Department of Urology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Department of Urology, Huzhou first people's hospital, Huzhou, China.
Int Braz J Urol. 2020 Sep-Oct;46(5):691-704. doi: 10.1590/S1677-5538.IBJU.2019.0360.
The diagnostic value and suitability of prostate cancer antigen 3 (PCA3) for the detection of prostate cancer (PCa) have been inconsistent in previous studies. Thus, the aim of the present meta-analysis was performed to systematically evaluate the diagnostic value of PCA3 for PCa.
A meta-analysis was performed to search relevant studies using online databases EMBASE, PubMed and Web of Science published until February 1st, 2019. Ultimately, 65 studies met the inclusion criteria for this meta-analysis with 8.139 cases and 14.116 controls. The sensitivity, specificity, positive likelihood ratios (LR+), negative likelihood ratios (LR-), and other measures of PCA3 were pooled and determined to evaluate the diagnostic rate of PCa by the random-effect model.
With PCA3, the pooled overall diagnostic sensitivity, specificity, LR+, LR-, and 95% confidence intervals (CIs) for predicting significant PCa were 0.68 (0.64-0.72), 0.72 (0.68-0.75), 2.41 (2.16-2.69), 0.44 (0.40-0.49), respectively. Besides, the summary diagnostic odds ratio (DOR) and 95% CIs for PCA3 was 5.44 (4.53-6.53). In addition, the area under summary receiver operating characteristic (sROC) curves and 95% CIs was 0.76 (0.72-0.79). The major design deficiencies of included studies were differential verification bias, and a lack of clear inclusion and exclusion criteria.
The results of this meta-analysis suggested that PCA3 was a non-invasive method with the acceptable sensitivity and specificity in the diagnosis of PCa, to distinguish between patients and healthy individuals. To validate the potential applicability of PCA3 in the diagnosis of PCa, more rigorous studies were needed to confirm these conclusions.
前列腺癌抗原 3（PCA3）在前列腺癌（PCa）检测中的诊断价值和适用性在之前的研究中并不一致。因此，本荟萃分析的目的是系统评估 PCA3 对 PCa 的诊断价值。
使用在线数据库 EMBASE、PubMed 和 Web of Science 进行荟萃分析，检索截至 2019 年 2 月 1 日发表的相关研究。最终，有 65 项研究符合本荟萃分析的纳入标准，共纳入 8139 例病例和 14116 例对照。采用随机效应模型汇总并确定 PCA3 的灵敏度、特异性、阳性似然比（LR+）、阴性似然比（LR-）等指标，以评估 PCa 的诊断率。
使用 PCA3 时，预测有意义的 PCa 的汇总总体诊断敏感性、特异性、LR+、LR-和 95%置信区间（CI）分别为 0.68（0.64-0.72）、0.72（0.68-0.75）、2.41（2.16-2.69）、0.44（0.40-0.49）。此外，PCA3 的汇总诊断优势比（DOR）和 95%CI 为 5.44（4.53-6.53）。此外，汇总受试者工作特征（sROC）曲线下面积和 95%CI 为 0.76（0.72-0.79）。纳入研究的主要设计缺陷是差异验证偏倚，并且缺乏明确的纳入和排除标准。
本荟萃分析的结果表明，PCA3 是一种非侵入性方法，在诊断 PCa 方面具有可接受的敏感性和特异性，可区分患者和健康个体。为了验证 PCA3 在诊断 PCa 中的潜在适用性，需要进行更严格的研究来证实这些结论。
