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Duplicated network meta-analysis in advanced prostate cancer: a case study and recommendations for change.

Authors :
Fisher, David J.
Burdett, Sarah
Vale, Claire
White, Ian R.
Tierney, Jayne F.
Source :
Systematic Reviews; 12/16/2022, Vol. 11 Issue 1, p1-11, 11p
Publication Year :
2022

Abstract

Background: Research overlap and duplication is a recognised problem in the context of both pairwise and network systematic reviews and meta-analyses. As a case study, we carried out a scoping review to identify and examine duplicated network meta-analyses (NMAs) in a specific disease setting where several novel therapies have recently emerged: hormone-sensitive metastatic prostate cancer (mHSPC). Methods: MEDLINE and EMBASE were systematically searched, in January 2020, for indirect or mixed treatment comparisons or network meta-analyses of the systemic treatments docetaxel and abiraterone acetate in the mHSPC setting, with a time-to-event outcome reported on the hazard-ratio scale. Eligibility decisions were made, and data extraction performed, by two independent reviewers. Results: A total of 13 eligible reviews were identified, analysing between 3 and 8 randomised comparisons, and comprising between 1773 and 7844 individual patients. Although the included trials and treatments showed a high degree of overlap, we observed considerable variation between identified reviews in terms of review aims, eligibility criteria and included data, statistical methodology, reporting and inference. Furthermore, crucial methodological details and specific source data were often unclear. Conclusions and recommendations: Variation across duplicated NMAs, together with reporting inadequacies, may compromise identification of best-performing treatments. Particularly in fast-moving fields, review authors should be aware of all relevant studies, and of other reviews with potential for overlap or duplication. We recommend that review protocols be published in advance, with greater clarity regarding the specific aims or scope of the project, and that reports include information on how the work builds upon existing knowledge. Source data and results should be clearly and completely presented to allow unbiased interpretation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20464053
Volume :
11
Issue :
1
Database :
Complementary Index
Journal :
Systematic Reviews
Publication Type :
Academic Journal
Accession number :
160839481
Full Text :
https://doi.org/10.1186/s13643-022-02137-6