Measuring time saved in Alzheimer's disease: What is a meaningful slowing of progression?
Bibliographic record
Abstract
INTRODUCTION: Minimal clinically important differences (MCIDs) for Alzheimer's disease (AD) have previously been estimated using clinician-based anchors. However, MCIDs have been criticized for not reflecting the preferences of people living with AD (PLWAD). Furthermore, interpretations of clinical trial results have been criticized for conflating within-person meaningfulness thresholds and between-group differences. Here, we simulate scenarios of disease slowing and compare those to published MCIDs. METHODS: Scenarios of 5%-95% disease slowing were simulated using Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Time saved and point differences on the Clinical Dementia Rating scale-Sum of Boxes (CDR-SB) were estimated for these scenarios and compared to published MCIDs. RESULTS: Scenario analyses resulted in estimates of time saved at ∼3 weeks-17 months and mean changes at 0.08-1.5 CDR-SB points over 18 months. The often referenced MCID for mild cognitive impairment (0.98) thereby corresponded to 11 months slowing, whereas the MCID for mild dementia (1.63) corresponded to >17 months slowing. DISCUSSION: Translating trial endpoints to estimates of time saved supports that often-referenced MCIDs may not be aligned with realistic and meaningful slowing of clinical progression. Highlights: AD slowing of clinical progression by 5%-95% resulted in 0.74-17 months saved and 0.08-1.5 CDR-SB points change at 18 months.Slowing of at least 60% or 11 months of time saved over 18 months met an often-cited MCID threshold of 0.98 points for mild cognitive impairment.For mild AD dementia, an MCID of 1.63 meant that even an 18-month delay over 18 months would be considered only borderline meaningful-a face invalid and unrealistic proposition.
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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 | 0.020 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".