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Prediction of significant prostate cancer in biopsy-naïve men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS

BACKGROUND: Risk models (RM) need external validation to assess their value beyond the setting in which they were developed. We validated a RM combining mpMRI and clinical parameters for the probability of harboring significant prostate cancer (sPC, Gleason Score ≥ 3+4) for biopsy-naïve men. MATERIA...

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Autores principales: Radtke, Jan Philipp, Giganti, Francesco, Wiesenfarth, Manuel, Stabile, Armando, Marenco, Jose, Orczyk, Clement, Kasivisvanathan, Veeru, Nyarangi-Dix, Joanne Nyaboe, Schütz, Viktoria, Dieffenbacher, Svenja, Görtz, Magdalena, Stenzinger, Albrecht, Roth, Wilfried, Freeman, Alex, Punwani, Shonit, Bonekamp, David, Schlemmer, Heinz-Peter, Hohenfellner, Markus, Emberton, Mark, Moore, Caroline M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710031/
https://www.ncbi.nlm.nih.gov/pubmed/31450235
http://dx.doi.org/10.1371/journal.pone.0221350
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author Radtke, Jan Philipp
Giganti, Francesco
Wiesenfarth, Manuel
Stabile, Armando
Marenco, Jose
Orczyk, Clement
Kasivisvanathan, Veeru
Nyarangi-Dix, Joanne Nyaboe
Schütz, Viktoria
Dieffenbacher, Svenja
Görtz, Magdalena
Stenzinger, Albrecht
Roth, Wilfried
Freeman, Alex
Punwani, Shonit
Bonekamp, David
Schlemmer, Heinz-Peter
Hohenfellner, Markus
Emberton, Mark
Moore, Caroline M.
author_facet Radtke, Jan Philipp
Giganti, Francesco
Wiesenfarth, Manuel
Stabile, Armando
Marenco, Jose
Orczyk, Clement
Kasivisvanathan, Veeru
Nyarangi-Dix, Joanne Nyaboe
Schütz, Viktoria
Dieffenbacher, Svenja
Görtz, Magdalena
Stenzinger, Albrecht
Roth, Wilfried
Freeman, Alex
Punwani, Shonit
Bonekamp, David
Schlemmer, Heinz-Peter
Hohenfellner, Markus
Emberton, Mark
Moore, Caroline M.
author_sort Radtke, Jan Philipp
collection PubMed
description BACKGROUND: Risk models (RM) need external validation to assess their value beyond the setting in which they were developed. We validated a RM combining mpMRI and clinical parameters for the probability of harboring significant prostate cancer (sPC, Gleason Score ≥ 3+4) for biopsy-naïve men. MATERIAL AND METHODS: The original RM was based on data of 670 biopsy-naïve men from Heidelberg University Hospital who underwent mpMRI with PI-RADS scoring prior to MRI/TRUS-fusion biopsy 2012–2015. Validity was tested by a consecutive cohort of biopsy-naïve men from Heidelberg (n = 160) and externally by a cohort of 133 men from University College London Hospital (UCLH). Assessment of validity was performed at fusion-biopsy by calibration plots, receiver operating characteristics curve and decision curve analyses. The RM`s performance was compared to ERSPC-RC3, ERSPC-RC3+PI-RADSv1.0 and PI-RADSv1.0 alone. RESULTS: SPC was detected in 76 men (48%) at Heidelberg and 38 men (29%) at UCLH. The areas under the curve (AUC) were 0.86 for the RM in both cohorts. For ERSPC-RC3+PI-RADSv1.0 the AUC was 0.84 in Heidelberg and 0.82 at UCLH, for ERSPC-RC3 0.76 at Heidelberg and 0.77 at UCLH and for PI-RADSv1.0 0.79 in Heidelberg and 0.82 at UCLH. Calibration curves suggest that prevalence of sPC needs to be adjusted to local circumstances, as the RM overestimated the risk of harboring sPC in the UCLH cohort. After prevalence-adjustment with respect to the prevalence underlying ERSPC-RC3 to ensure a generalizable comparison, not only between the Heidelberg and die UCLH subgroup, the RM`s Net benefit was superior over the ERSPC`s and the mpMRI`s for threshold probabilities above 0.1 in both cohorts. CONCLUSIONS: The RM discriminated well between men with and without sPC at initial MRI-targeted biopsy but overestimated the sPC-risk at UCLH. Taking prevalence into account, the model demonstrated benefit compared with clinical risk calculators and PI-RADSv1.0 in making the decision to biopsy men at suspicion of PC. However, prevalence differences must be taken into account when using or validating the presented risk model.
