Finding Treatment Effects in Alzheimer Trials in the Face of Disease Progression Heterogeneity
- PMID: 34550903
- PMCID: PMC8205463
- DOI: 10.1212/WNL.0000000000012022
Finding Treatment Effects in Alzheimer Trials in the Face of Disease Progression Heterogeneity
Abstract
Objective: To investigate the influence of heterogeneity in disease progression for detecting treatment effects in Alzheimer disease (AD) trials, using a simulation study.
Methods: Individuals with an abnormal amyloid PET scan, diagnosis of mild cognitive impairment or dementia, baseline Mini-Mental State Examination (MMSE) score ≥24, global Clinical Dementia Rating (CDR) score of 0.5, and ≥1 follow-up cognitive assessment were selected from the Alzheimer's Disease Neuroimaging Initiative database (n = 302, age 73 ± 6.7; 44% female; 16.1 ± 2.7 years of education; 69% APOE ε4 carrier). We simulated a clinical trial by randomly assigning individuals to a "placebo" and "treatment" group and subsequently computed group differences on the CDR-sum of boxes (CDR-SB), Alzheimer's Disease Assessment Scale-cognitive subscale-13 and MMSE after 18 months follow-up. We repeated this simulation 10,000 times to determine the 95% range of effect sizes. We further studied the influence of known AD risk factors (age, sex, education, APOE ε4 status, CSF total tau levels) on the variability in effect sizes.
Results: Individual trajectories on all cognitive outcomes were highly variable, and the 95% ranges of possible effect sizes at 18 months were broad (e.g., ranging from 0.35 improvement to 0.35 decline on the CDR-SB). Results of recent anti-amyloid trials mostly fell within these 95% ranges of effect sizes. APOE ε4 carriers and individuals with abnormal baseline tau levels showed faster decline at group level, but also greater within-group variability, as illustrated by broader 95% effect size ranges (e.g., ±0.70 points for the CDR-SB).
Conclusions: Individuals with early AD show heterogeneity in disease progression, which increases when stratifying on risk factors associated with progression. We provide guidance for a priori effect sizes on cognitive outcomes for detecting true change, which is crucial for future AD trials.
Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.
Figures
Comment in
-
Cognitive Heterogeneity in Alzheimer Clinical Trials: Harnessing Noise to Achieve Meaningfulness.Neurology. 2021 Jun 1;96(22):1017-1018. doi: 10.1212/WNL.0000000000012027. Neurology. 2021. PMID: 34550902 No abstract available.
Similar articles
-
Longitudinal Neuropsychological Outcome in Taiwanese Alzheimer's Disease Patients Treated with Medication.Curr Alzheimer Res. 2018 Mar 14;15(5):474-481. doi: 10.2174/1567205014666171010112518. Curr Alzheimer Res. 2018. PMID: 29032750
-
Characterizing Clinical Progression in Cognitively Unimpaired Older Individuals with Brain Amyloid: Results from the A4 Study.J Prev Alzheimers Dis. 2024;11(4):814-822. doi: 10.14283/jpad.2024.123. J Prev Alzheimers Dis. 2024. PMID: 39044489 Free PMC article. Clinical Trial.
-
Effect of apolipoprotein E ε4 allele on the progression of cognitive decline in the early stage of Alzheimer's disease.Alzheimers Dement (N Y). 2020 Mar 20;6(1):e12007. doi: 10.1002/trc2.12007. eCollection 2020. Alzheimers Dement (N Y). 2020. PMID: 32211510 Free PMC article.
-
Efficacy and safety of anti-amyloid-β monoclonal antibodies in current Alzheimer's disease phase III clinical trials: A systematic review and interactive web app-based meta-analysis.Ageing Res Rev. 2023 Sep;90:102012. doi: 10.1016/j.arr.2023.102012. Epub 2023 Jul 7. Ageing Res Rev. 2023. PMID: 37423541 Review.
-
Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative.Alzheimers Dement. 2019 Jan;15(1):106-152. doi: 10.1016/j.jalz.2018.08.005. Epub 2018 Oct 13. Alzheimers Dement. 2019. PMID: 30321505 Review.
Cited by
-
Individualized and Biomarker-Based Prognosis of Longitudinal Cognitive Decline in Early Symptomatic Alzheimer's Disease.J Alzheimers Dis Rep. 2024 Sep 27;8(1):1301-1315. doi: 10.3233/ADR-240049. eCollection 2024. J Alzheimers Dis Rep. 2024. PMID: 39434814 Free PMC article.
-
Baseline multimodal imaging to predict longitudinal clinical decline in atypical Alzheimer's disease.Cortex. 2024 Nov;180:18-34. doi: 10.1016/j.cortex.2024.07.020. Epub 2024 Sep 11. Cortex. 2024. PMID: 39305720
-
Characterizing the clinical heterogeneity of early symptomatic Alzheimer's disease: a data-driven machine learning approach.Front Aging Neurosci. 2024 Aug 12;16:1410544. doi: 10.3389/fnagi.2024.1410544. eCollection 2024. Front Aging Neurosci. 2024. PMID: 39193492 Free PMC article.
-
TMS-derived short afferent inhibition discriminates cognitive status in older adults without dementia.Aging Brain. 2024 Jul 19;6:100123. doi: 10.1016/j.nbas.2024.100123. eCollection 2024. Aging Brain. 2024. PMID: 39132326 Free PMC article.
-
Serial Cerebrospinal Fluid Sampling Reveals Trajectories of Potential Synaptic Biomarkers in Early Stages of Alzheimer's Disease.J Alzheimers Dis. 2024;100(s1):S103-S114. doi: 10.3233/JAD-240610. J Alzheimers Dis. 2024. PMID: 39121126 Free PMC article.
References
-
- Food and Drug Administration. Early Alzheimer's Disease: Developing Drugs for Treatment: Guidance for Industry. Food and Drug Administration; 2018.
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Medical
Miscellaneous