Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
Centre for Health and Society, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
Acta Diabetol. 2022 Oct;59(10):1349-1359. doi: 10.1007/s00592-022-01917-9. Epub 2022 Jul 25.
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.
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.
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.
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.
新的抗糖尿病药物的大型心血管结局试验（CVOT）的治疗效果几乎完全以风险比的形式报告，尽管报告指南建议也以绝对规模报告治疗效果，例如需要治疗的人数（NNT）。我们旨在分析比较二肽基肽酶-4（DPP-4）抑制剂、胰高血糖素样肽-1（GLP-1）受体激动剂或钠-葡萄糖共转运蛋白-2（SGLT2）抑制剂与安慰剂的 CVOT 中的 NNT。
我们对 19 项比较 DPP-4 抑制剂、GLP-1 受体激动剂或 SGLT2 抑制剂与安慰剂的 CVOT 中的主要结局和全因死亡率的个体时间事件信息进行了数字化。我们为每个试验和结局估计了威布尔模型，并得出了每月的 NNT。通过随机效应荟萃分析方法，在所有试验中汇总 NNT，并在药物类别内汇总 NNT。
如果以 NNT 报告，CVOT 中的治疗效果似乎较小：总体而言，需要治疗 29 个月（所有试验的中位数随访时间）才能避免 100 例（95%-CI：60，303）患者发生主要结局的单个事件，需要治疗 39 个月才能避免 128 例（95%-CI：85，265）患者发生单个死亡。GLP-1 受体激动剂和 SGLT2 抑制剂的 NNT 时间曲线非常相似，而 DPP-4 抑制剂的治疗效果较小。
我们发现，以绝对规模（即需要治疗的人数）报告时，治疗效果看起来不那么令人印象深刻。为了全面了解新的抗糖尿病药物的益处，试验作者还应报告治疗效果的绝对规模。
