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探索钠-葡萄糖共转运蛋白 2 抑制剂在 2 型糖尿病中的心血管死亡获益比较:基于频率论和贝叶斯网络荟萃分析评分的研究。

Exploring the comparative cardiovascular death benefits of sodium-glucose cotransporter 2 inhibitors in type 2 diabetes: a frequentist and Bayesian network meta-analysis-based scoring.

机构信息

Department of Endocrinology, Nightingale Hospital, Kolkata, India.

Department of Endocrinology, AMRI Hospital, Kolkata, India.

出版信息

Front Endocrinol (Lausanne). 2023 Jul 3;14:1168755. doi: 10.3389/fendo.2023.1168755. eCollection 2023.

DOI:10.3389/fendo.2023.1168755
PMID:37469980
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10353048/
Abstract

BACKGROUND AND AIMS

Cardiovascular death (CV death) is the most objective component of the primary or secondary endpoint in cardiovascular outcome trials (CVOTs) conducted with sodium-glucose cotransporter 2 inhibitors (SGLT-2is). CV death is often incorporated into primary composite outcomes. It is combined with major adverse cardiovascular events (MACEs) in trials with atherosclerotic cardiovascular disease (ASCVD) at baseline and with hospitalization due to heart failure (hHF) in trials with heart failure at baseline. Unlike the primary composites, CV death reduction by itself demonstrated significant variations among the CVOTs with SGLT-2is. Moreover, the impact of the individual agents within the SGLT-2i group on the reduction in CV death has not been explored objectively. This network meta-analysis was undertaken to construct a hierarchy based on indirect pairwise comparisons and rankings among the individual agents within SGLT-2is.

METHODS

A Cochrane library-based web search yielded 13 randomized controlled trials for analysis. Stata/BE 17.0 and RStudio 2022.07.1 Build 554 software were used to conduct a frequentist and Bayesian network meta-analysis. The effect size was assessed based on the risk ratio (RR). Ranking of the individual agents was performed with a frequentist approach (P-score and a multidimensional scaling [MDS] rank system) and a Bayesian ranking (surface under the cumulative ranking [SUCRA]).

RESULTS

Regarding the overall data, SGLT-2is reduced the CV death risk by 12% (RR: 0.88, 95% CI 0.80-0.96). All three scoring methods resulted in empagliflozin scoring the highest. There was a 15% RR reduction in CV death (95% CI 0.71-1.02) in the ASCVD and multiple cardiovascular risk factor (MRF) groups and an 11% RR reduction in the HF group, with empagliflozin ranking the highest in the former group and dapagliflozin in the latter.

CONCLUSIONS

Empagliflozin ranked the highest compared to the other SGLT-2is in the overall population and the trials including type 2 diabetes (T2D) patients with ASCVD or MRF at baseline, while dapagliflozin ranked the highest in the trials of patients with HF at baseline.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022381556, identifier CRD42022381556.

摘要

背景与目的

心血管死亡(CV 死亡)是使用钠-葡萄糖共转运蛋白 2 抑制剂(SGLT-2i)进行的心血管结局试验(CVOT)中主要或次要终点最客观的组成部分。CV 死亡通常纳入主要复合结局。在基线时患有动脉粥样硬化性心血管疾病(ASCVD)的试验中,它与主要不良心血管事件(MACEs)合并,在基线时患有心力衰竭(HF)的试验中,它与心力衰竭住院相关。与主要复合结局不同,SGLT-2i 中的 CVOT 之间单独使用 SGLT-2i 可显著降低 CV 死亡。此外,尚未客观探讨 SGLT-2i 组内各个药物对降低 CV 死亡的影响。本网络荟萃分析旨在基于 SGLT-2i 中个体药物的间接成对比较和排名构建一个层次结构。

方法

基于 Cochrane 图书馆的网络搜索得出了 13 项用于分析的随机对照试验。使用 Stata/BE 17.0 和 RStudio 2022.07.1 Build 554 软件进行了频率论和贝叶斯网络荟萃分析。根据风险比(RR)评估效应大小。使用频率论方法(P 评分和多维标度[MDS]排名系统)和贝叶斯排名(累积排名下的表面积[SUCRA])对个体药物进行排名。

结果

关于整体数据,SGLT-2i 降低了 12%的 CV 死亡风险(RR:0.88,95%CI 0.80-0.96)。三种评分方法均得出恩格列净评分最高。在 ASCVD 和多种心血管危险因素(MRF)组中,CV 死亡的 RR 降低了 15%(95%CI 0.71-1.02),HF 组中 RR 降低了 11%,恩格列净在前者中排名最高,达格列净在后者中排名最高。

结论

与其他 SGLT-2i 相比,恩格列净在整体人群以及包括基线时患有 ASCVD 或 MRF 的 2 型糖尿病(T2D)患者的试验中排名最高,而在基线时患有 HF 的患者中,达格列净排名最高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/350f/10353048/8933fdeca3e7/fendo-14-1168755-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/350f/10353048/d001e35dbb49/fendo-14-1168755-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/350f/10353048/f00672b1dcca/fendo-14-1168755-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/350f/10353048/e5464d0248ef/fendo-14-1168755-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/350f/10353048/8933fdeca3e7/fendo-14-1168755-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/350f/10353048/d001e35dbb49/fendo-14-1168755-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/350f/10353048/f00672b1dcca/fendo-14-1168755-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/350f/10353048/e5464d0248ef/fendo-14-1168755-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/350f/10353048/8933fdeca3e7/fendo-14-1168755-g004.jpg

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