Gaining precision on the Alzheimer's Disease Assessment Scale‐cognitive: A comparison of item response theory‐based scores and total scores

Balsis, Steve; Unger, Alexis A.; Benge, Jared F.; Geraci, Lisa; Doody, Rachelle S.

doi:10.1016/j.jalz.2011.05.2409

Cited by 34 publications

(34 citation statements)

References 15 publications

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“…Better quantification of disease severity will also improve our assessment of disease progression and treatment effect. Comparable results were obtained for ADAScog score in Alzheimer's disease (11).…”

Section: Discussionsupporting

confidence: 58%

“…Traditional scoring consists of summarizing all the information in one composite score, which might lead to loss of information captured in the individual item. The recent application of IRT to Alzheimer's disease has demonstrated that increased precision in cognitive assessment can be achieved by not only considering scores on item level, but also how those items function and the amount of information they contain for the studied population (11,12).…”

Section: Introductionmentioning

confidence: 99%

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Application of Item Response Theory to Modeling of Expanded Disability Status Scale in Multiple Sclerosis

Novakovic

Krekels

Munafo

et al. 2016

AAPS J

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ABSTRACT.In this study, we report the development of the first item response theory (IRT) model within a pharmacometrics framework to characterize the disease progression in multiple sclerosis (MS), as measured by Expanded Disability Status Score (EDSS). Data were collected quarterly from a 96-week phase III clinical study by a blinder rater, involving 104,206 item-level observations from 1319 patients with relapsing-remitting MS (RRMS), treated with placebo or cladribine. Observed scores for each EDSS item were modeled describing the probability of a given score as a function of patients' (unobserved) disability using a logistic model. Longitudinal data from placebo arms were used to describe the disease progression over time, and the model was then extended to cladribine arms to characterize the drug effect. Sensitivity with respect to patient disability was calculated as Fisher information for each EDSS item, which were ranked according to the amount of information they contained. The IRT model was able to describe baseline and longitudinal EDSS data on item and total level. The final model suggested that cladribine treatment significantly slows disease-progression rate, with a 20% decrease in disease-progression rate compared to placebo, irrespective of exposure, and effects an additional exposure-dependent reduction in disability progression. Four out of eight items contained 80% of information for the given range of disabilities. This study has illustrated that IRT modeling is specifically suitable for accurate quantification of disease status and description and prediction of disease progression in phase 3 studies on RRMS, by integrating EDSS item-level data in a meaningful manner.

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Section: Discussionsupporting

confidence: 58%

Section: Introductionmentioning

confidence: 99%

Application of Item Response Theory to Modeling of Expanded Disability Status Scale in Multiple Sclerosis

Novakovic

Krekels

Munafo

et al. 2016

AAPS J

View full text Add to dashboard Cite

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“…IRT is a statistical framework consisting of mathematical models that describe the relationship between an individual's underlying latent (or hidden) variable to the pattern of responses to the items on the assessment scale and such a relationship is described by the Item Characteristic Curves (ICC). The recent application of the IRT methodology in Alzheimer's disease (9)(10)(11), where it was shown to be a more advantageous approach than the traditional analysis of the composite score because of an improved utilization of the data at an individual item level, was later applied and further explored in other disease areas such as multiple sclerosis (12) and schizophrenia (13) In this manuscript, we aimed to further the understanding of the disease progression characteristics in PD by describing the longitudinal changes in the MDS-UPDRS data using the IRT approach.…”

