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04/10/19 7:34 PM
Three-Month Stability of the CogState Brief Battery in Healthy Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease: Results from the Australian Imaging, Biomarkers, and Lifestyle-Rate of Change Substudy (AIBL-ROCS)
Yen Ying Lim Judith Jaeger Karra Harrington Tim Ashwood Kathryn A. Ellis Albrecht Stöffler Cassandra Szoeke Rebecca Lachovitzki Ralph N. Martins Victor L. Villemagne ... Show more
Archives of Clinical Neuropsychology, Volume 28, Issue 4, June 2013, Pages 320–330, https://doi.org/10.1093/arclin/act021
Published: 03 April 2013 Article history
Abstract
Large prospective studies of Alzheimer's disease (AD) have sought to understand the pathological evolution of AD and factors that may influence the rate of disease progression. Estimates of rates of cognitive change are available for 12 or 24 months, but not for shorter time frames (e.g., 3 or 6 months). Most clinical drug trials seeking to reduce or modify AD symptoms have been conducted over 12- or 24-week periods. As such, we aimed to characterize the performance of a group of healthy older adults, adults with amnestic mild cognitive impairment (aMCI), and adults with AD on the CogState battery of tests over short test–retest intervals. This study recruited 105 healthy older adults, 48 adults with aMCI, and 42 adults with AD from the Australian Imaging, Biomarkers, and Lifestyle study and administered the CogState battery monthly over 3 months. The CogState battery of tests showed high test–retest reliability and stability in all clinical groups when participants were assessed over 3 months. When considered at baseline, the CogState battery of tests was able to detect AD-related cognitive impairment. The data provide important estimates of the reliability, stability, and variability of each cognitive test in healthy older adults, adults with aMCI, and adults with AD. This may potentially be used to inform future estimates of cognitive change in clinical trials.
In a series of recent studies, we have found that tests from the CogState battery were sensitive to cognitive impairment (i.e., relative to matched controls) in mild to moderate AD, aMCI, and also in healthy older adults who carry putative AD biomarkers (Harel et al., 2011; Lim, Ellis, Harrington, et al., 2012; Lim, Pietrzak, Snyder, Darby, & Maruff, 2012). Of equivalent importance, in a different sample, we also found that performance on these same CogState tasks remained stable despite repeated administration in healthy older adults and was characterized by reliable decline over periods of 12 months or greater in aMCI (Harel et al., 2011). Furthermore, in patients with AD, performance on the verbal list learning task of the CogState battery declined over 1 year (Lim, Pietrzak, et al., 2012). Taken together, these data suggest that the same computerized battery of cognitive tests may be used to measure cognitive function repeatedly in older individuals with normal cognition and in patients with aMCI and AD. However, for use in AD groups, it has been necessary to simplify some (i.e., visual learning and associate learning; Harel et al., 2011) but not all (i.e., verbal learning; Lim, Pietrzak, et al., 2012) tests of memory in order to maximize their acceptability. Finally, the CogState battery has demonstrated sensitivity to cognitive improvement arising from treatment with current pharmacotherapies for AD (e.g., cholinesterase inhibitors), with clinical trial data showing that performance is improved after acute treatment with donepezil in healthy older adults (Pietrzak, Maruff, & Snyder, 2009; Snyder, Bednar, Cromer, & Maruff, 2005) and with daily dosing in AD (Jaeger, Hardemark, & Zettergren, 2011). There is a growing appreciation of the importance of understanding the dynamics and reliability of neuropsychological assessments used for repeated assessments (Duff, 2012; Heilbronner et al., 2010). However, as yet, there has been no direct comparison of the stability and reliability of these same tests between healthy older adults and those with MCI or AD assessed over the same time intervals.
