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Abstract #81315 Published in IGR 20-3
Rapid network meta-analysis using data from Food and Drug Administration approval packages is feasible but with limitations
Wang L; Rouse B; Marks-Anglin A; Duan R; Shi Q; Quach K; Chen Y; Cameron C; Schmid CH; Li TJournal of Clinical Epidemiology 2019; 114: 84-94
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.
Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.
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