ABSTRACT

Introduction

Alzheimer’s disease (AD) is a complex neurodegenerative disease, affecting millions of people worldwide and imposing heavy economic burdens to societies. Currently, only symptomatic treatments are available for patients, but there is ongoing research on potential therapies that can modify the course of disease. The main objective of this work is to identify and explore the challenges surrounding decision modeling for economic evaluation of interventions for AD.

Areas covered

This article discusses the challenges in modeling the natural history of disease, particularly regarding the selection of disease progression and outcome measures, the inclusion of biomarker status in models, and the approach to model mortality. Challenges stemming from the use of long-term assumptions regarding treatment effects and the need for real-world evidence to fill data gaps are discussed. Lastly, the overwhelming economic impact of disease and the challenges in estimating these costs for modeling are addressed.

Expert opinion

Value assessment frameworks need to be reconsidered in order to demonstrate the full benefit of new disease-modifying therapies spanning beyond the scope of health systems. Data collection efforts that expand the evidence base, upon which economic models are based, will reduce the uncertainties surrounding the long-term outcomes of interventions in AD.

中文翻译：

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证明疾病改善疗法对阿尔茨海默病的价值的挑战。

摘要

介绍

阿尔茨海默病 (AD) 是一种复杂的神经退行性疾病，影响全球数百万人，给社会带来沉重的经济负担。目前，只有对症治疗可供患者使用，但正在研究可以改变病程的潜在疗法。这项工作的主要目标是确定和探索围绕决策建模对 AD 干预措施进行经济评估的挑战。

涵盖的领域

本文讨论了在疾病自然史建模方面的挑战，特别是在疾病进展和结果测量的选择、模​​型中生物标志物状态的纳入以及死亡率模型的方法方面。讨论了使用有关治疗效果的长期假设以及需要真实世界的证据来填补数据空白所带来的挑战。最后，解决了疾病对经济的巨大影响以及估算这些建模成本所面临的挑战。

专家意见

需要重新考虑价值评估框架，以证明超越卫生系统范围的新疾病改善疗法的全部益处。扩大经济模型所依据的证据基础的数据收集工作将减少围绕 AD 干预的长期结果的不确定性。