Prospective Validation Study of a Novel Integrated Pathway Based on Clinical Features, Magnetic Resonance Imaging Biomarkers, and MicroRNAs for Early Detection of Prostate Cancer.

Decision curve analysis Early diagnosis Magnetic resonance imaging MicroRNA Prostate cancer

Journal

European urology oncology
ISSN: 2588-9311
Titre abrégé: Eur Urol Oncol
Pays: Netherlands
ID NLM: 101724904

Informations de publication

Date de publication:
01 Jun 2023
Historique:
received: 23 12 2022
revised: 03 05 2023
accepted: 19 05 2023
medline: 4 6 2023
pubmed: 4 6 2023
entrez: 3 6 2023
Statut: aheadofprint

Résumé

Prostate cancer (PCa) is the most diagnosed cancer in men, with an increasing need to integrate noninvasive imaging and circulating microRNAs beyond prostate-specific antigen for screening and early detection. To validate magnetic resonance imaging (MRI) biomarkers and circulating microRNAs as triage tests for patients directed to prostate biopsy, and to test different diagnostic pathways to compare their performance on patients' outcome, in terms of unnecessary biopsy avoidance. A prospective single-center cohort study, enrolling patients with PCa suspicion who underwent MRI, MRI-directed fusion biopsy (MRDB), and circulating microRNAs, was conducted. A network-based analysis was used to identify MRI biomarkers and microRNA drivers of clinically significant PCa. MRI, MRDB, and blood sampling. The decision curve analysis was exploited to assess the performance of the proposed diagnostic pathways and to quantify their benefit in terms of biopsy avoidance. Overall, 261 men were enrolled and underwent MRDB for PCa detection. A total of 178 patients represented the entire cohort: 55 (30.9%) were negative for PCa, 39 (21.9%) had grade group (GG) 1 PCa, and 84 (47.2%) had GG >1 PCa. The proposed integrated pathway, including clinical data, MRI biomarkers, and microRNAs, provided the best net benefit with a biopsy avoidance rate of about 20% at a low disease probability. The main limitation is the monocentric design in a referral center. The integrated pathway represents a validated model that sees MRI biomarkers and microRNAs as a prebiopsy triage of patients at a risk for clinically significant PCa. The proposed pathway showed the highest net benefit in terms of unnecessary biopsy avoidance. The proposed integrated pathway for early detection of prostate cancer (PCa) allows accurate patient allocation to biopsy and patients' stratification into risk group categories, reducing overdiagnosis and overtreatment of clinically insignificant PCa.

Sections du résumé

BACKGROUND BACKGROUND
Prostate cancer (PCa) is the most diagnosed cancer in men, with an increasing need to integrate noninvasive imaging and circulating microRNAs beyond prostate-specific antigen for screening and early detection.
OBJECTIVE OBJECTIVE
To validate magnetic resonance imaging (MRI) biomarkers and circulating microRNAs as triage tests for patients directed to prostate biopsy, and to test different diagnostic pathways to compare their performance on patients' outcome, in terms of unnecessary biopsy avoidance.
DESIGN, SETTING, AND PARTICIPANTS METHODS
A prospective single-center cohort study, enrolling patients with PCa suspicion who underwent MRI, MRI-directed fusion biopsy (MRDB), and circulating microRNAs, was conducted. A network-based analysis was used to identify MRI biomarkers and microRNA drivers of clinically significant PCa.
INTERVENTION METHODS
MRI, MRDB, and blood sampling.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS METHODS
The decision curve analysis was exploited to assess the performance of the proposed diagnostic pathways and to quantify their benefit in terms of biopsy avoidance.
RESULTS AND LIMITATIONS CONCLUSIONS
Overall, 261 men were enrolled and underwent MRDB for PCa detection. A total of 178 patients represented the entire cohort: 55 (30.9%) were negative for PCa, 39 (21.9%) had grade group (GG) 1 PCa, and 84 (47.2%) had GG >1 PCa. The proposed integrated pathway, including clinical data, MRI biomarkers, and microRNAs, provided the best net benefit with a biopsy avoidance rate of about 20% at a low disease probability. The main limitation is the monocentric design in a referral center.
CONCLUSIONS CONCLUSIONS
The integrated pathway represents a validated model that sees MRI biomarkers and microRNAs as a prebiopsy triage of patients at a risk for clinically significant PCa. The proposed pathway showed the highest net benefit in terms of unnecessary biopsy avoidance.
PATIENT SUMMARY RESULTS
The proposed integrated pathway for early detection of prostate cancer (PCa) allows accurate patient allocation to biopsy and patients' stratification into risk group categories, reducing overdiagnosis and overtreatment of clinically insignificant PCa.

Identifiants

pubmed: 37270379
pii: S2588-9311(23)00108-6
doi: 10.1016/j.euo.2023.05.008
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2023 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Auteurs

Martina Pecoraro (M)

Department of Radiological Sciences, Oncology and Pathology, Sapienza University, Policlinico Umberto I, Rome, Italy.

Giuseppina Catanzaro (G)

Department of Experimental Medicine, Sapienza University, Policlinico Umberto I, Rome, Italy.

Federica Conte (F)

Institute for Systems Analysis and Computer Science "A. Ruberti" (IASI), National Research Council (CNR), Rome, Italy.

Zein Mersini Besharat (ZM)

Department of Experimental Medicine, Sapienza University, Policlinico Umberto I, Rome, Italy.

Emanuele Messina (E)

Department of Radiological Sciences, Oncology and Pathology, Sapienza University, Policlinico Umberto I, Rome, Italy.

Ludovica Laschena (L)

Department of Radiological Sciences, Oncology and Pathology, Sapienza University, Policlinico Umberto I, Rome, Italy.

Sofia Trocchianesi (S)

Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.

Elena Splendiani (E)

Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.

Alessandro Sciarra (A)

Department of Maternal Infant and Urologic Sciences, Sapienza University of Rome, Rome, Italy.

Carlo Catalano (C)

Department of Radiological Sciences, Oncology and Pathology, Sapienza University, Policlinico Umberto I, Rome, Italy.

Paola Paci (P)

Department of Computer, Control and Management Engineering, Sapienza University, Rome, Italy.

Elisabetta Ferretti (E)

Department of Experimental Medicine, Sapienza University, Policlinico Umberto I, Rome, Italy.

Valeria Panebianco (V)

Department of Radiological Sciences, Oncology and Pathology, Sapienza University, Policlinico Umberto I, Rome, Italy. Electronic address: Valeria.panebianco@uniroma1.it.

Classifications MeSH