OBJECTIVE: To consider the methods available to model Alzheimer's disease (AD) progression over time to inform on the structure and development of model-based evaluations, and the future direction of modelling methods in AD. METHODS: A systematic search of the health care literature was undertaken to identify methods to model disease progression in AD. Modelling methods are presented in a descriptive review. RESULTS: The literature search identified 42 studies presenting methods or applications of methods to model AD progression over time. The review identified 10 general modelling frameworks available to empirically model the progression of AD as part of a model-based evaluation. Seven of these general models are statistical models predicting progression of AD using a measure of cognitive function. The main concerns with models are on model structure, around the limited characterization of disease progression, and on the use of a limited number of health states to capture events related to disease progression over time. None of the available models have been able to present a comprehensive model of the natural history of AD. CONCLUSIONS: Although helpful, there are serious limitations in the methods available to model progression of AD over time. Advances are needed to better model the progression of AD and the effects of the disease on peoples' lives. Recent evidence supports the need for a multivariable approach to the modelling of AD progression, and indicates that a latent variable analytic approach to characterising AD progression is a promising avenue for advances in the statistical development of modelling methods.
OBJECTIVE: To consider the methods available to model Alzheimer's disease (AD) progression over time to inform on the structure and development of model-based evaluations, and the future direction of modelling methods in AD. METHODS: A systematic search of the health care literature was undertaken to identify methods to model disease progression in AD. Modelling methods are presented in a descriptive review. RESULTS: The literature search identified 42 studies presenting methods or applications of methods to model AD progression over time. The review identified 10 general modelling frameworks available to empirically model the progression of AD as part of a model-based evaluation. Seven of these general models are statistical models predicting progression of AD using a measure of cognitive function. The main concerns with models are on model structure, around the limited characterization of disease progression, and on the use of a limited number of health states to capture events related to disease progression over time. None of the available models have been able to present a comprehensive model of the natural history of AD. CONCLUSIONS: Although helpful, there are serious limitations in the methods available to model progression of AD over time. Advances are needed to better model the progression of AD and the effects of the disease on peoples' lives. Recent evidence supports the need for a multivariable approach to the modelling of AD progression, and indicates that a latent variable analytic approach to characterising AD progression is a promising avenue for advances in the statistical development of modelling methods.
Authors: Eric Jutkowitz; Robert L Kane; Joseph E Gaugler; Richard F MacLehose; Bryan Dowd; Karen M Kuntz Journal: J Am Geriatr Soc Date: 2017-08-17 Impact factor: 5.562
Authors: Qolamreza R Razlighi; Eric Stallard; Jason Brandt; Deborah Blacker; Marilyn Albert; Nikolaos Scarmeas; Bruce Kinosian; Anatoliy I Yashin; Yaakov Stern Journal: J Alzheimers Dis Date: 2014 Impact factor: 4.472
Authors: Ilona Hallikainen; Janne Martikainen; Pei-Jung Lin; Joshua T Cohen; Raquel Lahoz; Tarja Välimäki; Kristiina Hongisto; Saku Väätäinen; Matti Vanhanen; Peter J Neumann; Tuomo Hänninen; Anne Maria Koivisto Journal: Dement Geriatr Cogn Dis Extra Date: 2014-12-11