Diagnostic Performance of Multiparametric MRI for the Detection of suspected Prostate Cancer in Biopsy-Naive Patients: A Systematic Review and Meta-analysis

医学 荟萃分析 诊断优势比 接收机工作特性 前列腺癌 科克伦图书馆 诊断试验中的似然比 曲线下面积 列联表 多参数磁共振成像 子群分析 优势比 活检 内科学 放射科 癌症 统计 数学
作者
Lei Yang,Taijuan Zhang,Shunli Liu,Hui Ding,Zhiming Li,Zaixian Zhang
出处
期刊:Academic Radiology [Elsevier BV]
卷期号:32 (1): 260-274 被引量:4
标识
DOI:10.1016/j.acra.2024.08.027
摘要

Rationale and ObjectivesThis meta-analysis aimed to assess the diagnostic accuracy of multiparametric MRI (mpMRI) in detecting suspected prostate cancer (PCa) in biopsy-naive men.Materials and MethodsPubMed, Scopus, and the Cochrane Library databases were systematically searched for studies published from January 2013 to April 2024. Sixteen studies comprising 4973 patients met the inclusion criteria. Data were extracted to construct 2×2 contingency tables for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). A random-effects model was used for pooled estimation, and subgroup analyses were conducted. Summary receiver operating characteristic (SROC) curves were generated to summarize overall diagnostic performance.ResultsThe overall detection rate of PCa across studies was 57.3%. For detecting any PCa, mpMRI showed pooled sensitivity of 82% (95% CI, 80–83%) and specificity of 62% (95% CI, 60–64%), with positive likelihood ratio (LR) of 1.97 (95% CI, 1.71–2.26), negative LR of 0.28 (95% CI, 0.24–0.34), and diagnostic odds ratio (DOR) of 7.34 (95% CI, 5.60–9.63), and an area under the SROC curve of 0.81. For clinically significant PCa (csPCa), mpMRI had pooled sensitivity of 88% (95% CI, 87–90%) and specificity of 64% (95% CI, 63–66%), with positive LR of 2.49 (95% CI, 2.03–3.05), negative LR of 0.20 (95% CI, 0.16–0.25), DOR of 13.83 (95% CI, 9.14–20.9), and area under the curve of 0.90.ConclusionThis meta-analysis suggests that mpMRI is effective in detecting PCa in biopsy-naive patients, particularly for csPCa. It can help reduce unnecessary biopsies and lower the risk of missing clinically significant cases, thereby guiding informed biopsy decisions.
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