Cognitive and functional changes associated with Aβ pathology and the progression to mild cognitive impairment

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Cognitive and functional changes associated with Aβ pathology and the progression to mild cognitive impairment. / Insel, Philip S.; Donohue, Michael C.; Mackin, R. Scott; Aisen, Paul S.; Hansson, Oskar; Weiner, Michael W.; Mattsson, Niklas.

I: Neurobiology of Aging, Vol. 48, 12.2016, s. 172-181.

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TY - JOUR

T1 - Cognitive and functional changes associated with Aβ pathology and the progression to mild cognitive impairment

AU - Insel, Philip S.

AU - Donohue, Michael C.

AU - Mackin, R. Scott

AU - Aisen, Paul S.

AU - Hansson, Oskar

AU - Weiner, Michael W.

AU - Mattsson, Niklas

PY - 2016/12

Y1 - 2016/12

N2 - Cognitively-normal people with evidence of β-amyloid (Aβ) pathology and subtle cognitive dysfunction are believed to be at high risk for progression to mild cognitive impairment due to Alzheimer's disease (AD). Clinical trials in later stages of AD typically include a coprimary endpoint to demonstrate efficacy on both cognitive and functional assessments. Recent trials focus on cognitively-normal people, but functional decline has not been explored for trial designs in this group. The goal of this study was therefore to characterize cognitive and functional decline in (1) cognitively-normal people converting to mild cognitive impairment (MCI) and (2) cognitively-normal β-amyloid-positive (Aβ+) people. Specifically, we sought to identify and compare the cognitive and functional assessments and their weighted combinations that maximize the longitudinal decline specific to these 2 groups. We studied 68 people who converted from normal cognition to MCI and 70 nonconverters, as well as 137 Aβ+ and 210 β-amyloid-negative cognitively-normal people. We used bootstrap aggregation and cross-validated mixed-models to estimate the distribution of weights applied to cognitive and functional outcomes to form composites. We also evaluated best subset optimization. Using optimized composites, we estimated statistical power for a variety of clinical trial scenarios. Overall, 55.4% of cognitively-normal to MCI converters were Aβ+. Large gains in power estimates were obtained when requiring participants to have both subtle cognitive dysfunction and Aβ pathology compared with requiring Aβ pathology alone. Additional power resulted when including functional as well as cognitive outcomes as part of the composite. Composites formed by applying equal weights to all measures provided the highest estimates of cross-validated power, although similar to both continuous weight optimization and best subset optimization. Using a composite to detect a 30% slowing of decline, 80% power was obtained for predicted Aβ+ converters with 375 completers/arm for a 30-month trial using a combination of cognitive/ functional measures. In the Aβ+ group, power to approach levels suitable for a phase III clinical trial would require considerably larger sample sizes. Composites incorporating both cognitive and functional measures may substantially increase the power of a trial in a preclinical (Aβ+) AD population with subtle evidence of cognitive dysfunction.

AB - Cognitively-normal people with evidence of β-amyloid (Aβ) pathology and subtle cognitive dysfunction are believed to be at high risk for progression to mild cognitive impairment due to Alzheimer's disease (AD). Clinical trials in later stages of AD typically include a coprimary endpoint to demonstrate efficacy on both cognitive and functional assessments. Recent trials focus on cognitively-normal people, but functional decline has not been explored for trial designs in this group. The goal of this study was therefore to characterize cognitive and functional decline in (1) cognitively-normal people converting to mild cognitive impairment (MCI) and (2) cognitively-normal β-amyloid-positive (Aβ+) people. Specifically, we sought to identify and compare the cognitive and functional assessments and their weighted combinations that maximize the longitudinal decline specific to these 2 groups. We studied 68 people who converted from normal cognition to MCI and 70 nonconverters, as well as 137 Aβ+ and 210 β-amyloid-negative cognitively-normal people. We used bootstrap aggregation and cross-validated mixed-models to estimate the distribution of weights applied to cognitive and functional outcomes to form composites. We also evaluated best subset optimization. Using optimized composites, we estimated statistical power for a variety of clinical trial scenarios. Overall, 55.4% of cognitively-normal to MCI converters were Aβ+. Large gains in power estimates were obtained when requiring participants to have both subtle cognitive dysfunction and Aβ pathology compared with requiring Aβ pathology alone. Additional power resulted when including functional as well as cognitive outcomes as part of the composite. Composites formed by applying equal weights to all measures provided the highest estimates of cross-validated power, although similar to both continuous weight optimization and best subset optimization. Using a composite to detect a 30% slowing of decline, 80% power was obtained for predicted Aβ+ converters with 375 completers/arm for a 30-month trial using a combination of cognitive/ functional measures. In the Aβ+ group, power to approach levels suitable for a phase III clinical trial would require considerably larger sample sizes. Composites incorporating both cognitive and functional measures may substantially increase the power of a trial in a preclinical (Aβ+) AD population with subtle evidence of cognitive dysfunction.

KW - Clinical trials

KW - Cognition

KW - Composite

KW - Function

KW - Mild cognitive impairment

KW - β-amyloid

UR - http://www.scopus.com/inward/record.url?scp=84991609096&partnerID=8YFLogxK

U2 - 10.1016/j.neurobiolaging.2016.08.017

DO - 10.1016/j.neurobiolaging.2016.08.017

M3 - Article

VL - 48

SP - 172

EP - 181

JO - Neurobiology of Aging

T2 - Neurobiology of Aging

JF - Neurobiology of Aging

SN - 1558-1497

ER -