445-P: Network Meta-analysis of Seven Glucagon-Like Peptide-1 Receptor Agonists: A Focus on Cardiovascular Outcome Trials Data

Objective: To indirectly compare glucagon like peptide-1 receptor agonists (GLP-1RA) cardiovascular outcome trials (CVOTs) using network meta-analysis (NMA). Methods: We searched Medline to retrieve CVOTs that involved GLP-1RA. We conducted NMAs using binomial likelihood logit link model for the following outcomes: CV death, myocardial infarction (IM), stroke, and death from any cause. After running both fixed effects and random effects models for each outcome, we identified the best fit model that has the smallest deviance information and the average posterior residual deviance. We followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA-NMA) in reporting this NMA. Results: After screening, a total of seven GLP-1RA CVOTs were included. The NMA results showed that oral semaglutide was statistically better than exenatide (HR 0.47, CI: 0.21-0.99), dulaglutide (HR 0.46, CI: 0.20-0.97), albiglutide (HR 0.45, CI: 0.19-0.97), and lixisenatide (HR 0.43, CI: 0.19-0.92) in reducing CV death events. No significant differences were detected between most of the treatments regarding reducing death from any cause, MI and stroke events. The ranking results showed that oral semaglutide had the highest probability to be ranked first (>90%) in reducing CV death and death from any cause. Moreover, once weekly semaglutide had the highest probability to be ranked first in reducing MI and stroke events. Conclusion: The indirect comparison of GLP-1RAs using CVOTs data showed that oral semaglutide is preferred over most of the GLP-1RAs in reducing CV death and death from any cause events. The ranking probability showed that once weekly semaglutide and oral semaglutide are the most likely to be ranked first in reducing the outcomes of interest.