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An updated Alzheimer’s disease progression model: incorporating non-linearity, beta regression, and a third-level random effect in NONMEM

Journal of Pharmacokinetics and Pharmacodynamics volume 41, pages 581–598 (2014)Cite this article

Abstract

Our objective was to expand our understanding of the predictors of Alzheimer’s disease (AD) progression to help design a clinical trial on a novel AD medication. We utilized the Coalition Against Major Diseases AD dataset consisting of control-arm data (both placebo and stable background AD medication) from 15 randomized double-blind clinical trials in mild-to-moderate AD patients (4,495 patients; July 2013). Our ADAS-cog longitudinal model incorporates a beta-regression with between-study, -subject, and -residual variability in NONMEM; it suggests that faster AD progression is associated with younger age and higher number of apolipoprotein E type 4 alleles (APOE*4), after accounting for baseline disease severity. APOE*4, in particular, seems to be implicated in the AD pathogenesis. In addition, patients who are already on stable background AD medications appear to have a faster progression relative to those who are not receiving AD medication. The current knowledge does not support a causality relationship between use of background AD medications and higher rate of disease progression, and the correlation is potentially due to confounding covariates. Although causality has not necessarily been demonstrated, this model can inform inclusion criteria and stratification, sample size, and trial duration.

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Acknowledgments

The authors would like to thank Dr. Mahesh Samtani (Johnson and Johnson Pharmaceutical Research and Development) for his technical guidance and invaluable input in conducting the analysis. The authors would also like to acknowledge CAMD database management team to provide the assembled dataset and to respond authors’ queries. All authors are employees of Pfizer Inc.

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Author notes

  1. Daniela J. Conrado

    Present address: Pfizer Global Innovative Pharma Business, Pfizer Inc., 445 Eastern Point Road, Groton, CT, 06340, USA

Authors and Affiliations

  1. Pharmatherapeutics Clinical Pharmacology, Pfizer Inc., Cambridge, MA, 02139, USA

    Daniela J. Conrado, William S. Denney & Danny Chen

  2. Pfizer Global Innovative Pharma Business, Pfizer Inc., 445 Eastern Point Road, Groton, CT, 06340, USA

    Kaori Ito

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  1. Daniela J. Conrado
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Corresponding author

Correspondence to Daniela J. Conrado.

Additional information

The Coalition Against Major Diseases: Data used in preparation of this article were obtained from the Coalition Against Major Diseases (CAMD) database (http://codr.c-path.org). A complete listing of CAMD members can be found at: http://c-path.org/programs/camd/.

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Supplementary material 1 (DOCX 515 kb)

Appendix: NONMEM 7.3 code for final model

Appendix: NONMEM 7.3 code for final model

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Conrado, D.J., Denney, W.S., Chen, D. et al. An updated Alzheimer’s disease progression model: incorporating non-linearity, beta regression, and a third-level random effect in NONMEM. J Pharmacokinet Pharmacodyn 41, 581–598 (2014). https://doi.org/10.1007/s10928-014-9375-z

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  • DOI: https://doi.org/10.1007/s10928-014-9375-z

Keywords

  • Alzheimer’s disease
  • Disease progression
  • Patient-level model-based meta-analysis
  • Coalition Against Major Diseases (CAMD)
  • ADAS-cog
  • NONMEM