Derivation of a New ADAS-cog Composite Using Tree-based Multivariate Analysis

Llano, Daniel A.; Laforet, Genevieve; Devanarayan, Viswanath

doi:10.1097/wad.0b013e3181f5b8d8

Cited by 61 publications

(62 citation statements)

References 36 publications

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“…It also incorporates principle component methodology to account for item correlation. Related methodologies to produce composite scores have been successfully applied including the ADAS Tree (32) and ADAS-cog revisited (33). …”

Section: Discussionmentioning

confidence: 99%

Methodological Aspects of the Phase Ii Study Aff006 Evaluating Amyloid-Beta -Targeting Vaccine Affitope® Ad02 in Early Alzheimer’s Disease – Prospective Use of Novel Composite Scales

et al. 2015

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BACKGROUND: Optimized scales and composite outcomes have been proposed as a way to more accurately measure Alzheimer’s disease related decline. AFFITOPE® AD02, is an amyloid-beta (Aβ)-targeting vaccine to elicit anti-Aβ antibodies. IMM-AD04, commonly known as Alum, originally designated as a control agent, appeared to have disease-modifying activity in a multicenter, parallel group phase II study in early AD patients. OBJECTIVES: To develop adapted outcomes for cognition, function and a composite scale with improved sensitivity to decline and treatment effects in early AD (mild plus prodromal AD) based on historical data and to assess these adapted outcomes in this phase II study. DESIGN: Data from public datasets was analyzed using a partial least squares model in order to identify an optimally weighted cognitive outcome, Adapted ADAS-cog, and an optimally weighted ADL outcome, Adapted ADCS-ADL which were prospectively defined as co-primary endpoints for the study and were also combined into a composite scale. Data from 162 patients in the placebo groups of ADCS studies and 156 mild patients in the ADNI I study were pooled for this analysis. The Adapted ADAS-cog scale considered 13 ADAS-cog items as well as several Neuropsychological test items and CogState items, the Adapted ADCS-ADL considered all ADCS-ADL items. After the pre-specified analyses were complete, additional adapted and composite scales were investigated in a post-hoc manner. Evaluation of the adapted and composite scales was performed on Phase II trial data for AFFITOPE® AD02 (AFF006, Clinical Trial Identifier: NCT01117818) and historic data in early AD. Least square means, standard deviations, and least squares mean to standard deviation ratios were compared among adapted and composite scales and traditional scales for the 5 treatment groups in the phase II study and overall for the historic data. Treatment effect sizes and p-values were also compared for the phase II study. RESULTS: Cognitive items that were selected for the adapted cognitive scale (aADAS-cog) and had the highest weights were Word Recall, Word Recognition, and Orientation. Delayed Word Recall and Digit Cancellation were among the items excluded due to lack of improved sensitivity to decline. Highly weighted ADL items included in the adapted functional scale (aADCS-ADL) were using the telephone, traveling, preparing a meal/snack, selecting clothing, shopping and using appliances. Excluded items were primarily basic ADLs such as eating, walking, toileting and bathing. Comparisons between traditional scales and primary outcome adapted scales show improved sensitivity to group differences with the adapted scales in the phase II trial. Most of the improvement in the sensitivity of the aADAS-cog and the aADCS-ADL is due to a larger treatment difference observed rather than the improved sensitivity to decline in the comparison groups. CONCLUSION: To our knowledge, this is the first study to prospectively use optimized scales as primary endpoints and to demonstrate the superior power of optimized scales and composites in early disease. Although it is possible that the treatment difference between randomized groups is due to a factor other than the treatment itself, for instance baseline imbalance, the improved power to detect these differences still argues in favor of the adapted scales. The issue of oversensitivity to detect treatment effects is controlled by selection of the alpha level for significance, and in our case will happen less than 5% of the time. Clinical relevance of the treatment difference should be assessed separately from statistical significance, and in this phase II study, is supported by significant or similar sizes of effect on function, behaviour and quality of life outcomes, which are important to patients and caregivers.

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Section: Discussionmentioning

confidence: 99%

Methodological Aspects of the Phase Ii Study Aff006 Evaluating Amyloid-Beta -Targeting Vaccine Affitope® Ad02 in Early Alzheimer’s Disease – Prospective Use of Novel Composite Scales

et al. 2015

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“…For instance, we observed that CDR-sum score increased at a steeper rate compared to the index. Thus, to overcome this limitation, it has been proposed to create richer cognitive distributions by constructing novel composite scores employing machine learning algorithms, that are able to predict conversion from MCI to AD better than standard cognitive scores (Llano et al, 2011). …”

Section: Discussionmentioning

confidence: 99%

Application of a MRI based index to longitudinal atrophy change in Alzheimer disease, mild cognitive impairment and healthy older individuals in the AddNeuroMed cohort

Aguilar

Mecocci

Vellas

et al. 2014

Front. Aging Neurosci.

