Dataset Information

New scoring methodology improves the sensitivity of the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) in clinical trials.

ABSTRACT:

Introduction

As currently used, the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) has low sensitivity for measuring Alzheimer's disease progression in clinical trials. A major reason behind the low sensitivity is its sub-optimal scoring methodology, which can be improved to obtain better sensitivity.

Methods

Using item response theory, we developed a new scoring methodology (ADAS-CogIRT) for the ADAS-Cog, which addresses several major limitations of the current scoring methodology. The sensitivity of the ADAS-CogIRT methodology was evaluated using clinical trial simulations as well as a negative clinical trial, which had shown an evidence of a treatment effect.

Results

The ADAS-Cog was found to measure impairment in three cognitive domains of memory, language, and praxis. The ADAS-CogIRT methodology required significantly fewer patients and shorter trial durations as compared to the current scoring methodology when both were evaluated in simulated clinical trials. When validated on data from a real clinical trial, the ADAS-CogIRT methodology had higher sensitivity than the current scoring methodology in detecting the treatment effect.

Conclusions

The proposed scoring methodology significantly improves the sensitivity of the ADAS-Cog in measuring progression of cognitive impairment in clinical trials focused in the mild-to-moderate Alzheimer's disease stage. This provides a boost to the efficiency of clinical trials requiring fewer patients and shorter durations for investigating disease-modifying treatments.

SUBMITTER: Verma N

PROVIDER: S-EPMC4642693 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Publications

New scoring methodology improves the sensitivity of the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) in clinical trials.

Verma Nishant N Beretvas S Natasha SN Pascual Belen B Masdeu Joseph C JC Markey Mia K MK

Alzheimer's research & therapy 20151112 1

<h4>Introduction</h4>As currently used, the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) has low sensitivity for measuring Alzheimer's disease progression in clinical trials. A major reason behind the low sensitivity is its sub-optimal scoring methodology, which can be improved to obtain better sensitivity.<h4>Methods</h4>Using item response theory, we developed a new scoring methodology (ADAS-CogIRT) for the ADAS-Cog, which addresses several major limitations of the curren ...[more]

PMID: 26560146

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Project description:The Alzheimer's Disease Assessment Scale-Cognitive (ADAS-Cog) has been used widely as a cognitive end point in Alzheimer's Disease (AD) clinical trials. Efforts to treat AD pathology at earlier stages have also used ADAS-Cog, but failure in these trials can be difficult to interpret because the scale has well-known ceiling effects that limit its use in mild cognitive impairment (MCI) and early AD. A wealth of data exists in ADAS-Cog from both historical trials and contemporary longitudinal natural history studies that can provide insights about parts of the scale that may be better suited for MCI and early AD trials.Using Alzheimer's Disease Neuroimaging Initiative study data, we identified the most informative cognitive measures from the ADAS-Cog and other available scales. We used cross-sectional analyses to characterize trajectories of ADAS-Cog and its individual subscales, as well as other cognitive, functional, or global measures across disease stages. Informative measures were identified based on standardized mean of 2-year change from baseline and were combined into novel composite endpoints. We assessed performance of the novel endpoints based on sample size requirements for a 2-year clinical trial. A bootstrap validation procedure was also undertaken to assess the reproducibility of the standardized mean changes of the selected measures and the corresponding composites.All proposed novel endpoints have improved standardized mean changes and thus improved statistical power compared with the ADAS-Cog 11. Further improvements were achieved by using cognitive-functional composites. Combining the novel composites with an enrichment strategy based on cerebral spinal fluid beta-amyloid (A?(1-42)) in a 2-year trial yielded gains in power of 20% to 40% over ADAS-Cog 11, regardless of the novel measure considered.An empirical, data-driven approach with existing instruments was used to derive novel composite scales based on ADAS-Cog 11 with improved performance characteristics for MCI and early AD clinical trials. Together with patient enrichment based on A?(1-42) pathology, these modified endpoints may allow more efficient clinical trials in these populations and can be assessed without modifying current test administration procedures in ongoing trials.

Project description:BACKGROUND:Development of new treatments for Alzheimer's disease (AD) has broadened into early interventions in individuals with modest cognitive impairment and a slow decline. The 11-item version of the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) was originally developed to measure cognition in patients with mild to moderate AD. Attempts to improve its properties for early AD by removing items prone to ceiling and/or by adding cognitive measures known to be impaired early have yielded a number of ADAS-Cog variants. Using Alzheimer's Disease Neuroimaging Initiative data, we compared the performance of the 3-, 5-, 11- and 13-item ADAS-Cog variants in subjects with early AD. Given the interest in enrichment strategies, we also examined this aspect with a focus on cerebrospinal fluid (CSF) markers. METHODS:Subjects with mild cognitive impairment (MCI) and mild AD with available ADAS-Cog 13 and CSF data were analysed. The decline over time was defined by change from baseline. Direct cross-comparison of the ADAS-Cog variants was performed using the signal-to-noise ratio (SNR), with higher values reflecting increased sensitivity to detect change over time. RESULTS:The decline over time on any of the ADAS-Cog variants was minimal in subjects with MCI. Approximately half of subjects with MCI fulfilled enrichment criteria for positive AD pathology. The impact of enrichment was detectable but subtle in MCI. The annual decline in mild AD was more pronounced but still modest. More than 90 % of subjects with mild AD had positive AD pathology. SNRs were low in MCI but greater in mild AD. The numerically largest SNRs were seen for the ADAS-Cog 5 in MCI and for both the 5- and 13-item ADAS-Cog variants in mild AD, although associated confidence intervals were large. CONCLUSIONS:The possible value of ADAS-Cog expansion or reduction is less than compelling, particularly in MCI. In mild AD, adding items known to be impaired at early stages seems to provide more benefit than removing items on which subjects score close to ceiling.

Dataset Information

New scoring methodology improves the sensitivity of the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) in clinical trials.

Introduction

Methods

Results

Conclusions

Publications

New scoring methodology improves the sensitivity of the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) in clinical trials.

Similar Datasets

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