Section: Introductionmentioning

confidence: 99%

Modeling a Composite Score in Parkinson’s Disease Using Item Response Theory

Gottipati

Karlsson

Plan

2017

AAPS J

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Abstract.In the current work, we present the methodology for development of an Item Response Theory model within a non-linear mixed effects framework to characterize the longitudinal changes of the Movement Disorder Society (sponsored revision) of Unified Parkinson's Disease Rating Scale (MDS-UPDRS) endpoint in Parkinson's disease (PD). The data were obtained from Parkinson's Progression Markers Initiative database and included 163,070 observations up to 48 months from 430 subjects belonging to De Novo PD cohort. The probability of obtaining a score, reported for each of the items in the questionnaire, was modeled as a function of the subject's disability. Initially, a single latent variable model was explored to characterize the disease progression over time. However, based on the understanding of the questionnaire set-up and the results of a residuals-based diagnostic tool, a three latent variable model with a mixture implementation was able to adequately describe longitudinal changes not only at the total score level but also at each individual item level. The linear progression rates obtained for the patient-reported items and the non-sided items were similar, each of which roughly take about 50 months for a typical subject to progress linearly from the baseline by one standard deviation. However for the sided items, it was found that the better side deteriorates quicker than the disabled side. This study presents a framework for analyzing MDS-UPDRS data, which can be adapted to more traditional UPDRS data collected in PD clinical trials and result in more efficient designs and analyses of such studies.

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“…These approaches are not necessarily mutually exclusive; for instance, theoretical knowledge of preclinical AD can be taken into account when empirically deriving a composite cognitive test score. Several different analyses methods are available to developing composites, including but not limited to latent variable analyses or partial least squares regression (29–31), principal components (32), item-response theory (33), Rasch Measurement Theory (34) or item-level analysis (35). While there have been some efforts focused on refining existing cognitive assessments, this may be best suited for MCI and early AD trials (36).…”

Section: Introductionmentioning

confidence: 99%

An empirically derived composite cognitive test score with improved power to track and evaluate treatments for preclinical Alzheimer's disease

Langbaum¹,

Hendrix

Ayutyanont³

et al. 2014

Alzheimer's & Dementia

111

142

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Background There is growing interest in the evaluation of preclinical Alzheimer’s disease (AD) treatments. As a result, there is a need to identify a cognitive composite that is sensitive to tracking preclinical AD decline to be used as a primary endpoint in treatment trials. Methods Longitudinal data from initially cognitively normal, 70–85 year old participants in three cohort studies of aging and dementia from the Rush Alzheimer’s Disease Center were examined to empirically define a composite cognitive endpoint that is sensitive to detecting and tracking cognitive decline prior to the onset of cognitive impairment. The mean to standard deviation ratios (MSDR) of change over time were calculated in a search for the optimal combination of cognitive tests/sub-tests drawn from the neuropsychological battery in cognitively normal participants who subsequently progressed to clinical stages of AD during a two and five year period, using data from those who remained unimpaired during the same time period to correct for aging and practice effects. Combinations that performed well were then evaluated for representation of relevant cognitive domains, robustness across individual years prior to diagnosis, and occurrence of selected items within top performing combinations. Results The optimal composite cognitive test score is comprised of 7 cognitive tests/sub-tests with an MSDR=0.964. By comparison, the most sensitive individual test score, Logical Memory – Delayed Recall, MSDR= 0.64. Conclusions We have identified a composite cognitive test score representing multiple cognitive domains that has improved power compared to the most sensitive single test item to track preclinical AD decline and evaluate preclinical AD treatments. We are confirming the power of the composite in independent cohorts, and with other analytical approaches, which may result in refinements, and have designated it as the primary endpoint in the Alzheimer’s Prevention Initiative’s preclinical treatment trials for individuals at high imminent risk for developing symptoms due to late-onset AD.

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Gaining precision on the Alzheimer's Disease Assessment Scale‐cognitive: A comparison of item response theory‐based scores and total scores

Abstract: These findings suggest that item response theory scoring of the ADAS-cog may measure cognitive dysfunction more precisely than a total score method.

Cited by 34 publications

References 15 publications

Application of Item Response Theory to Modeling of Expanded Disability Status Scale in Multiple Sclerosis

Application of Item Response Theory to Modeling of Expanded Disability Status Scale in Multiple Sclerosis

Modeling a Composite Score in Parkinson’s Disease Using Item Response Theory

An empirically derived composite cognitive test score with improved power to track and evaluate treatments for preclinical Alzheimer's disease

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