Today, I review, link to, and excerpt from A Combined Measure of Cognition and Function for Clinical Trials: The Integrated Alzheimer’s Disease Rating Scale (iADRS). [PubMed Abstract] [Full-Text HTML] [Full-Text PDF]. J Prev Alzheimers Dis. 2015 Dec 1;2(4):227-241. doi: 10.14283/jpad.2015.82.
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Abstract
It is generally recognized that more sensitive instruments for the earliest stages of Alzheimer’s disease (AD) are needed. The integrated Alzheimer’s Disease Rating Scale (iADRS) combines scores from 2 widely accepted measures, the Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-Cog) and the Alzheimer’s Disease Cooperative Study – instrumental Activities of Daily Living (ADCS-iADL). Disease progression and treatment differences as measured by the iADRS were analyzed using data from solanezumab EXPEDITION, EXPEDITION2, and EXPEDITION-EXT Studies; semagacestat IDENTITY Study; and donepezil ADCS – mild cognitive impairment (ADCS-MCI) Study. Psychometric properties of the iADRS were established through principal component analysis (PCA) and estimation of contributions of subscores and individual item scores to the iADRS total score. The iADRS performed better than most composites and scales in detecting disease progression and comparably or better than individual scales in detecting treatment differences. PCA demonstrated the iADRS can be divided into two principal components primarily representing cognitive items and instrumental ADLs. Dynamic ranges of the subscales were similar across all studies, reflecting approximately equal contributions from both subscales to the iADRS total score. In item analyses, every item contributed to the total score, with varying strength of contributions by item and across data sets. The iADRS demonstrated acceptable psychometric properties and was effective in capturing disease progression from MCI through moderate AD and treatment effects across the early disease spectrum. These findings suggest the iADRS can be used in studies of mixed populations, ensuring sensitivity to treatment effects as subjects progress during studies of putative disease-modifying agents.
Keywords: Alzheimer’s disease; clinical trials; iADRS; outcome measure.
Introduction
Clinical trials for new therapies of Alzheimer’s disease (AD) are enrolling patients earlier in the disease continuum to maintain optimal function and intervene before pathological changes are severe. The need for more sensitive and responsive instruments for early stages of AD is increasingly recognized. Because development and validation of new scales de novo is a long process, recent efforts have focused on developing composites from existing scales. Strategies that have been applied toward that end include theory-driven and data-mining approaches. Theory-driven composite development consists of construction of an instrument to include neuropsychological tests measuring domains known to be impaired at a particular disease stage of interest, for example, the Alzheimer’s Disease Cooperative Study (ADCS)-Preclinical Alzheimer Cognitive Composite (ADCS-PACC), a cognitive composite being used in the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s (A4) study of preclinical AD (1, 2). A data-mining approach applies mathematical calculations to existing items within a scale or scales to identify the most sensitive items and applies weighting and adding/subtracting items to improve performance. These approaches may also be combined. A common data-mining strategy for composite outcome measures developed specifically for mild cognitive impairment (MCI) or early AD has been to eliminate the items from the Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-Cog) (3, 4) that appear less sensitive to disease progression and combine those with items from measures (with or without weighting of individual items) from other instruments of cognition and/or function, with the goal of improving sensitivity to detect change and reducing variability (5–10).
The objective of our work was to identify a composite scale that would appropriately measure the most important domains of AD (i.e., cognition and function) that could be used to monitor disease progression in observational studies and show treatment effects in placebo-controlled clinical trials.
Adopting a theory-driven approach as described above, the starting point for this work was to test the concept of a composite that combines cognition (with a particular focus on episodic memory, executive function, and global cognitive abilities) and function (activities of daily living) through the evaluation of existing scales. Various composites constructed using several different scales were first evaluated for their ability to detect disease progression in data sets including MCI and mild AD patients. These analyses demonstrated that assessing cognitive and functional items in a single composite scale was more sensitive to detecting disease progression than testing the domains separately. In both MCI and mild AD populations, the best performing composite was the combination of the ADAS-Cog13 with the Functional Activities Questionnaire (FAQ) (11). The next stage of analysis was to determine whether this construct was sensitive in detection of treatment effects. The treatment trials available for these analyses included the ADCS-ADL scale, rather than the FAQ, as the functional measure, and specified the ADAS-Cog14 as the primary cognitive outcome measure for the mild AD population; thus, the construct was represented as the ADAS-Cog14 combined with the ADCS-instrumental Activities of Daily Living (iADL). This process resulted in and supported the use of a simple combination of the ADAS-Cog14 and the ADCS-iADL scales, which we termed the integrated Alzheimer’s Disease Rating Scale (iADRS). Herein, we describe the analyses conducted to develop the iADRS, to assess the ability of the iADRS to detect disease progression and treatment effects, and to describe its psychometric properties.
