Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Seoul, Republic of Korea.
J Digit Imaging. 2020 Jun;33(3):586-594. doi: 10.1007/s10278-019-00312-1.
The aim of this study was to test an interactive up-to-date meta-analysis (iu-ma) of studies on MRI in the management of men with suspected prostate cancer. Based on the findings of recently published systematic reviews and meta-analyses, two freely accessible dynamic meta-analyses (https://iu-ma.org) were designed using the programming language R in combination with the package "shiny." The first iu-ma compares the performance of the MRI-stratified pathway and the systematic transrectal ultrasound-guided biopsy pathway for the detection of clinically significant prostate cancer, while the second iu-ma focuses on the use of biparametric versus multiparametric MRI for the diagnosis of prostate cancer. Our iu-mas allow for the effortless addition of new studies and data, thereby enabling physicians to keep track of the most recent scientific developments without having to resort to classical static meta-analyses that may become outdated in a short period of time. Furthermore, the iu-mas enable in-depth subgroup analyses by a wide variety of selectable parameters. Such an analysis is not only tailored to the needs of the reader but is also far more comprehensive than a classical meta-analysis. In that respect, following multiple subgroup analyses, we found that even for various subgroups, detection rates of prostate cancer are not different between biparametric and multiparametric MRI. Secondly, we could confirm the favorable influence of MRI biopsy stratification for multiple clinical scenarios. For the future, we envisage the use of this technology in addressing further clinical questions of other organ systems.
本研究旨在测试一种交互式最新荟萃分析(iu-ma),以评估 MRI 在疑似前列腺癌男性管理中的作用。基于最近发表的系统评价和荟萃分析的结果,我们使用编程语言 R 和“shiny”包设计了两个免费的动态荟萃分析(https://iu-ma.org)。第一个 iu-ma 比较了 MRI 分层路径和系统经直肠超声引导活检路径在检测临床显著前列腺癌方面的性能,而第二个 iu-ma 则侧重于使用双参数与多参数 MRI 进行前列腺癌诊断。我们的 iu-ma 允许轻松添加新的研究和数据,从而使医生能够跟踪最新的科学发展,而无需依赖可能在短时间内过时的经典静态荟萃分析。此外,iu-ma 可以通过各种可选参数进行深入的亚组分析。这种分析不仅符合读者的需求,而且比经典的荟萃分析更全面。在这方面,我们进行了多次亚组分析后发现,即使对于各种亚组,双参数与多参数 MRI 的前列腺癌检出率也没有差异。其次,我们可以确认 MRI 活检分层对多种临床情况的有利影响。未来,我们设想将这项技术用于解决其他器官系统的进一步临床问题。