Clinical importance in Alzheimer’s disease: effects of anchor agreement and disease severity
Bibliographic record
Abstract
OBJECTIVES: Methods of evaluating clinically meaningful decline are critical in research on Alzheimer's disease. A common method of quantifying clinically meaningful change is to calculate an anchor-based minimal clinically important difference (MCID) score. In this approach, individuals who report a meaningful change serve as the "anchors", and the mean level of change for this group serves as the MCID. In research on Alzheimer's disease, there are several possible anchors, including patients, knowledgeable observers (e.g., a family member), and clinicians. The goal of this study was to examine the extent to which agreement among anchors impacts MCID estimation and whether this relationship is moderated by cognitive severity status. METHODS: Analyses were completed on a longitudinal sample of 2247 adults, aged 50-103, from the Uniform Data Set. Outcome measures included the Montreal Cognitive Assessment, Clinical Dementia Rating-Sum of Boxes, and Functional Activities Questionnaire. RESULTS: For all of the outcomes, the MCID estimate was significantly higher when meaningful decline was endorsed by all of the anchors compared to when there was disagreement among the anchors. In addition, the MCID estimate was higher with increasing severity of cognitive impairment. Finally, cognitive severity status moderated the influence of agreement among anchors on MCID estimation; as disease severity increased, anchor agreement demonstrated less influence on the MCID. CONCLUSIONS: MCID estimates based on one anchor may underestimate meaningful change, and researchers should consider the viewpoints of multiple anchors in constructing MCIDs, particularly in the early stages of cognitive decline.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".