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O1‐10‐03: APOE risk in the Alzheimer's prevention initiative
Author(s) -
Blacker Deborah,
Qian Jing,
Beiser Alexa S.,
Haan Mary,
Karlawish Jason,
Langbaum Jessica B.,
Reiman Eric M.,
Neuhaus John,
Seshadri Sudha,
Tariot Pierre N.,
Betensky Rebecca A.
Publication year - 2015
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2015.07.083
Subject(s) - medicine , proportional hazards model , framingham risk score , hazard ratio , dementia , cumulative incidence , gerontology , demography , cohort , population , apolipoprotein e , framingham heart study , confidence interval , disease , environmental health , sociology
plan and perform statistical analyses to understand the complexity of impact of APOE gene on multiple key parameters in a hypothesized clinical trial, such as determining trial duration, identifying target population, comparing potential clinical outcomes and testing the statistical interaction between APOE and multiple types of imaging biomarkers. Results:The observed ApoE gene effect on AD clinical progression appears to be modest during the first 2w3 years after enrollment in theMCI population. Over six years, cognitive decline rates are significantly different by ApoE status (Figure 1), and are influenced by brain Ab deposition status (Figure 2). In designing a clinical trial, this genetic by imaging interactionmay be translated to 30% reduction in sample size for certain clinical endpoints. Conclusions:A more effecient clinical trial may be designed by considering APOE, as well as other biomarkers, in population stratification. Moreover, public data, such as ADNI, is very helpful to design clinical trials.