ADNI data is made available to researchers around the world. As such, there are many active research projects accessing and applying the shared ADNI data. To further encourage Alzheimer’s disease research collaboration, and to help prevent duplicate efforts, the list below shows the specific research focus of the active ADNI investigations. This information is requested annually as a requirement for data access.
|Principal Investigator's Name:||Farkad Ezzet|
|Institution:||Aycer Pharma Consulting|
|Department:||Free Lance Consultant|
|Proposed Analysis:||Measurement of MMSE and CDR Global will be used to determine the subject’s disease state, i.e. control, mild cognitive impairment (MCI) or Alzheimer Disease (AD). The time to transition to a worse state will be used to estimate the rates of transition. Because of the three states, "Control", "MCI" and "AD", two rates will be estimated using a "Multi-state Markov Model". A special function available in the open source statistical language "R" is thus appropriate. The advantage of this function is its ability to factor in the discrete nature of the measurements, namely 6 months intervals, treating the transition times as though being measured with error. The modeling procedure allows making inference on covariates e.g. demographics, imaging and any other influential variables the database may have. Additionally, the analysis incorporate subject random effects to account for the repeated measurement aspect of the data and inter subject variability. The analysis will thus determine which set of covariates are predictive of transitioning to MCI and to AD. Such information should help optimize clinical trial design by way of selecting appropriate patient population and study duration. For a given recruitment rate, the total clinical trial length can be projected, to enable sponsors to evaluate probability of success assuming appropriate effect size as compared to standard of care.|