Elucidating the need for prostate cancer risk calculators in conjunction with mpMRI in initial risk assessment before prostate biopsy at a tertiary prostate cancer center
© 2024. The Author(s)..
OBJECTIVE: Utilizing personalized risk assessment for clinically significant prostate cancer (csPCa) incorporating multiparametric magnetic resonance imaging (mpMRI) reduces biopsies and overdiagnosis. We validated both multi- and univariate risk models in biopsy-naïve men, with and without the inclusion of mpMRI data for csPCa detection.
METHODS: N = 565 men underwent mpMRI-targeted prostate biopsy, and the diagnostic performance of risk calculators (RCs), mpMRI alone, and clinical measures were compared using receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA). Subgroups were stratified based on mpMRI findings and quality.
RESULTS: csPCa was detected in 56.3%. PI-RADS score achieved the highest area under the curve (AUC) when comparing univariate risk models (AUC 0.82, p < 0.001). Multivariate RCs showed only marginal improvement in csPCa detection compared to PI-RADS score alone, with just one of four RCs showing significant superiority. In mpMRI-negative cases, the non-MRI-based RC performed best (AUC 0.80, p = 0.016), with the potential to spare biopsies for 23%. PSA-density and multivariate RCs demonstrated comparable performance for PI-RADS 3 constellation (AUC 0.65 vs. 0.60-0.65, p > 0.5; saved biopsies 16%). In men with suspicious mpMRI, both mpMRI-based RCs and the PI-RADS score predicted csPCa excellently (AUC 0.82-0.79 vs. 0.80, p > 0.05), highlighting superior performance compared to non-MRI-based models (all p < 0.002). Quality-assured imaging consistently improved csPCa risk stratification across all subgroups.
CONCLUSION: In tertiary centers serving a high-risk population, high-quality mpMRI provides a simple yet effective way to assess the risk of csPCa. Using multivariate RCs reduces multiple biopsies, especially in mpMRI-negative and PI-RADS 3 constellation.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:24 |
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| Enthalten in: |
BMC urology - 24(2024), 1 vom: 26. März, Seite 71 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Krausewitz, Philipp [VerfasserIn] |
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| Links: |
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| Themen: |
Clinically significant prostate cancer |
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| Anmerkungen: |
Date Completed 28.03.2024 Date Revised 29.03.2024 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1186/s12894-024-01460-5 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM37021918X |
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| 100 | 1 | |a Krausewitz, Philipp |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Elucidating the need for prostate cancer risk calculators in conjunction with mpMRI in initial risk assessment before prostate biopsy at a tertiary prostate cancer center |
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| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2024. The Author(s). | ||
| 520 | |a OBJECTIVE: Utilizing personalized risk assessment for clinically significant prostate cancer (csPCa) incorporating multiparametric magnetic resonance imaging (mpMRI) reduces biopsies and overdiagnosis. We validated both multi- and univariate risk models in biopsy-naïve men, with and without the inclusion of mpMRI data for csPCa detection | ||
| 520 | |a METHODS: N = 565 men underwent mpMRI-targeted prostate biopsy, and the diagnostic performance of risk calculators (RCs), mpMRI alone, and clinical measures were compared using receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA). Subgroups were stratified based on mpMRI findings and quality | ||
| 520 | |a RESULTS: csPCa was detected in 56.3%. PI-RADS score achieved the highest area under the curve (AUC) when comparing univariate risk models (AUC 0.82, p < 0.001). Multivariate RCs showed only marginal improvement in csPCa detection compared to PI-RADS score alone, with just one of four RCs showing significant superiority. In mpMRI-negative cases, the non-MRI-based RC performed best (AUC 0.80, p = 0.016), with the potential to spare biopsies for 23%. PSA-density and multivariate RCs demonstrated comparable performance for PI-RADS 3 constellation (AUC 0.65 vs. 0.60-0.65, p > 0.5; saved biopsies 16%). In men with suspicious mpMRI, both mpMRI-based RCs and the PI-RADS score predicted csPCa excellently (AUC 0.82-0.79 vs. 0.80, p > 0.05), highlighting superior performance compared to non-MRI-based models (all p < 0.002). Quality-assured imaging consistently improved csPCa risk stratification across all subgroups | ||
| 520 | |a CONCLUSION: In tertiary centers serving a high-risk population, high-quality mpMRI provides a simple yet effective way to assess the risk of csPCa. Using multivariate RCs reduces multiple biopsies, especially in mpMRI-negative and PI-RADS 3 constellation | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Clinically significant prostate cancer | |
| 650 | 4 | |a Prostate biopsy | |
| 650 | 4 | |a Risk calculators | |
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| 700 | 1 | |a Büttner, Thomas |e verfasserin |4 aut | |
| 700 | 1 | |a von Danwitz, Marthe |e verfasserin |4 aut | |
| 700 | 1 | |a Weiten, Richard |e verfasserin |4 aut | |
| 700 | 1 | |a Cox, Alexander |e verfasserin |4 aut | |
| 700 | 1 | |a Klümper, Niklas |e verfasserin |4 aut | |
| 700 | 1 | |a Stein, Johannes |e verfasserin |4 aut | |
| 700 | 1 | |a Luetkens, Julian |e verfasserin |4 aut | |
| 700 | 1 | |a Kristiansen, Glen |e verfasserin |4 aut | |
| 700 | 1 | |a Ritter, Manuel |e verfasserin |4 aut | |
| 700 | 1 | |a Ellinger, Jörg |e verfasserin |4 aut | |
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