P3–007: Cognitive screening in the antioxidant AD prevention (PREADVISE) trial: Concordance of MIS and CERAD
Bibliographic record
Abstract
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 5,200 men in the U.S., Canada, and Puerto Rico in collaboration with the NCI–sponsored SELECT prostate prevention study. The accuracy of cognitive screening tools utilized will be essential to the ability of PREADVISE to successfully identify cognitive changes in the study participants and render a conclusion as to the primary aim of the study (dementia incidence). (1) Provide preliminary results of cognitive testing in an AD prevention trial. (2) Compare results of the MIS and CERAD battery. PREADVISE participants are screened yearly with the Memory Impairment Screen (MIS). Participants scoring below cutoff on the MIS are administered the Longer Memory and Thinking Test (LMTS or CERAD battery). PREADVISE also has a Normal Aging (NAG) subsample. This cohort of participants (scoring above cutoff on the MIS) is administered a cognitive battery annually. The NAG assessment consists of the CERAD battery supplemented by paragraph recall, visual attention, digit symbol, phonemic verbal fluency, and the National Adult Reading Test. The current analysis evaluates the correspondence between MIS and CERAD scores in the first 146 NAG and LMTS participants. Statistical Analysis Software 9.1 (SAS) was used to complete a multiple linear regression using CERAD total and memory scores to MIS scores. The resultant equation was CERAD = 55.9340 + 2.7135(MIS score); with a statistically significant R of 0.14 (p <.0001). Mean CERAD scores for each MIS score are shown in Table 1. The table shows a general trend of participants with higher CERAD scores obtaining higher MIS scores. Results of the MIS and CERAD appear to have a significant, positive correspondence. Given the excellent discrimination of the CERAD battery between normal and AD samples as well as the high sensitivity and specificity of the MIS, these screening tools hold promise for future use in AD prevention trials. Further, the MIS appears to be an effective indicator of overall performance compared to a more complete cognitive battery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".