183541 USING Logistic Regression to Identify Factors Associated with Practice Effect of Repeated Mis Scores in Preadvise

Monday, October 27, 2008: 11:30 AM

Marta S. Mendiondo, PhD , Department of Biostatistics, University of Kentucky, Lexington, KY
Richard J. Kryscio, PhD , Dept. of Biostatistics, Dept of Statistics, University of Kentucky, Lexington, KY
Erin L. Abner, MA, MPH , College of Public Health, University of Kentucky, Lexington, KY
William Markesbery, MD , Neurology Department Center on Aging, University of Kentucky, Lexington, KY
Frederick Schmitt, PhD , Neurology Department Center on Aging, University of Kentucky, Lexington, KY
The primary aim of the NIA-sponsored PREADVISE trial is to determine the effectiveness of vitamin E and selenium in preventing the onset of Alzheimer's disease (AD) in over 6,667 men in collaboration with the NCI-sponsored SELECT prostate cancer prevention study. PREADVISE participants have annual Memory Impairment Screen (MIS) evaluations.

The mean age of the 86.2% white repeat cohort at baseline was 67.6 years with 15.0 years of education. MIS scores ranged from 3 to 8 with 67.9% scoring a perfect 8, and 80.0% of these participants scoring 8 at the second assessment.

Of the 1,650 enrollees scoring less than 8 at baseline, 30.3% had greater scores on the second MIS. A logistic regression showed that having 16+ years of education, age at enrollment, taking Statins medications, and presence of CABG were associated with improvement in MIS performance.

Of the 4,626 men scoring 7 or 8 at baseline, 4.8% showed a decline to a score below 7 at the second screen (increased risk for MCI or dementia). In a logistic model, white race, 16+ years of education, age at baseline, and at least some college, presence of diabetes were associated with a decline.

In conclusion, college education has a positive effect, whereas age, CABG, and Statins have a negative effect, on the odds that a practice effect is observed among those who scored less than 8 on the baseline MIS. In addition, the data suggest that white race, high education, younger age, and absence of diabetes protect against a decline.

Learning Objectives:
1. Describe and characterize the Preadvise population. 2. Analyze, using logistic regression, the factors that influence practice effect of the MIS. 3. Learn how to interpret the results obtained from the model.

Keywords: Statistics, Prevention

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: PhD in Statistics - Faculty in the College of Public Health - University of Kentucky
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.