Key findings
To allow a more granular analysis of the effect of semaglutide on MACE and its relation to baseline CV risk, a continuous CV risk prediction model was developed using data from a liraglutide CVOT (LEADER). This CV risk prediction model was used to distribute subjects by baseline CV risk in a pooled dataset including data for both s.c. and oral semaglutide. The CV risk prediction model predicted the risk of CV outcomes observed in the semaglutide trials fairly well, validating the selection of the LEADER model for this analysis.
The results showed that there was a reduced relative and absolute risk of MACE with semaglutide vs comparators across the spectrum of baseline CV risk scores. While relative risk reductions are typically independent of baseline risk in the population and absolute risk reductions are dependent on this, our data may also indicate some effect of baseline CV risk on relative risk reduction. Similar findings were also obtained for the individual MACE components when data were analyzed with only placebo as a comparator and when the results were analyzed by trial type. The results of the placebo sensitivity analysis were to be expected, because the majority of subjects receiving comparators (59%) were randomized to placebo rather than active comparators in the included trials.
Although the absolute risk reduction was small, there was a trend (p = 0.06) towards the largest relative risk reduction occurring in those with lowest CV risk. The explanatory mechanism underlying this observation is unclear. It could be hypothesized that more advanced disease may be more resistant (or very high-risk groups more non-responsive) to the beneficial effects of GLP-1 receptor agonists on CV outcomes.
Findings in context of the broader literature
Our results are consistent overall with a post hoc analysis of pooled SUSTAIN and PIONEER data, which also showed that the effect of semaglutide vs comparators on MACE was largely consistent across different CV subgroups [
35]. Furthermore, a meta-analysis including CVOTs for all GLP-1 receptor agonists found no significant heterogeneity in the effect of these therapies in subgroups with a history of CVD vs those with no history of CVD [
36]. Although there were no significant subgroup interactions in the meta-analysis, there was a numerically lower risk of MACE in subjects with a history of CVD (−14%, hazard ratio 0.86) vs those without such a history (−6%, hazard ratio 0.94) [
36]. The HARMONY Outcomes CVOT (which only included subjects with established CVD) similarly showed a 22% CV risk reduction with albiglutide vs placebo (hazard ratio 0.78) [
37], and the REWIND CVOT showed an identical 13% effect size across subgroups with and without established CVD (hazard ratio 0.87) [
38]. Taken together, these findings are counter to the suggestion that there is a greater relative CV benefit of GLP-1 receptor agonists in subjects at lower CV risk. Therefore, we believe the totality of data for GLP-1 receptor agonists indicates similar relative risk reduction effects across a broad continuum of baseline CV risk.
While the analysis presented here was not designed to assess the mechanisms by which semaglutide reduces CV risk, previous studies have revealed several potential beneficial effects. In an animal model of acute inflammation, semaglutide decreased levels of plasma markers of systemic inflammation and down-regulated multiple inflammatory pathways vs controls, and was associated with significant attenuation of plaque lesion development [
39]. In clinical trials, semaglutide has provided clinically relevant reductions in CV risk factors such as excess body weight [
8‐
30]. Weight loss with s.c. semaglutide was shown to be of a similar or greater magnitude compared with liraglutide 3.0 mg [
40], and possibly more rapid – potentially as a result of the higher albumin affinity of semaglutide compared with liraglutide [
41]. Furthermore, in subjects receiving liraglutide for an average of 4 years, switching to s.c. semaglutide has been shown to provide further reductions in HbA
1c [
42]. Clinical trials have also demonstrated a beneficial effect of semaglutide on CV outcomes. In SUSTAIN 6, in addition to significantly reducing the risk of the primary outcome (3-point MACE: CV death, non-fatal stroke, non-fatal myocardial infarction), s.c. semaglutide significantly decreased the incidence of new or worsening nephropathy and of non-fatal stroke vs placebo [
13]—the latter being a finding that has not been observed in CVOTs with other GLP-1 receptor agonists [
43]. Nevertheless, it should be noted that a higher risk of diabetic retinopathy complications was observed with s.c. semaglutide vs placebo in SUSTAIN 6—a finding possibly related to the rapid initial reduction in HbA
1c with this GLP-1 receptor agonist [
44]. A post hoc analysis of SUSTAIN 6 showed that the beneficial effect of s.c semaglutide vs placebo on MACE was not dependent on the gender, age or baseline CV risk profile of subjects [
45].
Our findings with semaglutide are based on a CV risk prediction model derived from data from the LEADER CVOT; LEADER had common adjudicated endpoints, shared baseline variables and similar inclusion criteria, and evaluated a similar T2D population, to those included in the semaglutide trials. In line with this, when the CV risk prediction model was applied to the semaglutide dataset it performed satisfactorily, both overall and when applied only to data from the glycemic efficacy trials, validating the utility of the LEADER model for this analysis.
There are other risk models in the literature that could have been candidates for this analysis. However, each has limitations that made them less suited for our analyses compared with the CV risk prediction model developed using the LEADER data. The Framingham [
46,
47] and SCORE [
48] models were not used because they did not include patients with established CVD, which constituted the majority of subjects in the CVOTs in our analysis, as prior CVD is generally considered to be an important risk factor for new events [
49]. Furthermore, an evaluation of the risk equations of models for CV risk (including Framingham and SCORE) has reported that these models do not provide reliable estimates of CV risk in patients with T2D [
50]. The DIAL model was considered for use in our analysis, as it was developed with data from patients both with and without established CVD (19% and 81%, respectively) [
51]. However, this was a community-based study and the translatability to a clinical trial population with adjudicated endpoints would be uncertain [
51]. In addition, DIAL had a considerably longer follow-up time than LEADER (only 5- and 10-year predictions could be validated in the DIAL model) and some of the risk factors in the DIAL model (e.g. micro- and macroalbuminuria) were not available in the full semaglutide dataset.
Strengths and limitations
A limitation of our study is that some baseline factors that may have been important predictors in the CV risk prediction model (e.g. urinary albumin-to-creatinine ratio) were not measured across all trials and, therefore, were not included in the analysis. Potential weaknesses of the LEADER model include that all patients were of high or higher CV risk than those in the SUSTAIN and PIONEER efficacy trials, which may have affected the analysis at the lower end of the continuum of risk. However, the AUC for the glycemic efficacy trials only was 0.74 [0.69;0.79], which is broadly in line with the AUC for the combined data set.