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Stat Med. 2018 Sep 20;37(21):3047-3055. doi: 10.1002/sim.7811. Epub 2018 May 14.

A novel cognitive disease progression model for clinical trials in autosomal-dominant Alzheimer's disease.

Author information

1
Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA.
2
Berry Consultants, Austin, TX, USA.
3
Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
4
F. Hoffmann-La Roche Ltd., Basel, Switzerland.
5
Department of Statistics and Data Sciences, University of Texas at Austin, Austin, TX, USA.
6
Lilly Research Laboratories, Indianapolis, IN, USA.

Abstract

Clinical trial outcomes for Alzheimer's disease are typically analyzed by using the mixed model for repeated measures (MMRM) or similar models that compare an efficacy scale change from baseline between treatment arms with or without participants' disease stage as a covariate. The MMRM focuses on a single-point fixed follow-up duration regardless of the exposure for each participant. In contrast to these typical models, we have developed a novel semiparametric cognitive disease progression model (DPM) for autosomal dominant Alzheimer's disease based on the Dominantly Inherited Alzheimer Network (DIAN) observational study. This model includes 3 novel features, in which the DPM (1) aligns and compares participants by disease stage, (2) uses a proportional treatment effect similar to the concept of the Cox proportional hazard ratio, and (3) incorporates extended follow-up data from participants with different follow-up durations using all data until last participant visit. We present the DPM model developed by using the DIAN observational study data and demonstrate through simulation that the cognitive DPM used in hypothetical intervention clinical trials produces substantial gains in power compared with the MMRM.

KEYWORDS:

Alzheimer's disease; disease progression model; mixed effects model for repeated measures; proportional treatment effect

PMID:
29761523
PMCID:
PMC6105413
[Available on 2019-09-20]
DOI:
10.1002/sim.7811

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