Risk factor screening and prediction modeling of gastrointestinal adverse reactions caused by GLP-1RAs - Gao, Rui; Li, Yue; Li, Anan; Zhou, Penglin; Zong, Huiying; Li, Yan (Frontiers in Endocrinology, 2024)
Objective: To explore the risk factors for gastrointestinal side effects (GISEs) in patients with type 2 diabetes mellitus (T2DM) during treatment with glucagon-like peptide-1 receptor agonists (GLP-1RAs) based on real-world data, and to develop a prediction model for GLP-1RAs related GISEs. Methods: A total of 855 patients who attended the First Affiliated Hospital of Shandong First Medical University from January 2020 to May 2023 were selected as the study participants, and were divided into the training set (598 cases) and validation set (297 cases) by using simple random sampling method in a ratio of 7:3. General information and biochemical indicators of participants were collected to assess the risk factors for GLP-1RAs related GISEs, and multifactorial logistic regression analysis was used to obtain the best predictors. The nomogram prediction model was constructed, Hosmer-Lemeshow test was used to assess the differentiation and calibration of the nomogram model, and decision curve analysis (DCA) was used to evaluate the clinical utility of the model. Results: Age, gender, history of gastrointestinal disorders, and number of combined oral medications were the risk factors for the occurrence of GISEs in T2DM patients using GLP-1RAs (P < 0.05). The nomogram prediction model based on the four factors had a good discriminability (AUC values of the training set and validation set were 0.855 and 0.836, respectively) and accuracy (Hosmer-Lemeshow test: P > 0.05 for the validation set). DCA curve analysis showed that the prediction model curve had clinical utility in the threshold probability interval of > 5 %. Conclusions: The established nomogram model has an excellent predictive effect on GISEs induced by GLP-1RAs in T2DM patients.