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Cross sectional studies of patients at risk of developing Alzheimer disease (AD) have identified several brain regions known to be prone to degeneration suitable as biomarkers, including hippocampal, ventricular, and whole brain volume. The aim of this study was to longitudinally evaluate an index based on morphometric measures derived from MRI data that could be used for classification of AD and healthy control subjects, as well as prediction of conversion from mild cognitive impairment (MCI) to AD. Patients originated from the AddNeuroMed project at baseline (119 AD, 119 MCI, 110 controls (CTL)) and 1-year follow-up (62 AD, 73 MCI, 79 CTL). Data consisted of 3D T1-weighted MR images, demographics, MMSE, ADAS-Cog, CERAD and CDR scores, and APOE e4 status. We computed an index using a multivariate classification model (AD vs. CTL), using orthogonal partial least squares to latent structures (OPLS). Sensitivity, specificity and AUC were determined. Performance of the classifier (AD vs. CTL) was high at baseline (10-fold cross-validation, 84% sensitivity, 91% specificity, 0.93 AUC) and at 1-year follow-up (92% sensitivity, 74% specificity, 0.93 AUC). Predictions of conversion from MCI to AD were good at baseline (77% of MCI converters) and at follow-up (91% of MCI converters). MCI carriers of the APOE e4 allele manifested more atrophy and presented a faster cognitive decline when compared to non-carriers. The derived index demonstrated a steady increase in atrophy over time, yielding higher accuracy in prediction at the time of clinical conversion. Neuropsychological tests appeared less sensitive to changes over time. However, taking the average of the two time points yielded better correlation between the index and cognitive scores as opposed to using cross-sectional data only. Thus, multivariate classification seemed to detect patterns of AD changes before conversion from MCI to AD and including longitudinal information is of great importance.

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“…Llano et al [96] developed a cognitive test based on ADAS-cog as an alternative to imaging or CSF biomarkers for use as an outcome measure or for subject enrichment in clinical trials. The ADAS.Tree composite was derived by weighting test components of ADAS-cog based on their ability to discriminate between control, MCI, and AD subjects of the ADNI cohort using a Random Forests tree-based algorithm.…”

Section: Methods Papersmentioning

confidence: 99%

“…Llano et al [96] compared the ADAS-cog and MMSE tests with a new form of ADAS-cog in which the subscores were given weights using a Random Forests tree algorithm, thereby resulting in a new metric, the composite ADAS.Tree. Therefore, ADAS.Tree represents a multivariate model in which subscales have been weighted according to their importance in discriminating between AD and control subjects.…”

Section: Studies Of the Adni Cohortmentioning

confidence: 99%

“…Llano et al [96] used a new Random Forests tree-based multivariate model of ADAS-cog in which the subscores had been weighted according to their contribution to patient discrimination. This model, ADAS.Tree, predicted conversion of MCI to AD more accurately than baseline MMSE or ADAS-cog and, in addition, was a better predictor of conversion than the best single imaging (left inferior temporal cortex), metabolism (left precuneus), or CSF (p-tau 181p /Aβ-42) biomarkers.…”

Section: Studies Of the Adni Cohortmentioning

confidence: 99%

See 1 more Smart Citation

The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Weiner

Veitch

Aisen

et al. 2013

Alzheimer's & Dementia

664

428

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The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151–3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [18F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and ...

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Derivation of a New ADAS-cog Composite Using Tree-based Multivariate Analysis

Cited by 61 publications

References 36 publications

Methodological Aspects of the Phase Ii Study Aff006 Evaluating Amyloid-Beta -Targeting Vaccine Affitope® Ad02 in Early Alzheimer’s Disease – Prospective Use of Novel Composite Scales

Methodological Aspects of the Phase Ii Study Aff006 Evaluating Amyloid-Beta -Targeting Vaccine Affitope® Ad02 in Early Alzheimer’s Disease – Prospective Use of Novel Composite Scales

Application of a MRI based index to longitudinal atrophy change in Alzheimer disease, mild cognitive impairment and healthy older individuals in the AddNeuroMed cohort

The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

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