Abstract | October 2019
Objective: To test rapid approaches that use Drugs@FDA (a public database of approved drugs) and ClinicalTrials.gov to identify trials and to compare these two sources with bibliographic databases as an evidence base for a systematic review and network meta-analysis (NMA).
Study design and setting: We searched bibliographic databases, Drugs@FDA, and ClinicalTrials.gov for eligible trials on first-line glaucoma medications. We extracted data, assessed risk of bias, and examined the completeness and consistency of information provided by different sources. We fitted random-effects NMA models separately for trials identified from each source and for all unique trials from three sources.
Results: We identified 138 unique trials including 29,394 participants on 15 first-line glaucoma medications. For a given trial, information reported was sometimes inconsistent across data sources. Journal articles provided the most information needed for a systematic review; trial registrations provided the least. Compared to an NMA including all unique trials, we were able to generate reasonably precise effect estimates and similar relative rankings for available interventions using trials from Drugs@FDA alone (but not ClinicalTrials.gov).
Conclusions: A rapid NMA approach using data from Drugs@FDA is feasible but has its own limitations. Reporting of trial design and results can be improved in both the drug approval packages and on ClinicalTrials.gov.
Funding This work was supported by the Agency for Healthcare Research and Quality [grant number 1R03HS024788–01). Arielle Marks-Anglin, Rui Duan and Yong Chen are also supported in part by grants 1R01LM012607, 1R01AI130460, P50MH113840, R01AI116794, and 7R01LM009012 from the National Institutes of Health.
Citation Wang L, Rouse B, Marks-Anglin A, Duan R, Shi Q, Quach K, Chen Y, Cameron C, Schmid CH, Li T. Rapid network meta-analysis using data from Food and Drug Administration approval packages is feasible but with limitations. J Clin Epidemiol. 2019 Oct;114:84-94. doi: 10.1016/j.jclinepi.2019.06.010. Epub 2019 Jun 18. PMID: 31226413; PMCID: PMC6773505.
