The aims of this study are to develop and validate a clinical decision support system based on demographics, prostate-specific antigen (PSA), microRNA (miRNA), and MRI for the detection of prostate cancer (PCa) and clinical significant (cs) PCa, and to assess if this system performs better compared to MRI alone.
This retrospective, multicenter, observational study included 222 patients (mean age 66, range 46-75 years) who underwent prostate MRI, miRNA (let-7a-5p and miR-103a-3p) assessment, and biopsy. Monoparametric and multiparametric models including age, PSA, miRNA, and MRI outcome were trained on 65% of the data and then validated on the remaining 35% to predict both PCa (any Gleason grade [GG]) and csPCa (GG ≥ 2 vs GG = 1/negative). Accuracy, sensitivity, specificity, positive and negative predictive value (NPV), and area under the receiver operating characteristic curve were calculated.
MRI outcome was the best predictor in the monoparametric model for both detection of PCa, with sensitivity of 90% (95%CI 73-98%) and NPV of 93% (95%CI 82-98%), and for csPCa identification, with sensitivity of 91% (95%CI 72-99%) and NPV of 95% (95%CI 84-99%). Sensitivity and NPV of PSA + miRNA for the detection of csPCa were not statistically different from the other models including MRI alone.
MRI stand-alone yielded the best prediction models for both PCa and csPCa detection in biopsy-naïve patients. The use of miRNAs let-7a-5p and miR-103a-3p did not improve classification performances compared to MRI stand-alone results.
The use of miRNA (let-7a-5p and miR-103a-3p), PSA, and MRI in a clinical decision support system (CDSS) does not improve MRI stand-alone performance in the detection of PCa and csPCa.
• Clinical decision support systems including MRI improve the detection of both prostate cancer and clinically significant prostate cancer with respect to PSA test and/or microRNA. • The use of miRNAs let-7a-5p and miR-103a-3p did not significantly improve MRI stand-alone performance. • Results of this study were in line with previous works on MRI and microRNA.
European radiology. 2024 Jan 04 [Epub ahead of print]
Simone Mazzetti, Arianna Defeudis, Giulia Nicoletti, Giovanna Chiorino, Stefano De Luca, Riccardo Faletti, Marco Gatti, Paolo Gontero, Matteo Manfredi, Maurizia Mello-Grand, Caterina Peraldo-Neia, Andrea Zitella, Francesco Porpiglia, Daniele Regge, Valentina Giannini
Radiology Unit, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy., Radiology Unit, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy. ., Department of Surgical Sciences, University of Turin, Turin, Italy., Cancer Genomics Lab, Fondazione Edo ed Elvo Tempia, Biella, Italy., Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy., Radiology Unit, Department of Surgical Sciences, University of Turin, Turin, Italy., Division of Urology, Department of Surgical Sciences, University of Turin, Turin, Italy.