The Alzheimer’s Prevention Initiative Composite Cognitive Test Score

Abstract

Objective-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.Method-We capitalized on longitudinal data, collected from 1995 to 2010, from cognitively unimpaired presenilin 1 (PSEN1) E280A mutation carriers from the world's largest known earlyonset autosomal dominant AD (ADAD) kindred to identify a composite cognitive test with the greatest statistical power to track preclinical AD decline and estimate the number of carriers age 30 and older needed to detect a treatment effect in the Alzheimer's Prevention Initiative's (API) preclinical AD treatment trial. The mean-to-standard-deviation ratios (MSDRs) of change over time were calculated in a search for the optimal combination of one to seven cognitive tests/sub-* To whom correspondence should be addressed: Napatkamon Ayutyanont, PhD, Banner Alzheimer's Institute, 901 E. Willetta Street, Phoenix, AZ 85006, telephone: 602.839.6825; Napatkamon.Ayutyanont@bannerhealth.com. ** These two authors are co-senior authors.Portions of this study were presented at the 2011 Alzheimer's Association International Conference, Paris, France and the 2011 Clinical Trials on Alzheimer's Disease (CTAD), San Diego, CA.They have no conflict of interest to report. 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 in ADAD mutation carriers and evaluate preclinical AD treatments. This API composite cognitive test score will be used as the primary endpoint in the first API trial in cognitively unimpaired ADAD carriers within 15 years of their estimated age at clinical onset. NIH Public AccessWe have independently confirmed our findings in a separate cohort of cognitively healthy older adults who progressed to the clinical stages of late-onset AD, described in a separate report, and continue to refine the composite in independent cohorts and compared with other analytical approaches.

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

“…This API composite cognitive test score and the approach taken to develop it appears to fit into the framework provided by the Food and Drug Administration’s recent draft guidance concerning a cognitive assessment serving as a primary efficacy measure in preclinical AD trials (51). Moreover, the composite identified in the present study was comprised of the same cognitive domains/assessments with the exception of one (present study included a test of visual spatial ability – Symbol Digits Modalities ) as a composite cognitive endpoint identified in cognitively healthy ADAD mutation carriers, despite substantial differences in the cohorts’ neuropsychological test batteries (52). This consistency is noteworthy as confirmation of the composite’s performance in an independent population, as well as suggesting that there is extensive overlap in the pattern of cognitive decline between the two forms of the disease even though they strike at different ages, and may have different preclinical and clinical time courses, underlying etiologies, and biological processes.…”

Linear combinations of multiple outcome measures to improve the power of efficacy analysis – application to clinical trials on early-stage Alzheimer's disease

“…Whereas ongoing clinical trials on early stage AD such as the A4 trial and the API trial have proposed differing cognitive composites using the same weights across multiple cognitive domains [17, 23], we sought to improve these by mathematically optimizing the weights so that the sample sizes for adequately powering such trials could be minimized. We proposed a multivariate mixed model for repeated measures to jointly model the longitudinal progression of multiple outcomes.…”

“…A large cognitive battery has been administered in DIAN participants [45], covering a wide range of domains. Based on recent reports on cognitive domains that may exhibit early progression from the ongoing A4 trial [17] and the API trial [23] as well as a preliminary analysis on the DIAN database, to demonstrate the application of our proposed methodology, we have chosen the following six candidates of the cognitive tests that can be considered for powering the upcoming Phase III cognitive endpoint trial: the total score of the MMSE [21], a widely used screening test that evaluates overall cognitive function by examining orientation to place, orientation to time, attention, concentration, language, ability to recall previously given words and visual-spatial skills. The Score of MMSE ranges from 0 to 30 [21];…”

“…In the API trial, the proposed cognitive composite is also equally weighted among the following individual tests over multiple cognitive domains [23]: Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word List Recall, CERAD Boston Naming Test (high frequency items), MMSE Orientation to Time, CERAD Constructional Praxis, and Raven's Progressive Matrices (Set A) [24-27]. It is reported that the proposed composite is more sensitive than using the entire CERAD battery [23]. Whereas each of the proposed cognitive composite score weighs multiple tests equally, and has performed reasonably well, it remains unknown whether they provide the optimum power for designing RCTs on early stage AD.…”

Longitudinal Positron Emission Tomography in Preventive Alzheimer's Disease Drug Trials, Critical Barriers from Imaging Science Perspective

“…time-to-AD conversion, may not be suitable for these early trials (1). While several groups are developing new composite cognitive tests that could serve as surrogate outcome measures by detecting subtle cognitive changes in normal people (2, 15), there is a need for longitudinal brain imaging techniques that can correlate with temporal changes in these new tests and provide additional objective measures of neuropathological changes in brain. In particular, within-individual longitudinal comparisons of imaging data may improve these evaluations by controlling for between subject variability.…”