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Avoid or Embrace? Practice Effects in Alzheimer's Disease Prevention Trials.

ABSTRACT: Demonstrating a slowing in the rate of cognitive decline is a common outcome measure in clinical trials in Alzheimer's disease (AD). Selection of cognitive endpoints typically includes modeling candidate outcome measures in the many, richly phenotyped observational cohort studies available. An important part of choosing cognitive endpoints is a consideration of improvements in performance due to repeated cognitive testing (termed "practice effects"). As primary and secondary AD prevention trials are comprised predominantly of cognitively unimpaired participants, practice effects may be substantial and may have considerable impact on detecting cognitive change. The extent to which practice effects in AD prevention trials are similar to those from observational studies and how these potential differences impact trials is unknown. In the current study, we analyzed data from the recently completed DIAN-TU-001 clinical trial (TU) and the associated DIAN-Observational (OBS) study. Results indicated that asymptomatic mutation carriers in the TU exhibited persistent practice effects on several key outcomes spanning the entire trial duration. Critically, these practice related improvements were larger on certain tests in the TU relative to matched participants from the OBS study. Our results suggest that the magnitude of practice effects may not be captured by modeling potential endpoints in observational studies where assessments are typically less frequent and drug expectancy effects are absent. Using alternate instrument forms (represented in our study by computerized tasks) may partly mitigate practice effects in clinical trials but incorporating practice effects as outcomes may also be viable. Thus, investigators must carefully consider practice effects (either by minimizing them or modeling them directly) when designing cognitive endpoint AD prevention trials by utilizing trial data with similar assessment frequencies.

SUBMITTER: Aschenbrenner AJ

PROVIDER: S-EPMC9244171 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Introduction:Practice effects (PEs) present a potential confound in clinical trials with cognitive outcomes. A single-blind placebo run-in design, with repeated cognitive outcome assessments before randomization to treatment, can minimize effects of practice on trial outcome. Methods:We investigated the potential implications of PEs in Alzheimer's disease prevention trials using placebo arm data from the Alzheimer's Disease Cooperative Study donepezil/vitamin E trial in mild cognitive impairment. Frequent ADAS-Cog measurements early in the trial allowed us to compare two competing trial designs: a 19-month trial with randomization after initial assessment, versus a 15-month trial with a 4-month single-blind placebo run-in and randomization after the second administration of the ADAS-Cog. Standard power calculations assuming a mixed-model repeated-measure analysis plan were used to calculate sample size requirements for a hypothetical future trial designed to detect a 50% slowing of cognitive decline. Results:On average, ADAS-Cog 13 scores improved at first follow-up, consistent with a PE and progressively worsened thereafter. The observed change for a 19-month trial (1.18 points) was substantively smaller than that for a 15-month trial with 4-month run-in (1.79 points). To detect a 50% slowing in progression under the standard design (i.e., a 0.59 point slowing), a future trial would require 3.4 times more subjects than would be required to detect the comparable percent slowing (i.e., 0.90 points) with the run-in design. Discussion:Assuming the improvement at first follow-up observed in this trial represents PEs, the rate of change from the second assessment forward is a more accurate representation of symptom progression in this population and is the appropriate reference point for describing treatment effects characterized as percent slowing of symptom progression; failure to accommodate this leads to an oversized clinical trial. We conclude that PEs are an important potential consideration when planning future trials.

Project description:BACKGROUND/AIMS:Clinical trials for Alzheimer's disease have been aimed primarily at persons who have cognitive symptoms at enrollment. However, researchers are now recognizing that the pathophysiological process of Alzheimer's disease begins years, if not decades, prior to the onset of clinical symptoms. Successful intervention may require intervening early in the disease process. Critical issues arise in designing clinical trials for primary and secondary prevention of Alzheimer's disease including determination of sample sizes and follow-up duration. We address a number of these issues through application of a unifying multistate model for the preclinical course of Alzheimer's disease. A multistate model allows us to specify at which points during the long disease process the intervention exerts its effects. METHODS:We used a nonhomogeneous Markov multistate model for the progression of Alzheimer's disease through preclinical disease states defined by biomarkers, mild cognitive impairment and Alzheimer's disease dementia. We used transition probabilities based on several published cohort studies. Sample size methods were developed that account for factors including the initial preclinical disease state of trial participants, the primary endpoint, age-dependent transition and mortality rates and specifications of which transition rates are the targets of the intervention. RESULTS:We find that Alzheimer's disease prevention trials with a clinical primary endpoint of mild cognitive impairment or Alzheimer's disease dementia will require sample sizes of the order many thousands of individuals with at least 5 years of follow-up, which is larger than most Alzheimer's disease therapeutic trials conducted to date. The reasons for the large trial sizes include the long and variable preclinical period that spans decades, high rates of attrition among elderly populations due to mortality and losses to follow-up and potential selection effects, whereby healthier subjects enroll in prevention trials. A web application is available to perform sample size calculations using the methods reported here. CONCLUSION:Sample sizes based on multistate models can account for the points in the disease process when interventions exert their effects and may lead to more accurate sample size determinations. We will need innovative strategies to help design Alzheimer's disease prevention trials with feasible sample size requirements and durations of follow-up.

Project description:Standardized tests of learning and memory are sensitive to changes associated with both aging and superimposed neurodegenerative diseases. Unfortunately, repeated behavioral test administration can be confounded by practice effects (PE), which may obscure declines in level of abilities and contribute to misdiagnoses. Growing evidence, however, suggests PE over successive longitudinal measurements may differentially predict cognitive status and risk for progressive decline associated with aging, mild cognitive impairment (MCI), and dementia. Thus, when viewed as a reflection of neurocognitive plasticity, PE may reveal residual abilities that can add to our understanding of age- and disease-related changes in learning and memory. The present study sought to evaluate differences in PE and verbal recall in a clinically characterized aging cohort assessed on multiple occasions over 3 years. Participants included 256 older adults recently diagnosed as cognitively unimpaired (CU; n = 126), or with MCI of amnestic (n = 65) or non-amnestic MCI (n = 2085), and multi-domain amnestic dementia of the Alzheimer's type (DAT; n = 45). We applied a continuous time structural equation modeling (ctsem) approach to verbal recall performance on the Hopkins Verbal Learning Test in order to distinguish PE from individual occasion performance, coupled random changes, age trends, and differing measurement quality. Diagnoses of MCI and dementia were associated with lower recall performance on all trials, reduced PE gain per occasion, and differences in non-linear dynamic parameters. Practice self-feedback is a dynamic measure of the decay or acceleration in PE process changes over longitudinal occasions. As with PE and mean recall, estimated practice self-feedback followed a gradient from positive in CU participants to null in participants with diagnosed MCI and negative for those with dementia diagnoses. Evaluation of sensitivity models showed this pattern of variation in PE was largely unmodified by differences in age, sex, or educational attainment. These results show dynamic modeling of PE from longitudinal performance on standardized learning and memory tests can capture multiple aspects of behavioral changes in MCI and dementia. The present study provides a new perspective for modeling longitudinal change in verbal learning in clinical and cognitive aging research.

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Avoid or Embrace? Practice Effects in Alzheimer's Disease Prevention Trials.

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