Development and validation of a clinical decision support system based on PSA, microRNAs, and MRI for the detection of prostate cancer

医学 前列腺癌 神经组阅片室 介入放射学 放射科 医学物理学 癌症检测 前列腺 磁共振成像 癌症 超声波 肿瘤科 内科学 神经学 精神科
作者
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,F. Porpiglia,Daniele Regge,Valentina Giannini
出处
期刊:European Radiology [Springer Science+Business Media]
卷期号:34 (8): 5108-5117 被引量:1
标识
DOI:10.1007/s00330-023-10542-1
摘要

Abstract Objectives 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. Methods 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. Results 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. Conclusion 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. Clinical relevance statement 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. Key Points • 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.
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