Diagnosis accuracy of PCA3 level in patients with prostate cancer: a systematic review with meta-analysis

Abstract

Background: 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.

Materials and methods: 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.

Results: 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.

Conclusions: 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.

Keywords: Meta-Analysis [Publication Type]; Prostate cancer, familial [Supplementary Concept]; prostate cancer antigen 3, human [Supplementary Concept].

Figure 1. Flowchart of literature search and selection process.

Figure 2. Flowchart of literature search and selection process.

Figure 3. Forest plots of summary diagnostic odds ratio of by PCA3 as a diagnostic marker for PCa in this meta-analysis. Each solid circle represents an eligible study. The size of solid circle reflects the sample size of each eligible study. Error bars represent 95% CIs.

Figure 4. Summary receiver operating characteristic curves of PCA3 for the diagnosis of PCa. Each solid circle represents an eligible study. The size of solid circle represents the sample size of each eligible study. The overall diagnostic efficiency is summarized by the regression curve.

Figure 5. Linear regression test of funnel plot asymmetry. The statistically non-significant P value of the slop coefficient indicates symmetry of the data and a low likelihood of publication bias.