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spelling pubmed-67100312019-09-10 Prediction of significant prostate cancer in biopsy-naïve men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS Radtke, Jan Philipp Giganti, Francesco Wiesenfarth, Manuel Stabile, Armando Marenco, Jose Orczyk, Clement Kasivisvanathan, Veeru Nyarangi-Dix, Joanne Nyaboe Schütz, Viktoria Dieffenbacher, Svenja Görtz, Magdalena Stenzinger, Albrecht Roth, Wilfried Freeman, Alex Punwani, Shonit Bonekamp, David Schlemmer, Heinz-Peter Hohenfellner, Markus Emberton, Mark Moore, Caroline M. PLoS One Research Article BACKGROUND: Risk models (RM) need external validation to assess their value beyond the setting in which they were developed. We validated a RM combining mpMRI and clinical parameters for the probability of harboring significant prostate cancer (sPC, Gleason Score ≥ 3+4) for biopsy-naïve men. MATERIAL AND METHODS: The original RM was based on data of 670 biopsy-naïve men from Heidelberg University Hospital who underwent mpMRI with PI-RADS scoring prior to MRI/TRUS-fusion biopsy 2012–2015. Validity was tested by a consecutive cohort of biopsy-naïve men from Heidelberg (n = 160) and externally by a cohort of 133 men from University College London Hospital (UCLH). Assessment of validity was performed at fusion-biopsy by calibration plots, receiver operating characteristics curve and decision curve analyses. The RM`s performance was compared to ERSPC-RC3, ERSPC-RC3+PI-RADSv1.0 and PI-RADSv1.0 alone. RESULTS: SPC was detected in 76 men (48%) at Heidelberg and 38 men (29%) at UCLH. The areas under the curve (AUC) were 0.86 for the RM in both cohorts. For ERSPC-RC3+PI-RADSv1.0 the AUC was 0.84 in Heidelberg and 0.82 at UCLH, for ERSPC-RC3 0.76 at Heidelberg and 0.77 at UCLH and for PI-RADSv1.0 0.79 in Heidelberg and 0.82 at UCLH. Calibration curves suggest that prevalence of sPC needs to be adjusted to local circumstances, as the RM overestimated the risk of harboring sPC in the UCLH cohort. After prevalence-adjustment with respect to the prevalence underlying ERSPC-RC3 to ensure a generalizable comparison, not only between the Heidelberg and die UCLH subgroup, the RM`s Net benefit was superior over the ERSPC`s and the mpMRI`s for threshold probabilities above 0.1 in both cohorts. CONCLUSIONS: The RM discriminated well between men with and without sPC at initial MRI-targeted biopsy but overestimated the sPC-risk at UCLH. Taking prevalence into account, the model demonstrated benefit compared with clinical risk calculators and PI-RADSv1.0 in making the decision to biopsy men at suspicion of PC. However, prevalence differences must be taken into account when using or validating the presented risk model. Public Library of Science 2019-08-26 /pmc/articles/PMC6710031/ /pubmed/31450235 http://dx.doi.org/10.1371/journal.pone.0221350 Text en © 2019 Radtke et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Radtke, Jan Philipp
Giganti, Francesco
Wiesenfarth, Manuel
Stabile, Armando
Marenco, Jose
Orczyk, Clement
Kasivisvanathan, Veeru
Nyarangi-Dix, Joanne Nyaboe
Schütz, Viktoria
Dieffenbacher, Svenja
Görtz, Magdalena
Stenzinger, Albrecht
Roth, Wilfried
Freeman, Alex
Punwani, Shonit
Bonekamp, David
Schlemmer, Heinz-Peter
Hohenfellner, Markus
Emberton, Mark
Moore, Caroline M.
Prediction of significant prostate cancer in biopsy-naïve men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS
title Prediction of significant prostate cancer in biopsy-naïve men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS
title_full Prediction of significant prostate cancer in biopsy-naïve men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS
title_fullStr Prediction of significant prostate cancer in biopsy-naïve men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS
title_full_unstemmed Prediction of significant prostate cancer in biopsy-naïve men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS
title_short Prediction of significant prostate cancer in biopsy-naïve men: Validation of a novel risk model combining MRI and clinical parameters and comparison to an ERSPC risk calculator and PI-RADS
title_sort prediction of significant prostate cancer in biopsy-naïve men: validation of a novel risk model combining mri and clinical parameters and comparison to an erspc risk calculator and pi-rads
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710031/
https://www.ncbi.nlm.nih.gov/pubmed/31450235
http://dx.doi.org/10.1371/journal.pone.0221350
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