Aihua Wang , Weilong Shi , Ning Zhang , Huilin Tang , Xin Feng
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引用次数: 0
Abstract
Purpose
Previous studies have shown that newer glucose-lowering drugs (GLDs), such as sodium-glucose transport protein 2 (SGLT2) inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1RAs), and dipeptidyl peptidase 4 (DPP-4) inhibitors, may decrease the risk of gout, however, the evidence remains inconclusive. This study aimed to assess the association between newer GLDs and risk of gout.
Methods
We systematically searched electronic databases up to August 2023 to include randomized, placebo-controlled outcome trials that reported gout-related outcomes in participants with and without type 2 diabetes. A random effects network meta-analysis was conducted to estimate the risk ratio (RR) with 95% confidence interval (CI) to compare the effects of SGLT2 inhibitors, GLP-1RAs, and DPP-4 inhibitors on risk of gout.
Findings
This study included 22 trials involving 173,498 patients. Compared with placebo, SGLT2 inhibitors were significantly associated with decreased risk of gout (RR, 0.51; 95% CI, 0.29–0.91) while both GLP-1RAs and DPP-4 inhibitors have no significant effects on gout risk. There were no significant differences between SGLT2 inhibitors and GLP-1RAs (RR, 0.75; 95%CI, 0.31–1.82) and between GLP-1RAs and DPP-4 inhibitors (RR, 0.39; 95%CI, 0.14–1.10).
Implications
SGLT2 inhibitors may potentially prevent the risk of gout, however, both GLP-1RAs and DPP-4 inhibitors have neutral effects.
期刊介绍:
Clinical Therapeutics provides peer-reviewed, rapid publication of recent developments in drug and other therapies as well as in diagnostics, pharmacoeconomics, health policy, treatment outcomes, and innovations in drug and biologics research. In addition Clinical Therapeutics features updates on specific topics collated by expert Topic Editors. Clinical Therapeutics is read by a large international audience of scientists and clinicians in a variety of research, academic, and clinical practice settings. Articles are indexed by all major biomedical abstracting databases.