A composite endpoint using version 3 of the Alzheimers’ Disease Research Centers’ neuropsychological test battery
Bibliographic record
Abstract
Abstract Background Version 3 of the Uniform Data Set (UDS) has been collected by the National Alzheimer’s Coordinating Center (NACC) since 2015, which contains neuropsychological test scores on multiple domains. However, its potential utility as prevention trial outcomes needs to be examined, in comparison with other previously validated outcomes. Method The analytical sample was extracted from the December 2022 data freeze from NACC, which includes baseline and follow‐up visits from participants who were cognitively normal during initial visits. Standardized z‐scores for each cognitive domain (attention/working memory, episodic memory, semantic memory/language, executive function, visuospatial function) were calculated. Linear mixed effects models with random intercepts and slopes were used for studying longitudinal changes comparing participants who progressed to MCI or AD (decline subgroup) and those who remained cognitively normal for up to 4 years of follow‐up (stable subgroup), controlling for baseline age, sex, race, education and APOE‐e4 carrier status. We then constructed an approximate effect size weighted average of domain‐specific scores as a global composite measure, obtain effect size estimates using the mini‐mental state examination (MMSE), the Montreal Cognitive Assessment (MoCA) and the composite measure as outcomes, and perform sample size calculations using the following assumptions: a significance level of 5%, 80% power, an equal proportion randomized in a hypothesized intervention and a placebo control arms, in which the intervention group has a 10% to 30% reduction of progression to MCI during the study period, each participant has a baseline visit and up to four annual follow‐up visits, a dropout rate of 10% per year. Result The estimated difference of the annualized rate of change in z‐scores between the decline and stable subgroups ranged from 0.028 (attention) to 0.105 (executive function) standardized units for the domain‐specific scores, and 0.068 standard deviation units for the composite score. The composite score requires a smaller sample size for detecting the same level of reduction in progression compared to MoCA and MMSE. Conclusion Using a global composite score of UDS version 3 neuropsychological tests as a prevention trial outcome would result in about 30‐50% reduction of sample size needed compared to MMSE and MoCA.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".