Predictive factors of body weight loss in patients with type 2 diabetes treated with GLP-1 receptor agonists: a 52-week prospective real-life study

GLP-1受体激动剂治疗2型糖尿病患者体重减轻的预测因素:一项为期52周的前瞻性真实世界研究

阅读:2

Abstract

INTRODUCTION: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are widely prescribed for their efficacy in glycemic control and weight reduction, but patient response is heterogeneous and predictors of weight loss remain insufficiently defined. This 52-week prospective, observational study aimed to identify predictors of weight reduction (≥5% from baseline) in patients with type 2 diabetes mellitus (T2D) undergoing GLP-1RA therapy (semaglutide or dulaglutide, including oral formulations). METHODS: A total of 194 adults with T2D initiating GLP-1RA therapy were evaluated at baseline, and after 6, and 12 months of therapy. To identify predictors of weight loss, variables differing between Responders (weight loss ≥5% than baseline) and Non-Responders were evaluated by ROC analysis and tested in univariate and multivariate logistic regression models adjusted for age, gender, GLP-1RA type and dosage. RESULTS: At 6 and 12 months, 58% and 49% of patients, respectively, achieved the primary outcome. Responders at 12 months exhibited elevated BMI, waist circumference, hepatic steatosis indices, fat mass, and insulin levels at baseline, along with reduced muscle-to-fat and muscle-to-visceral adipose tissue ratios. Moreover, female gender, younger age, shorter disease duration, and non-use of metformin prior to enrollment were significantly associated with response. Notably, early response at 6 months strongly predicted 12-month success. CONCLUSIONS: Our results highlight a valuable interplay between body composition, liver involvement, and the incretin response, also suggesting a maximal synergistic effect between metformin and GLP-1RAs when treatments are initiated concurrently rather than sequentially. These data provide valuable insights for the development of individualized treatment strategies.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。