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Original Paper

Free Access

Analyses of Diagnostic Patterns at 30 Alzheimer’s Disease Centers in the US

Steenland K.a, b · Macneil J.a · Bartell S.c · Lah J.b

Author affiliations

aRollins School of Public Health and bAlzheimer’s Disease Research Center, Emory University, Atlanta, Ga., and cProgram in Public Health, University of California at Irvine, Irvine, Calif., USA

Corresponding Author

Dr. Kyle Steenland

Emory University, Rollins School of Public Health

1518 Clifton Road

Atlanta, GA 30322 (USA)

Tel. +1 404 712 8277, E-Mail nsteenl@sph.emory.edu

Related Articles for ""

Neuroepidemiology 2010;35:19–27

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Background: The US Alzheimer’s Disease Centers (ADCs) (n = 30) recently created a uniform data set. We sought to determine which variables were most important in making a diagnosis, and how these differed across ADCs. Methods: A cross-sectional analysis of first visits to ADCs via polytomous logistic regression. We analyzed subjects with complete data (n = 7,555, 89%), and also used multiple imputation to infer missing data. Results: There were 8,495 subjects; 50, 26, and 24% were diagnosed as normal, having mild cognitive impairment (MCI), or mild Alzheimer’s disease [Clinical Dementia Rating (CDR) score <1], respectively. The model using 7,555 subjects was 86% accurate in predicting diagnosis. Important predictors were physician-reported decline and the CDR sum of boxes, followed by 4 cognitive tests (Mini Mental State Examination, Category Fluency Tests, Logical Memory Test, Boston Naming Test). Multiple imputation revealed Trail Making Test B to be additionally important. Consensus versus single-clinician diagnoses were 2–3 times more likely to result in MCI than normal diagnoses. Excluding clinical judgment variables, functional assessment and psychiatric symptoms were important additional predictors; model accuracy remained high (78%). There were significant differences between centers in the use of different cognitive tests in making diagnoses. Conclusions: We recommend creating a hypothetic data set to use across ADCs to improve diagnostic consistency, and a survey on the use of raw or adjusted cognitive test scores by different ADCs.

© 2010 S. Karger AG, Basel


  1. Morris JC, Weintraub S, Chui HC, Cummings J, Decarli C, Ferris S, Foster NL, Galasko D, Graff-Radford N, Peskind ER, Beekly D, Ramos EM, Kukull WA: The Uniform Data Set (UDS): clinical and cognitive variables and descriptive data from Alzheimer Disease Centers. Alzheimer Dis Assoc Disord 2006;20:210–216.
  2. Beekly DL, Ramos EM, Lee WW, Deitrich WD, Jacka ME, Wu J, Hubbard JL, Koepsell TD, Morris JC, Kukull WA, NIA Alzheimer’s Disease Centers: The National Alzheimer’s Coordinating Center (NACC) database: the Uniform Data Set. Alzheimer Dis Assoc Disord 2007;21:249–258.
  3. Petersen RC: Mild cognitive impairment as a diagnostic entity. J Intern Med 2004;256:183–194.
  4. Stephan BC, Matthews FE, McKeith IG, Bond J, Brayne C, Medical Research Council Cognitive Function and Aging Study: Early cognitive change in the general population: how do different definitions work? J Am Geriatr Soc 2007;55:1534–1540.
  5. Weintraub S, Salmon D, Mercaldo N, Ferris S, Graff-Radford NR, Chui H, Cummings J, DeCarli C, Foster NL, Galasko D, Peskind E, Dietrich W, Beekly DL, Kukull WA, Morris JC: The Alzheimer’s Disease Centers’ Uniform Data Set (UDS): the neuropsychologic test battery. Alzheimer Dis Assoc Disord 2009;23:91–101.
  6. Geisser S: The predictive sample reuse method with applications. J Am Stat Assoc 1975;70:320–328.
    External Resources
  7. Stone M: Cross-validatory choice and assessment of statistical predictions. J R Stat Soc Series B Stat Methodol 1974;36:111–147.
    External Resources
  8. Steyerberg EW, Harrell FE Jr, Borsboom GJ, Eijkemans MJ, Vergouwe Y, Habbema JD: Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol 2001;54:774–781.
  9. Little J, Rubin D: Statistical Analysis with Missing Data, ed 2. Hoboken, Wiley, 2002.
  10. Van Buuren S, Oudshoorn C: Mice: multivariate imputation by chained equations. R package version 1.16. 2007.
  11. R Core Development Team: R: A Language and Environment for Statistical Computing. Vienna, R Foundation for Statistical Computing, 2008.

Article / Publication Details

First-Page Preview
Abstract of Original Paper

Received: August 13, 2009
Accepted: December 19, 2009
Published online: April 02, 2010
Issue release date: July 2010

Number of Print Pages: 9
Number of Figures: 2
Number of Tables: 5

ISSN: 0251-5350 (Print)
eISSN: 1423-0208 (Online)

For additional information: https://www.karger.com/NED

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