with mpMRI findings. OBJECTIVE: To validate two of these models-the MRI-ERSPC-RC-3/4 and the risk model of van Leeuwen. METHODS: 265 men with clinical suspicion of PC were enrolled. Every patient received a prebiopsy mpMRI, which was reported according to PI-RADS v2.1, followed by MRI/TRUS fusion-biopsy. Cancers with ISUP grade ≥ 2 were classified as sPC. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Statistical analysis was performed by comparing discrimination, calibration, and clinical utility RESULTS: There was no significant difference in discrimination between the RCs. The MRI-ERSPC-RC-3/4-RC showed a nearly ideal calibration-slope (0.94; 95% CI 0.68-1.20) than the van Leeuwen model (0.70; 95% CI 0.52-0.88). Within a threshold range up to 9% for a sPC, the MRI-ERSPC-RC-3/4-RC shows a greater net benefit than the van Leeuwen model. From 10 to 15%, the van Leeuwen model showed a higher net benefit compared to the MRI-ERSP-3/4-RC. For a risk threshold of 15%, the van Leeuwen model would avoid 24% vs. 14% compared to the MRI-ERSPC-RC-3/4 model; 6% vs. 5% sPC would be overlooked, respectively. CONCLUSION: Both risk models supply accurate results and reduce the number of biopsies and basically no sPC were overlooked. The van Leeuwen model suggests a better balance between unnecessary biopsies and overlooked sPC at thresholds range of 10-15%. The MRI-ERSPC-RC-3/4 risk model provides better overall calibration.
Authors: Steven C Smith; Kiril Trpkov; Ying-Bei Chen; Rohit Mehra; Deepika Sirohi; Chisato Ohe; Andi K Cani; Daniel H Hovelson; Kei Omata; Jonathan B McHugh; Wolfram Jochum; Maurizio Colecchia; Mitual Amin; Mukul K Divatia; Ondřej Hes; Santosh Menon; Isabela Werneck da Cunha; Sergio Tripodi; Fadi Brimo; Anthony J Gill; Adeboye O Osunkoya; Cristina Magi-Galluzzi; Mathilde Sibony; Sean R Williamson; Gabriella Nesi; Maria M Picken; Fiona Maclean; Abbas Agaimy; Liang Cheng; Jonathan I Epstein; Victor E Reuter; Satish K Tickoo; Scott A Tomlins; Mahul B Amin Journal: Am J Surg Pathol Date: 2016-11 Impact factor: 6.394
Authors: Marinus J Hagens; Piter J Stelwagen; Hans Veerman; Sybren P Rynja; Martijn Smeenge; Vincent van der Noort; Ton A Roeleveld; Jolien van Kesteren; Sebastiaan Remmers; Monique J Roobol; Pim J van Leeuwen; Henk G van der Poel Journal: World J Urol Date: 2022-10-16 Impact factor: 3.661