A Bayesian network meta-analysis of PCSK9 inhibitors, statins and ezetimibe with or without statins for cardiovascular outcomes

Abstract

Background The comparative effects of statins, ezetimibe with or without statins and proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitors remain unassessed. Design Bayesian network meta-analysis was conducted to compare treatment groups. Methods Thirty-nine randomized controlled trials were selected using MEDLINE, EMBASE, and CENTRAL (inception – September 2017). Results In network meta-analysis of 189,116 patients, PCSK9 inhibitors were ranked as the best treatment for prevention of major adverse cardiovascular events (Surface Under Cumulative Ranking Curve (SUCRA), 85%), myocardial infarction (SUCRA, 84%) and stroke (SUCRA, 80%). PCSK9 inhibitors reduced the risk of major adverse cardiovascular events compared with ezetimibe + statin (odds ratio (OR): 0.72; 95% credible interval (CrI), 0.55–0.95; Grading of Recommendation Assessment, Development and Evaluation (GRADE) criteria: moderate), statin (OR: 0.78; 95% CrI: 0.62–0.97; GRADE: moderate) and placebo (OR: 0.63; 95% CrI: 0.49–0.79; GRADE: high). The PCSK9 inhibitors were consistently superior to groups for major adverse cardiovascular event reduction in secondary prevention trials (SUCRA, 95%). Statins had the highest probability of having lowest rates of all-cause mortality (SUCRA, 82%) and cardiovascular mortality (SUCRA, 84%). Compared with placebo, statins reduced the risk of all-cause mortality (OR: 0.88; 95% CrI: 0.83–0.94; GRADE: moderate) and cardiovascular mortality (OR: 0.84; 95% CrI: 0.77–0.90; GRADE: high). For cardiovascular mortality, PCSK9 inhibitors were ranked as the second best treatment (SUCRA, 78%) followed by ezetimibe + statin (SUCRA, 50%). Conclusion PCSK9 inhibitors were ranked as the most effective treatment for reducing major adverse cardiovascular events, myocardial infarction and stroke, without having major safety concerns. Statins were ranked as the most effective therapy for reducing mortality.