The Australian Imaging, Biomarkers, and Lifestyle (AIBL) study is a prospective natural history study of over 1000 adults who are cognitively normal or have either a diagnosis of MCI or mild AD (Ellis et al., 2009). These individuals undergo extensive assessment using psychiatric, neuropsychological, neurological, neuroradiological, and lifestyle measures at 18-month intervals (Ellis et al., 2009; Rowe et al., 2010). The AIBL Rates of Change substudy (hereafter referred to as ROCS) was designed to leverage the care and attention used in recruiting, assessing and characterizing the subjects in AIBL, by taking a subset of each clinical group and assessing them repeatedly at short retest intervals using the CogState battery to determine the extent to which any change in cognitive function could be detected in individuals with different stages of AD over intervals of 1, 2, 3, 6, 12, and 18 months. As the ROCS study is now enrolled fully and complete to the 3-month assessment, these data can be used to examine the acceptability of the tests in healthy adults, and adults with aMCI and AD, as well as to examine the magnitude of differences in performance between these groups. Some clinical trials of putative cognitive enhancers in AD are also conducted over 3 months and these trials generally measure cognitive performance at baseline and then at multiple follow-up assessments (i.e., weeks 4, 8 and 12; Pietrzak et al., 2009; Rogers et al., 1998). Therefore, we also investigated the stability of performance on the battery over 12 weeks in each of these cognitive measures between groups. Data from this prospective study can provide estimates of the expected rate of change in cognitive function over 12 weeks, as well as estimates of associated error (i.e., test–retest reliability and stability of the different outcome measures). Such data can be useful for computing power in clinical trials conducted over the same time interval. Finally, by restricting our analyses to the very short term, the effects of disease-related variability would be minimized, thus allowing direct comparison of any differences in rates of change or stability of performance in the different stages of the disease.
The first aim of this study was to directly compare the performance on the CogState battery between healthy older adults, adults with aMCI and adults with AD who had completed 3 months of assessment in the ROCS. The first hypothesis was that for tests where performance could be compared directly, healthy older adults would perform better than adults with aMCI, who would in turn show performance better than adults with AD. The second aim was to determine the stability of performance on the CogState battery over the initial 12 weeks of the ROCS in which it had been administered four times. The second hypothesis was that performance measures on the CogState battery would be reliable and remain stable (i.e., unchanged) over the short test–retest period in healthy, aMCI, and AD groups. The third aim was to explore the estimates of variability in performance over time on the CogState battery and to compare these between the three clinical groups to determine whether they are different.
The estimates of variability and expected mean change over time in the three groups studied here (i.e., Table 4) can be used to guide the design of clinical trials seeking to measure the effect of a pharmacotherapeutic intervention in groups of AD, aMCI, or even healthy older adults. For example, the change from baseline to week 12 on verbal memory (i.e., ISLT total recall) in the AD group was a very slight increase in words recalled of 0.46 with a standard deviation of 4.99 for this change. Thus, to plan a trial where the improvement in performance under treatment was, for example, d = 0.4 (i.e., an improvement of performance on the ISLT total recall of 2 words), then 100 patients would need to be assigned randomly to the placebo and treatment groups (assuming that there are two groups, the equal ratio of assignment to each group, Type I error of 0.05, and sample size required for statistical significance; Faul, Erdfelder, Lang, & Buchner, 2007). For the OCL, the same expected effect size (and, therefore, the same sample size) would require the accuracy of performance on this task to improve from 0.82 at baseline to 0.85 at week 12 (refer to Table 4) in order for an effect to be rendered statistically significant. It is important to note that for both tests, the magnitude of improvement associated with this effect size would not increase the level of performance of the AD group to that of the MCI group. The practice-corrected RCIs presented in Table 4 can be used by neuropsychologists to guide decisions about the presence of change of cognitive function in healthy older adults or in adults who meet clinical criteria for aMCI or AD. For example, the 85% CI for the ISLT delayed recall indicates that in the aMCI group, a reduction of 3 words over 3 months would be clinically meaningful. Similarly, in the AD group, an increase in 23 errors on the CPAL task over 3 months would be clinically significant at 85% CI. Further, the magnitude of change required for a decline in performance to be considered clinically meaningful in the different groups is relatively similar for each task.
Taken together, the results of this study show that performance in the AD and aMCI groups did not decline over the 3-month period and that this stability is consistent with that observed on other cognitive assessments in recent industry sponsored clinical trials (Faux et al., 2010; Salloway et al., 2009). This suggests that clinical trials of putative cognitive enhancing drugs should be designed to detect improvement in cognition in the treatment group compared with placebo. This approach is different to those where the beneficial effects of cognitively enhancing drugs are indicated by stabile cognitive function in the treated group while performance in the placebo group declines (Darby, Brodtmann, Woodward, Budge, & Maruff, 2011). Alternatively, trials of drugs designed to ameliorate AD-related cognitive decline will have to be conducted over time intervals longer than 3 months if the CogState battery is used to measure cognition. In a previous 12-month study of mild to moderate AD, we observed a moderate decline (d = 0.60, or 2.5 words) on the ISLT total recall measure (Lim, Pietrzak, et al., 2012). Similarly, we observed a decline in performance over 12 months on the OCL in patients with aMCI (Maruff et al., 2004). However, future analysis of ROCS data will provide estimates of the stability of performance on this cognitive test battery over 9, 12, and 18 month periods in the clinical groups studied here.
04/10/19 11:28 PM
