Pennington Becky, Cummins Ewen, Chandler Albany, Fotheringham James
Sheffield Centre for Health and Related Research, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.
McMDC Ltd, Aberdeen, UK.
Pharmacoeconomics. 2025 Jul 28. doi: 10.1007/s40273-025-01520-0.
The cost effectiveness of pharmacotherapies for obesity (such as semaglutide, tirzepatide, liraglutide, and newer agents) is increasingly being appraised by health technology assessment (HTA) bodies. Modelling is required to extrapolate weight change observed over relatively short clinical trial durations to long-term weight loss and associated cardio-metabolic outcomes and costs. Extrapolation is a common issue in HTA, but there is a unique challenge for anti-obesity drugs because of the number of interacting uncertainties. This is a particular concern given the substantial eligible population sizes and associated high financial decision risk of providing lifetime treatment. We describe four key challenges in modelling pharmacotherapies for obesity: (1) modelling long-term body mass index (BMI) trajectories with and without obesity pharmacotherapy, (2) modelling time on treatment, (3) using risk equations to link changes in BMI to clinical outcomes, and (4) modelling clinical outcomes not (solely) related to BMI changes. We discuss each of these challenges and the impact they have had in global HTA appraisals for pharmacotherapies. We speculate how these challenges relating to short-term clinical trials could be overcome to more robustly predict long-term outcomes and the role that observational data may play. As clinical trial and real-world evidence for technologies for obesity evolves, analysts and decision-makers need to determine which evidence sources are most appropriate and how they should be combined.
肥胖症药物治疗（如司美格鲁肽、替尔泊肽、利拉鲁肽及新型药物）的成本效益正日益受到卫生技术评估（HTA）机构的评估。需要进行建模，以便将在相对较短临床试验期间观察到的体重变化外推至长期体重减轻及相关的心血管代谢结局和成本。外推是卫生技术评估中的常见问题，但由于存在诸多相互作用的不确定性，抗肥胖药物面临独特挑战。鉴于符合条件的人群规模庞大以及提供终身治疗相关的高财务决策风险，这一问题尤为令人担忧。我们描述了肥胖症药物治疗建模中的四个关键挑战：（1）对接受和未接受肥胖症药物治疗的长期体重指数（BMI）轨迹进行建模；（2）对治疗时间进行建模；（3）使用风险方程将BMI变化与临床结局联系起来；（4）对并非（ solely）与BMI变化相关的临床结局进行建模。我们讨论了这些挑战中的每一个及其在全球肥胖症药物治疗HTA评估中所产生的影响。我们推测如何克服与短期临床试验相关的这些挑战，以便更可靠地预测长期结局，以及观察性数据可能发挥的作用。随着肥胖症治疗技术的临床试验和真实世界证据不断发展，分析人员和决策者需要确定哪些证据来源最为合适以及应如何将它们结合起来。
