J Cancer 2018; 9(13):2237-2248. doi:10.7150/jca.24690 This issue

Research Paper

Optimal biopsy strategy for prostate cancer detection by performing a Bayesian network meta-analysis of randomized controlled trials

Yi Wang1*, Jundong Zhu1,2*, Zhiqiang Qin1*, Yamin Wang1, Chen Chen1, Yichun Wang1, Xiang Zhou1, Qijie Zhang1, Xianghu Meng1✉, Ninghong Song1✉

1. Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
2. Current affiliation: Department of Urology, The Third Affiliated Hospital of Soochow University, Changzhou, 213000, China
* Yi Wang, Jundong Zhu and Zhiqiang Qin contributed equally to this work.

This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Wang Y, Zhu J, Qin Z, Wang Y, Chen C, Wang Y, Zhou X, Zhang Q, Meng X, Song N. Optimal biopsy strategy for prostate cancer detection by performing a Bayesian network meta-analysis of randomized controlled trials. J Cancer 2018; 9(13):2237-2248. doi:10.7150/jca.24690. Available from https://www.jcancer.org/v09p2237.htm

File import instruction


Objective: With the increasing recognition of the over-diagnosis and over-treatment of prostate cancer (PCa), the choice of a better prostate biopsy strategy had confused both the patients and clinical surgeons. Hence, this network meta-analysis was conducted to clarify this question.

Methods: In the current network meta-analysis, twenty eligible randomized controlled trials (RCTs) with 4,571 participants were comprehensively identified through Pubmed, Embase and Web of Science databases up to July 2017. The pooled odds ratio (OR) with 95% credible interval (CrI) was calculated by Markov chain Monte Carlo methods. A Bayesian network meta-analysis was conducted by using R-3.4.0 software with the help of package “gemtc” version 0.8.2.

Results: Six different PCa biopsy strategies and four clinical outcomes were ultimately analyzed in this study. Although, the efficacy of different PCa biopsy strategies by ORs with corresponding 95% CrIs had not yet reached statistical differences, the cumulative rank probability indicated that overall PCa detection rate from best to worst was FUS-GB plus TRUS-GB, FUS-GB, CEUS, MRI-GB, TRUS-GB and TPUS-GB. In terms of clinically significant PCa detection, CEUS, FUS-GB or FUS-GB plus TRUS-GB had a higher, whereas TRUS-GB or TPUS-GB had a relatively lower significant detection rate. Meanwhile, TPUS-GB or TRUS-GB had a higher insignificant PCa detection rate. As for TRUS-guided biopsy, the general trend was that the more biopsy cores, the higher overall PCa detection rate. As for targeted biopsy, it could yield a comparable or even a better effect with fewer cores, compared with traditional random biopsy.

Conclusion: Taken together, in a comprehensive consideration of four clinical outcomes, our outcomes shed light on that FUS-GB or FUS-GB plus TRUS-GB showed their superiority, compared with other puncture methods in the detection of PCa. Moreover, TPUS or TRUS-GB was more easily associated with the over-diagnosis and over-treatment of PCa. In addition, targeted biopsy was obviously more effective than traditional random biopsy. The subsequent RCTs with larger sample sizes were required to validate our findings.

Keywords: prostate cancer, prostate cancer detection, network meta-analysis, randomized controlled trials