Medications and conditions associated with weight loss in patients prescribed semaglutide based on real-world data

IF 4.2 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Obesity Pub Date : 2023-08-18 DOI:10.1002/oby.23859
William Powell, Xing Song, Yahia Mohamed, Dave Walsh, Elizabeth J. Parks, Tamara M. McMahon, Mirza Khan, Lemuel R. Waitman
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引用次数: 1

Abstract

Objective

Approved by the Food and Drug Administration (FDA) in 2017 for diabetes and in 2021 for weight loss, semaglutide has seen widespread use among individuals who aim to lose weight. The aim of this study was to evaluate weight loss and the influence of clinical factors on semaglutide patients in real-world clinical practice.

Methods

Using data from 10 health systems within the Greater Plains Collaborative (a PCORnet Clinical Research Network), nearly 4000 clinical factors encompassing demographic, diagnosis, and prescription information were extracted for semaglutide patients. A gradient-boosting, machine-learning classifier was developed for weight-loss prediction and identification of the most impactful factors via SHapley Additive exPlanations (SHAP) value extrapolation.

Results

A total of 3555 eligible patients (539 of whom were observed 52 weeks following exposure) from March 2017 to April 2022 were studied. On average, individuals lost 4.44% (male individuals, 3.66%; female individuals, 5.08%) of their initial weight. History of diabetes mellitus diagnosis was associated with less weight loss, whereas prediabetes and linaclotide use were associated with more pronounced weight loss.

Conclusions

Weight loss in patients prescribed semaglutide from real-world evidence was strong but attenuated compared with previous clinical trials. Machine-learning analysis of electronic health record data identified factors that warrant further research and consideration when tailoring weight-loss therapy.

Abstract Image

基于真实世界的数据,与患者体重减轻相关的药物和条件
西马鲁肽于2017年被美国食品和药物管理局(FDA)批准用于糖尿病治疗,于2021年被批准用于减肥,在以减肥为目标的人群中广泛使用。本研究的目的是在现实世界的临床实践中评估西马鲁肽患者的体重减轻和临床因素的影响。方法利用来自大平原协作组织(PCORnet临床研究网络)的10个卫生系统的数据,提取西马鲁肽患者的近4000个临床因素,包括人口统计学、诊断和处方信息。通过SHapley加性解释(SHAP)值外推,开发了一个梯度增强的机器学习分类器,用于减肥预测和识别最具影响的因素。结果2017年3月至2022年4月,共有3555名符合条件的患者(其中539人在暴露后52周观察)进行了研究。个体平均损失4.44%(雄性个体,3.66%;雌性个体,占其初始体重的5.08%。糖尿病诊断史与较少的体重减轻相关,而糖尿病前期和利那氯肽的使用与更明显的体重减轻相关。结论:实际证据表明,服用西马鲁肽的患者体重减轻明显,但与之前的临床试验相比有所减弱。对电子健康记录数据的机器学习分析确定了在定制减肥疗法时值得进一步研究和考虑的因素。
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来源期刊
Obesity
Obesity 医学-内分泌学与代谢
CiteScore
11.70
自引率
1.40%
发文量
261
审稿时长
2-4 weeks
期刊介绍: Obesity is the official journal of The Obesity Society and is the premier source of information for increasing knowledge, fostering translational research from basic to population science, and promoting better treatment for people with obesity. Obesity publishes important peer-reviewed research and cutting-edge reviews, commentaries, and public health and medical developments.
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