| Literature DB >> 31898035 |
Anton S Becker1, Julian Kirchner2, Thomas Sartoretti2, Soleen Ghafoor2, Sungmin Woo2, Chong Hyun Suh3, Joseph P Erinjeri2, Hedvig Hricak2, H Alberto Vargas2.
Abstract
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of the most recent scientific developments without having to resort to classical static meta-analyses that may become outdated in a short period of time.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.Entities:
Keywords: Evidence-based medicine; Magnetic resonance imaging; Meta-analysis; Prostate cancer; Radiology
Year: 2020 PMID: 31898035 PMCID: PMC7256175 DOI: 10.1007/s10278-019-00312-1
Source DB: PubMed Journal: J Digit Imaging ISSN: 0897-1889 Impact factor: 4.056