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Prostate Health Index and Multiparametric MRI: Partners in Crime Fighting Overdiagnosis and Overtreatment in Prostate Cancer

SIMPLE SUMMARY: In the last decades, the widespread use of PSA as the standard tool for prostate cancer diagnosis led to a high rate of overdiagnosis and overtreatment. More recently, multiparametric magnetic resonance imaging (mpMRI) became part of the diagnostic pathway, and several next-generatio...

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Autores principales: Ferro, Matteo, Crocetto, Felice, Bruzzese, Dario, Imbriaco, Massimo, Fusco, Ferdinando, Longo, Nicola, Napolitano, Luigi, La Civita, Evelina, Cennamo, Michele, Liotti, Antonietta, Lecce, Manuela, Russo, Gianluca, Insabato, Luigi, Imbimbo, Ciro, Terracciano, Daniela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8466029/
https://www.ncbi.nlm.nih.gov/pubmed/34572950
http://dx.doi.org/10.3390/cancers13184723
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author Ferro, Matteo
Crocetto, Felice
Bruzzese, Dario
Imbriaco, Massimo
Fusco, Ferdinando
Longo, Nicola
Napolitano, Luigi
La Civita, Evelina
Cennamo, Michele
Liotti, Antonietta
Lecce, Manuela
Russo, Gianluca
Insabato, Luigi
Imbimbo, Ciro
Terracciano, Daniela
author_facet Ferro, Matteo
Crocetto, Felice
Bruzzese, Dario
Imbriaco, Massimo
Fusco, Ferdinando
Longo, Nicola
Napolitano, Luigi
La Civita, Evelina
Cennamo, Michele
Liotti, Antonietta
Lecce, Manuela
Russo, Gianluca
Insabato, Luigi
Imbimbo, Ciro
Terracciano, Daniela
author_sort Ferro, Matteo
collection PubMed
description SIMPLE SUMMARY: In the last decades, the widespread use of PSA as the standard tool for prostate cancer diagnosis led to a high rate of overdiagnosis and overtreatment. More recently, multiparametric magnetic resonance imaging (mpMRI) became part of the diagnostic pathway, and several next-generation PSA-based tests (PHI, PHI density, 4Kscore, STHLM3) have been proposed. The multivariable approach promises to help with a better stratification of PCa patients at initial diagnosis. In this study, we evaluated the performance of the prostate health index (PHI) and mpMRI for the prediction of positive biopsy and of high-grade PCa at radical prostatectomy (RP). Our findings suggested that PHI had a better ability than mpMRI to predict positive biopsy, whereas a comparable performance in the identification of pathological aggressive PCa was pointed out. Notably, PHI and PHI density might represent useful biomarkers to recognize high-grade PCa in patients with low or uncertain PI-RADS scores on mpMRI. ABSTRACT: Widespread use of PSA as the standard tool for prostate cancer (PCa) diagnosis led to a high rate of overdiagnosis and overtreatment. In this study, we evaluated the performance of the prostate health index (PHI) and multiparametric magnetic resonance imaging (mpMRI) for the prediction of positive biopsy and of high-grade PCa at radical prostatectomy (RP). To this end, we prospectively enrolled 196 biopsy-naïve patients who underwent mpMRI. A subgroup of 116 subjects with biopsy-proven PCa underwent surgery. We found that PHI significantly outperformed both PI-RADS score (difference in AUC: 0.14; p < 0.001) and PHI density (difference in AUC: 0.08; p = 0.002) in the ability to predict positive biopsy with a cut-off value of 42.7 as the best threshold. Conversely, comparing the performance in the identification of clinically significant prostate cancer (csPCa) at RP, we found that PHI ≥ 61.68 and PI-RADS score ≥ 4 were able to identify csPCa (Gleason score ≥ 7 (3 + 4)) both alone and added to a base model including age, PSA, fPSA-to-tPSA ratio and prostate volume. In conclusion, PHI had a better ability than PI-RADS score to predict positive biopsy, whereas it had a comparable performance in the identification of pathological csPCa.
