Literature DB >> 18631970

Decision analytic models for Alzheimer's disease: state of the art and future directions.

Joshua T Cohen1, Peter J Neumann.   

Abstract

Decision analytic policy models for Alzheimer's disease (AD) enable researchers and policy makers to investigate questions about the costs and benefits of a wide range of existing and potential screening, testing, and treatment strategies. Such models permit analysts to compare existing alternatives, explore hypothetical scenarios, and test the strength of underlying assumptions in an explicit, quantitative, and systematic way. Decision analytic models can best be viewed as complementing clinical trials both by filling knowledge gaps not readily addressed by empirical research and by extrapolating beyond the surrogate markers recorded in a trial. We identified and critiqued 13 distinct AD decision analytic policy models published since 1997. Although existing models provide useful insights, they also have a variety of limitations. (1) They generally characterize disease progression in terms of cognitive function and do not account for other distinguishing features, such as behavioral symptoms, functional performance, and the emotional well-being of AD patients and caregivers. (2) Many describe disease progression in terms of a limited number of discrete states, thus constraining the level of detail that can be used to characterize both changes in patient status and the relationships between disease progression and other factors, such as residential status, that influence outcomes of interest. (3) They have focused almost exclusively on evaluating drug treatments, thus neglecting other disease management strategies and combinations of pharmacologic and nonpharmacologic interventions. Future AD models should facilitate more realistic and compelling evaluations of various interventions to address the disease. An improved model will allow decision makers to better characterize the disease, to better assess the costs and benefits of a wide range of potential interventions, and to better evaluate the incremental costs and benefits of specific interventions used in conjunction with other disease management strategies.

Entities:  

Mesh:

Year:  2008        PMID: 18631970     DOI: 10.1016/j.jalz.2008.02.003

Source DB:  PubMed          Journal:  Alzheimers Dement        ISSN: 1552-5260            Impact factor:   21.566


  17 in total

Review 1.  Dependence as a unifying construct in defining Alzheimer's disease severity.

Authors:  Trent McLaughlin; Howard Feldman; Howard Fillit; Mary Sano; Frederick Schmitt; Paul Aisen; Christopher Leibman; Lisa Mucha; J Michael Ryan; Sean D Sullivan; D Eldon Spackman; Peter J Neumann; Joshua Cohen; Yaakov Stern
Journal:  Alzheimers Dement       Date:  2010-11       Impact factor: 21.566

2.  Disease progression and costs of care in Alzheimer's disease patients treated with donepezil: a longitudinal naturalistic cohort.

Authors:  Anders Gustavsson; Linus Jönsson; Johan Parmler; Niels Andreasen; Carina Wattmo; Åsa K Wallin; Lennart Minthon
Journal:  Eur J Health Econ       Date:  2011-08-06

3.  Evaluating disease-modifying agents: a simulation framework for Alzheimer's disease.

Authors:  Shien Guo; Denis Getsios; Nikhil Revankar; Peng Xu; Gwilym Thompson; Joel Bobula; Loretto Lacey; Maren Gaudig
Journal:  Pharmacoeconomics       Date:  2014-11       Impact factor: 4.981

4.  Unfinished Business in Preventing Alzheimer Disease.

Authors:  Jason Karlawish; Kenneth M Langa
Journal:  JAMA Intern Med       Date:  2016-12-01       Impact factor: 21.873

5.  Societal and Family Lifetime Cost of Dementia: Implications for Policy.

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

6.  Dependence Stage and Pharmacoeconomic Outcomes in Patients With Alzheimer Disease.

Authors:  Tzeyu L Michaud; Robin High; Mary E Charlton; Daniel L Murman
Journal:  Alzheimer Dis Assoc Disord       Date:  2017 Jul-Sep       Impact factor: 2.703

Review 7.  Health state values for use in the economic evaluation of treatments for Alzheimer's disease.

Authors:  James Shearer; Colin Green; Craig W Ritchie; John P Zajicek
Journal:  Drugs Aging       Date:  2012-01-01       Impact factor: 3.923

Review 8.  Systematic Review of Model-Based Economic Evaluations of Treatments for Alzheimer's Disease.

Authors:  Luis Hernandez; Asli Ozen; Rodrigo DosSantos; Denis Getsios
Journal:  Pharmacoeconomics       Date:  2016-07       Impact factor: 4.981

9.  Cost effectiveness of donepezil in the treatment of mild to moderate Alzheimer's disease: a UK evaluation using discrete-event simulation.

Authors:  Denis Getsios; Steve Blume; K Jack Ishak; Grant D H Maclaine
Journal:  Pharmacoeconomics       Date:  2010       Impact factor: 4.981

10.  Evaluating the cost effectiveness of donepezil in the treatment of Alzheimer's disease in Germany using discrete event simulation.

Authors:  Susanne Hartz; Denis Getsios; Sunning Tao; Steve Blume; Grant Maclaine
Journal:  BMC Neurol       Date:  2012-02-08       Impact factor: 2.474

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