Absolute treatment effects for the primary outcome and all-cause mortality in the cardiovascular outcome trials of new antidiabetic drugs: a meta-analysis of digitalized individual patient data

Abstract

Aims: Treatment effects from the large cardiovascular outcome trials (CVOTs) of new antidiabetic drugs are almost exclusively communicated as hazard ratios, although reporting guidelines recommend to report treatment effects also on an absolute scale, e.g. as numbers needed to treat (NNT). We aimed to analyse NNTs in CVOTs comparing dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, or sodium–glucose cotransporter-2 (SGLT2) inhibitors to placebo. Methods: We digitalized individual time-to-event information for the primary outcome and all-cause mortality from 19 CVOTs that compared DPP-4 inhibitors, GLP-1 receptor agonists, or SGLT2 inhibitors to placebo. We estimated Weibull models for each trial and outcome and derived monthly NNTs. NNTs were summarized across all trials and within drug classes by random effects meta-analysis methods. Results: Treatment effects in the CVOTs appear smaller if they are reported as NNTs: Overall, 100 (95%-CI: 60, 303) patients have to be treated for 29 months (the median follow-up time across all trials) to avoid a single event of the primary outcome, and 128 (95%-CI: 85, 265) patients have to be treated for 39 months to avoid a single death. NNT time courses are very similar for GLP-1 receptor agonists and SGLT2 inhibitors, whereas treatment effects with DPP-4 inhibitors are smaller. Conclusions: We found that the respective treatment effects look less impressive when communicated on an absolute scale, as numbers needed to treat. For a valid overall picture of the benefit of new antidiabetic drugs, trial authors should also report treatment effects on an absolute scale.