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spelling pubmed-84660292021-09-27 Prostate Health Index and Multiparametric MRI: Partners in Crime Fighting Overdiagnosis and Overtreatment in Prostate Cancer Ferro, Matteo Crocetto, Felice Bruzzese, Dario Imbriaco, Massimo Fusco, Ferdinando Longo, Nicola Napolitano, Luigi La Civita, Evelina Cennamo, Michele Liotti, Antonietta Lecce, Manuela Russo, Gianluca Insabato, Luigi Imbimbo, Ciro Terracciano, Daniela Cancers (Basel) Article SIMPLE SUMMARY: In the last decades, the widespread use of PSA as the standard tool for prostate cancer diagnosis led to a high rate of overdiagnosis and overtreatment. More recently, multiparametric magnetic resonance imaging (mpMRI) became part of the diagnostic pathway, and several next-generation PSA-based tests (PHI, PHI density, 4Kscore, STHLM3) have been proposed. The multivariable approach promises to help with a better stratification of PCa patients at initial diagnosis. In this study, we evaluated the performance of the prostate health index (PHI) and mpMRI for the prediction of positive biopsy and of high-grade PCa at radical prostatectomy (RP). Our findings suggested that PHI had a better ability than mpMRI to predict positive biopsy, whereas a comparable performance in the identification of pathological aggressive PCa was pointed out. Notably, PHI and PHI density might represent useful biomarkers to recognize high-grade PCa in patients with low or uncertain PI-RADS scores on mpMRI. ABSTRACT: Widespread use of PSA as the standard tool for prostate cancer (PCa) diagnosis led to a high rate of overdiagnosis and overtreatment. In this study, we evaluated the performance of the prostate health index (PHI) and multiparametric magnetic resonance imaging (mpMRI) for the prediction of positive biopsy and of high-grade PCa at radical prostatectomy (RP). To this end, we prospectively enrolled 196 biopsy-naïve patients who underwent mpMRI. A subgroup of 116 subjects with biopsy-proven PCa underwent surgery. We found that PHI significantly outperformed both PI-RADS score (difference in AUC: 0.14; p < 0.001) and PHI density (difference in AUC: 0.08; p = 0.002) in the ability to predict positive biopsy with a cut-off value of 42.7 as the best threshold. Conversely, comparing the performance in the identification of clinically significant prostate cancer (csPCa) at RP, we found that PHI ≥ 61.68 and PI-RADS score ≥ 4 were able to identify csPCa (Gleason score ≥ 7 (3 + 4)) both alone and added to a base model including age, PSA, fPSA-to-tPSA ratio and prostate volume. In conclusion, PHI had a better ability than PI-RADS score to predict positive biopsy, whereas it had a comparable performance in the identification of pathological csPCa. MDPI 2021-09-21 /pmc/articles/PMC8466029/ /pubmed/34572950 http://dx.doi.org/10.3390/cancers13184723 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ferro, Matteo
Crocetto, Felice
Bruzzese, Dario
Imbriaco, Massimo
Fusco, Ferdinando
Longo, Nicola
Napolitano, Luigi
La Civita, Evelina
Cennamo, Michele
Liotti, Antonietta
Lecce, Manuela
Russo, Gianluca
Insabato, Luigi
Imbimbo, Ciro
Terracciano, Daniela
Prostate Health Index and Multiparametric MRI: Partners in Crime Fighting Overdiagnosis and Overtreatment in Prostate Cancer
title Prostate Health Index and Multiparametric MRI: Partners in Crime Fighting Overdiagnosis and Overtreatment in Prostate Cancer
title_full Prostate Health Index and Multiparametric MRI: Partners in Crime Fighting Overdiagnosis and Overtreatment in Prostate Cancer
title_fullStr Prostate Health Index and Multiparametric MRI: Partners in Crime Fighting Overdiagnosis and Overtreatment in Prostate Cancer
title_full_unstemmed Prostate Health Index and Multiparametric MRI: Partners in Crime Fighting Overdiagnosis and Overtreatment in Prostate Cancer
title_short Prostate Health Index and Multiparametric MRI: Partners in Crime Fighting Overdiagnosis and Overtreatment in Prostate Cancer
title_sort prostate health index and multiparametric mri: partners in crime fighting overdiagnosis and overtreatment in prostate cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8466029/
https://www.ncbi.nlm.nih.gov/pubmed/34572950
http://dx.doi.org/10.3390/cancers13184723
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