A model‐based approach to predict individual weight loss with semaglutide in people with overweight or obesity

赛马鲁肽 超重 减肥 医学 肥胖 人口统计学的 人口 加药 内科学 糖尿病 2型糖尿病 人口学 内分泌学 环境卫生 利拉鲁肽 社会学
作者
Anders Strathe,Deborah B. Horn,Malte Selch Larsen,Domenica Rubino,Rasmus Sørrig,Marie Thi Dao Tran,Sean Wharton,Rune Viig Overgaard
出处
期刊:Diabetes, Obesity and Metabolism [Wiley]
卷期号:25 (11): 3171-3180 被引量:22
标识
DOI:10.1111/dom.15211
摘要

Abstract Aims To determine the relationship between exposure and weight‐loss trajectories for the glucagon‐like peptide‐1 analogue semaglutide for weight management. Materials and Methods Data from one 52‐week, phase 2, dose‐ranging trial (once‐daily subcutaneous semaglutide 0.05–0.4 mg) and two 68‐week phase 3 trials (once‐weekly subcutaneous semaglutide 2.4 mg) for weight management in people with overweight or obesity with or without type 2 diabetes were used to develop a population pharmacokinetic (PK) model describing semaglutide exposure. An exposure‐response model describing weight change was then developed using baseline demographics, glycated haemoglobin and PK data during treatment. The ability of the exposure‐response model to predict 1‐year weight loss based on weight data collected at baseline and after up to 28 weeks of treatment, was assessed using three independent phase 3 trials. Results Based on population PK, exposure levels over time consistently explained the weight‐loss trajectories across trials and dosing regimens. The exposure‐response model had high precision and limited bias for predicting body weight loss at 1 year in independent datasets, with increased precision when data from later time points were included in the prediction. Conclusion An exposure‐response model has been established that quantitatively describes the relationship between systemic semaglutide exposure and weight loss and predicts weight‐loss trajectories for people with overweight or obesity who are receiving semaglutide doses up to 2.4 mg once weekly.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
风格化橙发布了新的文献求助10
1秒前
sjfczyh发布了新的文献求助10
2秒前
runner完成签到,获得积分10
2秒前
blizzard完成签到 ,获得积分10
2秒前
xxxksk完成签到 ,获得积分10
3秒前
超级小飞侠完成签到 ,获得积分10
4秒前
123455完成签到,获得积分10
6秒前
7秒前
Rainyin给Rainyin的求助进行了留言
7秒前
青丝完成签到,获得积分10
8秒前
清秀的梦安完成签到,获得积分20
9秒前
上官若男应助无情鼠标采纳,获得10
10秒前
zwhy579完成签到 ,获得积分10
10秒前
11秒前
全没了应助科研通管家采纳,获得10
12秒前
星辰大海应助科研通管家采纳,获得10
12秒前
爆米花应助科研通管家采纳,获得10
12秒前
夕木木应助科研通管家采纳,获得10
12秒前
13秒前
Mic应助科研通管家采纳,获得10
13秒前
13秒前
13秒前
完美世界应助科研通管家采纳,获得10
13秒前
13秒前
13秒前
夕木木应助科研通管家采纳,获得10
13秒前
Mic应助科研通管家采纳,获得10
13秒前
无花果应助科研通管家采纳,获得10
13秒前
完美世界应助科研通管家采纳,获得10
13秒前
夕木木应助科研通管家采纳,获得10
13秒前
Mic应助科研通管家采纳,获得10
13秒前
sagitar应助科研通管家采纳,获得20
13秒前
研友_VZG7GZ应助科研通管家采纳,获得10
13秒前
13秒前
全没了应助科研通管家采纳,获得10
13秒前
无花果应助科研通管家采纳,获得20
14秒前
慕青应助科研通管家采纳,获得10
14秒前
所所应助科研通管家采纳,获得10
14秒前
14秒前
Mic应助科研通管家采纳,获得10
14秒前
高分求助中
The Graphene Handbook (2019 Edition) 800
IEST-RP-CC018: Cleanroom Cleaning and Sanitization: Operating and Monitoring Procedures 600
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
久松真一著作集〈第5巻〉禅と芸術 500
Fundamentals of Modern Mathematics: A Practical Review (Dover Books on Mathematics) 500
Cold War Transcended: Australia's China Policy, 1949-1990 470
Comprehensive Organic Synthesis 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6596932
求助须知:如何正确求助?哪些是违规求助? 8366841
关于积分的说明 17909700
捐赠科研通 5749694
什么是DOI,文献DOI怎么找? 2953219
邀请新用户注册赠送积分活动 1928537
关于科研通互助平台的介绍 1822447