Effects of residual risk–targeted therapies on coronary plaque regression: a network meta-analysis of 40 studies
M Galli, S Benenati, F Gurgoglione, G Benatti, G Occhipinti, M Russo, R Vergallo, D D'Amario, S Sciarretta, G Frati, E Ernesto, I Porto, G Niccoli, F CreaAbstract
Background
New therapies targeting different residual risk pathways have been shown to reduce recurrent events in patients with coronary artery disease (CAD). Plaque regression has been proposed as one mechanism underlying these benefits, but the comparative effects of these strategies on plaque regression remain unclear.
Purpose
To evaluate the comparative effects of different residual risk–targeted therapies, added to statin treatment, on coronary plaque regression as assessed by intracoronary imaging (intravascular ultrasound [IVUS] or optical coherence tomography [OCT]) or coronary computed tomography angiography (CCTA).
Methods
Randomized controlled trials (RCTs) and observational studies evaluating the effects of residual risk–targeted therapies, added to statin treatment, on coronary plaque regression assessed by intracoronary imaging (IVUS or OCT) or CCTA were included. A frequentist network meta-analysis was performed to estimate mean differences (MDs). The primary outcome was total atheroma volume (TAV), and the secondary outcome was percent atheroma volume (PAV). Additional analyses included a sensitivity analysis excluding studies not using high-intensity statin therapy and a subgroup analysis stratified by diabetes mellitus status (yes vs no). Statin-only therapy served as the comparator. Treatment strategies were ranked using P-scores, ranging from 0 (worst performance) to 1 (best performance).
Results
A total of 30 RCTs and 10 observational studies testing 7 treatment strategies (i.e., ezetimibe, eicosapentaenoic acid [EPA], glucagon-like peptide-1 receptor agonists [GLP-1 RAs], icosapent ethyl [IPE], proprotein convertase subtilisin/kexin type 9 inhibitors [PCSK9i], polyunsaturated fatty acids [PUFA], colchicine and sodium–glucose cotransporter 2 inhibitors [SGLT2i]) were included in the network (Figure 1). Mean follow-up was 19 weeks. Compared with statin-only therapy, the greatest reduction in TAV was observed with IPE (MD -77.50; 95% CI -302.47; 147.47) followed by SGLT2i (MD -26.29; 95% CI -79.36; 26.78), PCSK9i (MD -17.90; 95% CI -29.66; -6.13) and colchicine (MD -15.90; 95% CI -52.02; 20.22), while other agents showed limited effects (ezetimibe = -4.53, PUFA = -0.87, GLP-1 RAs = 39.30)(Figure 2). Treatment ranking showed that PCSK9i (P-score = 0.739), IPE (P-score = 0.735), and SGLT2i (P-score = 0.717) performed best for TAV regression. Results were consistent across secondary analyses. For PAV, the greatest reductions were observed with SGLT2i and EPA, followed by PCSK9i, ezetimibe, and GLP-1 RAs.
Conclusion
Among patients with coronary artery disease receiving residual risk–targeted therapies on top of statin treatment, PCSK9i, IPE, and SGLT2i, were associated with the greatest degrees of plaque regression.Figure 1Figure 2