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.
European urology oncology. 2023 Jun 01 [Epub ahead of print]
Martina Pecoraro, Giuseppina Catanzaro, Federica Conte, Zein Mersini Besharat, Emanuele Messina, Ludovica Laschena, Sofia Trocchianesi, Elena Splendiani, Alessandro Sciarra, Carlo Catalano, Paola Paci, Elisabetta Ferretti, Valeria Panebianco
Department of Radiological Sciences, Oncology and Pathology, Sapienza University, Policlinico Umberto I, Rome, Italy., Department of Experimental Medicine, Sapienza University, Policlinico Umberto I, Rome, Italy., Institute for Systems Analysis and Computer Science "A. Ruberti" (IASI), National Research Council (CNR), Rome, Italy., Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy., Department of Maternal Infant and Urologic Sciences, Sapienza University of Rome, Rome, Italy., Department of Computer, Control and Management Engineering, Sapienza University, Rome, Italy., Department of Radiological Sciences, Oncology and Pathology, Sapienza University, Policlinico Umberto I, Rome, Italy. Electronic address: .
PubMed http://www.ncbi.nlm.nih.gov/pubmed/37270379
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