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. 2020 Mar 20;10(1):5157.
doi: 10.1038/s41598-020-62015-w.

Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone

Affiliations

Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone

Junxiao Liu et al. Sci Rep. .

Abstract

The gold standard for prostate cancer (PCa) diagnosis is prostate biopsy. However, it remines controversial as an invasive mean for patients with PSA levels in the gray zone (4-10 ng/mL). This study aimed to develop strategy to reduce the unnecessary prostate biopsy. We retrospectively identified 235 patients with serum total PSA testing in the gray zone before prostate biopsy between 2014 and 2018. Age, PSA derivates, prostate volume and multiparametric magnetic imaging (mpMRI) examination were assessed as predictors for PCa and clinically significant PCa with Gleason score ≥ 7 (CSPCa). Univariate analysis showed that prostate volume, PSAD, and mpMRI examination were significant predictors of PCa and CSPCa (P < 0.05). The differences of diagnostic accuracy between mpMRI examination (AUC = 0.69) and other clinical parameters in diagnostic accuracy for PCa were not statistically significant. However, mpMRI examination (AUC = 0.79) outperformed prostate volume and PSAD in diagnosis of CSPCa. The multivariate models (AUC = 0.79 and 0.84 for PCa and CSPCa) performed significantly better than mpMRI examination for detection of PCa (P = 0.003) and CSPCa (P = 0.036) among patients with PSA level in the gray zone. At the same level of sensitivity as the mpMRI examination to diagnose PCa, applying the multivariate models could reduce the number of biopsies by 5% compared with mpMRI examination. Overall, our results supported the view that the multivariate model could reduce unnecessary biopsies without compromising the ability to diagnose PCa and CSPCa. Further prospective validation is required.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
The comparison between mpMRI examination and the multivariate model in diagnostic efficacy.

References

    1. Moore CM, et al. Reporting Magnetic Resonance Imaging in Men on Active Surveillance for Prostate Cancer: The PRECISE Recommendations-A Report of a European School of Oncology Task Force. European urology. 2017;71:648–655. doi: 10.1016/j.eururo.2016.06.011. - DOI - PubMed
    1. Ye D, Zhu Y. Epidemiology of prostate cancer in China: an overview and clinical implication. Zhonghua wai ke za zhi [Chinese journal of surgery] 2015;53:249–252. - PubMed
    1. Zhang Yi-Yan, Li Qin, Xin Yi, Lv Wei-Qi. Differentiating Prostate Cancer from Benign Prostatic Hyperplasia Using PSAD Based on Machine Learning: Single-Center Retrospective Study in China. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2019;16(3):936–941. doi: 10.1109/TCBB.2018.2822675. - DOI - PubMed
    1. Xia J, et al. Effects of screening on radical prostatectomy efficacy: the prostate cancer intervention versus observation trial. Journal of the National Cancer Institute. 2013;105:546–550. doi: 10.1093/jnci/djt017. - DOI - PMC - PubMed
    1. European Association of Urology. EAU guidelines on prostate cancer, https://uroweb.org/guideline/prostate-cancer/ (2019).

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