Cengiz Anıl, Wu Calvin C, Lawley Sean D
Department of Mathematics, University of Utah, Salt Lake City, Utah, USA.
Tono Health, Brooklyn, New York, USA.
Diabetes Obes Metab. 2025 Aug;27(8):4109-4117. doi: 10.1111/dom.16438. Epub 2025 May 13.
GLP-1 and GIP-GLP-1 agonists have emerged as potent weight-loss medications. These incretin mimetics often have low patient adherence, and as with any medication, clinically meaningful efficacy requires adequate adherence. But what constitutes "adequate" adherence for incretin mimetics? The purpose of this paper is to address this question.
We use mathematical modelling and stochastic simulation to investigate the weight loss efficacy of incretin mimetics under imperfect adherence. We use validated pharmacokinetic and pharmacodynamic models of semaglutide and tirzepatide and assume that simulated patients randomly miss doses.
We find that semaglutide and tirzepatide forgive nonadherence, meaning that strong weight loss efficacy persists despite missed doses. For example, taking 80% of the prescribed doses yields around 90% of the weight loss achieved under perfect adherence. Taking only 50% of the prescribed doses yields nearly 70% of the weight loss of perfect adherence. Furthermore, such nonadherence causes only small fluctuations in body weight, assuming that patients do not typically miss more than several consecutive doses.
Incretin mimetics are powerful tools for combating obesity, perhaps even if patients can consistently take only half of their prescribed doses. The common assumption that significant weight loss requires at least 80% adherence needs revision.
胰高血糖素样肽 -1(GLP-1)和胃抑肽 -GLP-1激动剂已成为强效减肥药物。这些肠促胰岛素类似物患者依从性往往较低,与任何药物一样,具有临床意义的疗效需要足够的依从性。但对于肠促胰岛素类似物而言,什么才构成“足够”的依从性呢?本文旨在解决这个问题。
我们使用数学建模和随机模拟来研究不完全依从情况下肠促胰岛素类似物的减肥效果。我们使用了经验证的司美格鲁肽和替尔泊肽的药代动力学和药效学模型,并假设模拟患者随机漏服剂量。
我们发现司美格鲁肽和替尔泊肽对不依从具有宽容性,这意味着即使漏服剂量,强效减肥效果依然存在。例如,服用规定剂量的80%可产生在完全依从情况下约90%的体重减轻效果。仅服用规定剂量的50%可产生接近完全依从情况下70%的体重减轻效果。此外,假设患者通常不会连续漏服超过几剂,这种不依从只会导致体重出现小的波动。
肠促胰岛素类似物是对抗肥胖的有力工具,即便患者始终只能服用规定剂量的一半或许也行。认为显著体重减轻至少需要80%依从性的普遍假设需要修正。