Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-16T22:23:19.276Z Has data issue: false hasContentIssue false
  • English
  • Français

Statistical analysis, trial design and duration in Alzheimer's disease clinical trials: a review

Published online by Cambridge University Press:  13 September 2011

P. A. Thompson ,
D. E. Wright ,
C. E. Counsell  and
J. Zajicek
P. A. Thompson*
Affiliation:
Centre for Health and Environmental Statistics, University of Plymouth, Plymouth, UK
D. E. Wright
Affiliation:
Centre for Health and Environmental Statistics, University of Plymouth, Plymouth, UK
C. E. Counsell
Affiliation:
University of Aberdeen, Division of Applied Health Sciences, Foresterhill, Aberdeen, UK
J. Zajicek
Affiliation:
Peninsula College of Medicine and Dentistry, Plymouth, UK
*
Correspondence should be addressed to: Dr Paul Thompson, Centre for Health and Environmental Statistics, University of Plymouth, ITTC Building Tamar, Science Park, Davy Road, Derriford, Plymouth, PL6 8BX. Email: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

Background: The social and economic burden of Alzheimer's disease (AD) and its increasing prevalence has led to much work on new treatment strategies and clinical trials. The search for surrogate markers of disease progression continues but traditional parallel group trial designs that use well-established, but often insensitive, clinical outcome measures predominate.

Methods: We performed a systematic search across the Cochrane Library and PubMed abstracts published between January 2004 and August 2009. Information regarding the clinical trial methodology, outcome measures, intervention type and primary statistical analysis techniques was extracted and categorized, according to a standard protocol.

Results: We identified 149 papers describing results from clinical trials in AD containing sufficient detail for our purposes. The largest proportion (38%) presented results of trials based on tests of cognition as the primary outcome measure. The primary analysis in most papers (85%) was a univariate significance test of a single primary outcome measure.

Conclusions: The majority of trials reported a comparison of baseline and end-point assessment over relatively short patient follow-up periods, using univariate statistical methods to compare differences between intervention and control groups in the primary analysis. There is considerable scope to introduce newer statistical methods and trial designs in treatment evaluations in AD.

Keywords

Alzheimer's diseaseclinical trialsstatistical analysissurrogate markersoutcome measures
Type
Review Article
Information
International Psychogeriatrics , Volume 24 , Issue 5 , May 2012 , pp. 689 - 697
Copyright
Copyright © International Psychogeriatric Association 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Apostolova, L. G. et al. (2006). 3D mapping of Mini-Mental State Examination performance in clinical and preclinical Alzheimer's disease. Alzheimer Disease and Associated Disorders, 20, 224–231.CrossRefGoogle Scholar
Craig-Schapiro, R., Fagan, A. M. and Holtzman, D. M. (2009). Biomarkers of Alzheimer's disease. Neurobiology of Disease, 35, 128–140.CrossRefGoogle ScholarPubMed
Dubois, B. et al. (2010). Revising the definition of Alzheimer's disease: a new lexicon. Lancet Neurology, 9, 1118–1127.CrossRefGoogle ScholarPubMed
Fox, N. C., Scahill, R. I., Crum, W. R. and Rosser, M. N. (1999). Correlation between rates of brain atropy and cognitive decline in AD. Neurology, 52, 1687.Google Scholar
Hampel, H., Bürgerb, K., Teipel, S. J., Bokdea, A. L.W., Zetterberg, H. and Blennow, K. (2008). Core candidate neurochemical and imaging biomarkers of Alzheimer's disease. Alzheimer's and Dementia, 4, 38–48.Google Scholar
Hanyu, H. M., Sakurai, H., Iwamoto, T., Takaski, M., Shindo, H., and Abe, K. (1998). Diffusion weighted MR imaging of hippocampus and temporal white matter in Alzheimer's disease. Journal of Neurological Sciences, 156, 195–200.CrossRefGoogle ScholarPubMed
Higgins, J. P. T. and Green, S. (eds.) (2008). Cochrane Handbook for Systematic Reviews of Interventions (Version 5.0.1), The Cochrane Collaboration, available from www.cochrane-handbook.org.Google Scholar
Hobart, J., Posner, H., Aisen, P., Selnes, O., Stern, Y., Thomas, R., Weiner, M. and Zajicek, J. (2009). The ADAS-Cog's performance as a measure: lessons from the ADNI study: Part 3 – Do the scale modifications add value? Alzheimer's and Dementia, 5 (Suppl.), 256.Google Scholar
Mendiondo, M., Wesson Ashford, J., Kryscio, R. J. and Schmitt, F. A. (2000). Modelling Mini-Mental State Examination changes in Alzheimer's disease. Statistics in Medicine, 19, 1607–1616.Google Scholar
Moher, D. et al. (2010). CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trial. BMJ, 340, 869.Google Scholar
Molnar, F. J., Man-Son-Hing, M. and Fergusson, D. (2009). Systematic review of measures of clinical significance employed in randomized controlled trials of drugs for dementia. Journal of the American Geriatrics Society, 57, 536–546.Google Scholar
Nestor, P. J., Scheltens, P. and Hodges, J. R. (2004). Advances in early detection of Alzheimer's disease. Nature Reviews: Neuroscience, 5, S34–S41.Google Scholar
Pocock, S. J., Geller, N. L. and Tsiatis, A. A. (1987). The analysis of multiple endpoints in clinical trials. Biometrics, 43, 487–498.Google Scholar
Rencher, A. C. (2002). Methods of Multivariate Analysis, New York: Wiley Interscience.Google Scholar
Skrondal, A. and Rabe-Hesketh, S. (2004). Generalized Latent Variable Modeling: Multilevel, Longitudinal and Structural Equation Models. London: Chapman and Hall/CRC.Google Scholar
Tang, D., Geller, N. L. and Pocock, S. J. (1993). On the design and analysis of randomised clinical trials with multiple endpoints. Biometrics, 49, 23–30.CrossRefGoogle ScholarPubMed
Upton, G. and Cook, I. (2008). Oxford Dictionary of Statistics (2nd edn). Oxford: Oxford University Press.Google Scholar
Wolfson, C., Moride, Y., Perrault, A., Momoli, F., Demers, L. and Oremus, M. (2000). Drug Treatments for Alzheimer's Disease II. A Review of Outcome Measures in Clinical Trials. Ottawa: Canadian Coordinating Office for Health Technology Assessment (CCOHTA).Google Scholar
Woodford, H. J. and George, J. (2007). Cognitive assessment in the elderly: a review of clinical methods. QJM: An International Journal of Medicine, 100, 469–484.CrossRefGoogle ScholarPubMed
Zhang, J., Quan, H., Ng, J. and Stepanavage, M. E. (1997). Some statistical methods for multiple endpoints in clinical trials. Controlled Clinical Trials, 18, 204–221.CrossRefGoogle ScholarPubMed