Reduced sample sizes for atrophy outcomes in Alzheimer's disease trials: Baseline adjustment

Dementia Research Centre, Institute of Neurology, UCL, London WC1N 3BG, UK.
Neurobiology of aging (Impact Factor: 5.01). 08/2010; 31(8):1452-62, 1462.e1-2. DOI: 10.1016/j.neurobiolaging.2010.04.011
Source: PubMed


Cerebral atrophy rate is increasingly used as an outcome measure for Alzheimer's disease (AD) trials. We used the Alzheimer's disease Neuroimaging initiative (ADNI) dataset to assess if adjusting for baseline characteristics can reduce sample sizes. Controls (n = 199), patients with mild cognitive impairment (MCI) (n = 334) and AD (n = 144) had two MRI scans, 1-year apart; approximately 55% had baseline CSF tau, p-tau, and Abeta1-42. Whole brain (KN-BSI) and hippocampal (HMAPS-HBSI) atrophy rate, and ventricular expansion (VBSI) were calculated for each group; numbers required to power a placebo-controlled trial were estimated. Sample sizes per arm (80% power, 25% absolute rate reduction) for AD were (95% CI): brain atrophy = 81 (64,109), hippocampal atrophy = 88 (68,119), ventricular expansion = 118 (92,157); and for MCI: brain atrophy = 149 (122,188), hippocampal atrophy = 201 (160,262), ventricular expansion = 234 (191,295). To detect a 25% reduction relative to normal aging required increased sample sizes approximately 3-fold (AD), and approximately 5-fold (MCI). Disease severity and Abeta1-42 contributed significantly to atrophy rate variability. Adjusting for 11 predefined covariates reduced sample sizes by up to 30%. Treatment trials in AD should consider the effects of normal aging; adjusting for baseline characteristics can significantly reduce required sample sizes.

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    • "Beyond the standardization of methods and data sets, MRI studies carried out with the ADNI cohort have impacted clinical trials in a number of ways. Fox and coworkers developed improved methods for measuring the rate of atrophy across multiple sites and for reducing required sample sizes [39] [40] [41], and also developed automated methods to measure brain and hippocampal volume and rates of atrophy [39] [42] [43]. These have been incorporated into large commercial clinical trials and submitted to the European Medicines Agency, leading to guidance on hippocampal volume measurement in trials [24]. "
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    ABSTRACT: The Alzheimer's Disease Neuroimaging Initiative (ADNI) was established in 2004 to facilitate the development of effective treatments for Alzheimer's disease (AD) by validating biomarkers for AD clinical trials. We searched for ADNI publications using established methods. ADNI has (1) developed standardized biomarkers for use in clinical trial subject selection and as surrogate outcome measures; (2) standardized protocols for use across multiple centers; (3) initiated worldwide ADNI; (4) inspired initiatives investigating traumatic brain injury and post-traumatic stress disorder in military populations, and depression, respectively, as an AD risk factor; (5) acted as a data-sharing model; (6) generated data used in over 600 publications, leading to the identification of novel AD risk alleles, and an understanding of the relationship between biomarkers and AD progression; and (7) inspired other public-private partnerships developing biomarkers for Parkinson's disease and multiple sclerosis. ADNI has made myriad impacts in its first decade. A competitive renewal of the project in 2015 would see the use of newly developed tau imaging ligands, and the continued development of recruitment strategies and outcome measures for clinical trials. Copyright © 2015 The Alzheimer's Association. All rights reserved.
    Alzheimer's & dementia: the journal of the Alzheimer's Association 07/2015; 11(7):865-84. DOI:10.1016/j.jalz.2015.04.005 · 12.41 Impact Factor
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    • "Sample size calculation depends on the size of the effect and the measurement error of the outcome. For example, in one study, detection of 25% clinical slowing in mild AD with 80% power was shown to require 81 patients per arm if whole-brain atrophy was used as the trial outcome, 88 patients if hippocampal volume loss was the outcome, and 118 patients if ventricular outcome was used [26]. 2. Screening. "
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    ABSTRACT: Atrophy in the medial temporal lobe (MTA) is being used as a criterion to support a diagnosis of Alzheimer’s disease (AD). There are several structural neuroimaging approaches for quantifying MTA, including semiquantitative visual rating scales, volumetry (3D), planimetry (2D) and linear measures (1D). Current applications of structural neuroimaging in Alzheimer’s disease clinical trials (ADCTs) incorporate it as a tool for improving the selection of subjects for enrollment or for stratification, for tracking disease progression or providing evidence of target engagement for new therapeutic agents. It may also be used as a surrogate marker, providing evidence of disease-modifying effects. However, despite the widespread use of volumetric magnetic resonance imaging (MRI) in ADCTs, there are some important challenges and limitations, such as difficulties in the interpretation of results, limitations in translating results into clinical practice and reproducibility issues, among others. Solutions to these issues may arise from other methodologies that are able to link the results of volumetric MRI from trials with conventional MRIs performed in routine clinical practice (linear or planimetric methods). Also of potential benefit are automated volumetry, using indices for comparing the relative rate of atrophy of different regions instead of absolute rates of atrophy, and combining structural neuroimaging with other biomarkers. In this review, authors present the existing structural neuroimaging approaches for MTA quantification. They then discuss solutions to the limitations of the different techniques as well as the current challenges of the field. Finally and due to their relevance, they discuss how the current advances in AD neuroimaging can help AD diagnosis.
    Journal of Alzheimer's disease: JAD 06/2015; DOI:10.3233/JAD-150226 · 4.15 Impact Factor
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    • "Using these biomarkers as outcome measures in trials would also have the potential to show a disease modifying effect on fewer subjects than standard cognitive tests, with proper enrichment strategies making these useful for predementia trials. (Grill et al., 2013; Schott et al., 2010). "
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    ABSTRACT: Brain atrophy measured using structural MRI has been widely used as an imaging biomarker for disease diagnosis and tracking of pathological progression in neurodegenerative diseases. In this work, we present a generalised and extended formulation of the Boundary Shift Integral (gBSI) using probabilistic segmentations in order to estimate anatomical changes between 2 time points. This method adaptively estimates a non-binary XOR region-of-interest from probabilistic brain segmentations of the baseline and repeat scans, in order to better localise and capture the brain atrophy. We evaluate the proposed method by comparing the sample size requirements for a hypothetical clinical trial of Alzheimer’s disease to that needed for the current implementation of BSI as well as a fuzzy implementation of BSI. The gBSI method results in a modest, but reduced sample size, providing increased sensitivity to disease changes through the use of the probabilistic XOR region.
    Neurobiology of Aging 08/2014; 36(Suppl 1). DOI:10.1016/j.neurobiolaging.2014.04.035 · 5.01 Impact Factor
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