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Session: Caring for the Elderly
Room: Elissa Hall
Time: Sat 10:15-11:30

Presenter: Colin Green (University of Exeter. Peninsula Medical School)

Abstract

Alzheimer’s disease (AD) is a key health care priority in many health systems. However due to the large number of people affected by AD it represents a large burden on the health care budget and policy makers are often faced with difficult decisions over the provision of health and social care. Decision modeling can inform these decisions, but policy makers must be aware of the strengths and weaknesses of the methods used to model disease progression, and any subsequent cost-effectiveness analyses.

The aim of this research is to examine recent developments in the methods used to model disease progression in Alzheimer’s disease (AD), and to consider future directions and developments that may enhance the value of modelling methods for use in cost-effectiveness analyses in AD. This research explores the methods available to model disease progression in Alzheimer’s disease, in particular the structure of models and the way that the natural history of disease and related risk factors are modeled in an empirical way, and how these empirical models are used in decision-analytic models.

A systematic literature search and review has been undertaken to inform on the modeling methods available. The review identifies over 40 papers reporting modeling of Alzheimer’s disease over time. Many of these studies have used common approaches to model disease progression, with some adjustments in a decision-analytic context. The literature in these areas has developed over the last decade, however there remains a reliance on modeling methods, and data inputs, that are based on assessment of AD against cognitive function (often alone). Recent contributions to the literature have strengthened a growing view that modeling in AD should be based on multiple dimensions of Alzheimers’s disease, and this is the foundation for considering future directions in modeling methods. A literature review has also been undertaken to inform on the key structural elements and data inputs around costs of caring, QALY values and mortality in Alzheimer’s disease.

The statistical modeling of disease progression is a key element of the broader structure of a decision-analytic model. This research provides guidance on this important element of decision models, where the choices made over alternative methods to model disease progression can have an important impact on the results produced and the interpretation and generalisability of findings. Given the growing impact of AD, and the pipeline of promising new treatments, there will be an even greater reliance on the use of modeling methods to inform decision-making. This research highlights a need for greater awareness of the current methodology and the need to develop new approaches for the modeling of AD - providing a suggested modelling framework for future analyses.

Key Terms

Alzheimer’s disease, ageing, modeling, cost-effectiveness analysis

Authors:

Colin Green (University of Exeter. Peninsula Medical School) , James Shearer (University of Exeter. Peninsula Medical School) , David Wright (University of Plymouth. Mathematics and Statistics) and Paul Thompson (University of Plymouth. Mathematics and Statistics)

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