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Estimation and Validation of a Multiattribute Model of Alzheimer Disease Progression

Author

Listed:
  • Eric Stallard

    (Department of Sociology and Center for Population Health and Aging, Duke University, Durham, North Carolina)

  • Bruce Kinosian

    (Division of General Internal Medicine, University of Pennsylvania Health System, Philadelphia, Center for Health Equity Research and Promotion (CHERP), Philadelphia VA Medical Center, Philadelphia, Pennsylvania, brucek@mail.med.upenn.edu)

  • Arthur S. Zbrozek

    (Global Health Outcomes Assessment, Wyeth Pharmaceuticals, Collegeville, Pennsylvania)

  • Anatoliy I. Yashin

    (Department of Sociology and Center for Population Health and Aging, Duke University, Durham, North Carolina)

  • Henry A. Glick

    (Division of General Internal Medicine, University of Pennsylvania Health System, Philadelphia)

  • Yaakov Stern

    (Department of Neurology and the Gertrude H. Sergievsky Center and the Taub Institute for the Research on Alzheimer's Disease and the Aging Brain, Columbia University College of Physicians & Surgeons, New York, NY)

Abstract

Objectives. To estimate and validate a multiattribute model of the clinical course of Alzheimer disease (AD) from mild AD to death in a high-quality prospective cohort study, and to estimate the impact of hypothetical modifications to AD progression rates on costs associated with Medicare and Medicaid services. Data and Methods. The authors estimated sex-specific longitudinal Grade of Membership (GoM) models for AD patients (103 men, 149 women) in the initial cohort of the Predictors Study (1989—2001) based on 80 individual measures obtained every 6 mo for 10 y. These models were replicated for AD patients (106 men, 148 women) in the 2nd Predictors Study cohort (1997—2007). Model validation required that the disease-specific transition parameters be identical for both Predictors Study cohorts. Medicare costs were estimated from the National Long Term Care Survey. Results. Sex-specific models were validated using the 2nd Predictors Study cohort with the GoM transition parameters constrained to the values estimated for the 1st Predictors Study cohort; 57 to 61 of the 80 individual measures contributed significantly to the GoM models. Simulated, cost-free interventions in the rate of progression of AD indicated that large potential cost offsets could occur for patients at the earliest stages of AD. Conclusions. AD progression is characterized by a small number of parameters governing changes in large numbers of correlated indicators of AD severity. The analysis confirmed that the progression of AD represents a complex multidimensional physiological process that is similar across different study cohorts. The estimates suggested that there could be large cost offsets to Medicare and Medicaid from the slowing of AD progression among patients with mild AD. The methodology appears generally applicable in AD modeling.

Suggested Citation

  • Eric Stallard & Bruce Kinosian & Arthur S. Zbrozek & Anatoliy I. Yashin & Henry A. Glick & Yaakov Stern, 2010. "Estimation and Validation of a Multiattribute Model of Alzheimer Disease Progression," Medical Decision Making, , vol. 30(6), pages 625-638, November.
  • Handle: RePEc:sae:medema:v:30:y:2010:i:6:p:625-638
    DOI: 10.1177/0272989X10363479
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    References listed on IDEAS

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    1. Denis Getsios & Kristen Migliaccio-Walle & Jaime Caro, 2007. "NICE Cost-Effectiveness Appraisal of Cholinesterase Inhibitors," PharmacoEconomics, Springer, vol. 25(12), pages 997-1006, December.
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    Cited by:

    1. Alexander Schmidt-Richberg & Christian Ledig & Ricardo Guerrero & Helena Molina-Abril & Alejandro Frangi & Daniel Rueckert & on behalf of the Alzheimer’s Disease Neuroimaging Initiative, 2016. "Learning Biomarker Models for Progression Estimation of Alzheimer’s Disease," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-27, April.

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