A Comparison of HU12 and HU13 Utility Scores in Alzheimer's Disease
Bibliographic record
Abstract
PURPOSE: The Health Utilities Index (HUI) is a generic, multiattribute, preference-based health-status classification system. The HUI Mark 3 (HUI3) differs from the earlier HUI2 by modifying attributes and allowing more flexibility for capturing high levels of impairment. The authors compared HUI2 and HUI3 scores of patients with Alzheimer's disease (AD) and caregivers, and contrasted results of a cost-effectiveness analysis of new drugs for AD using the two systems. METHODS: In a cross-sectional study of 679 AD patient/caregiver pairs, stratified by patient's disease stage (questionable/mild/moderate/severe/profound/terminal) and setting (community/assisted living/nursing home), caregivers completed the combined HUI2/HUI3 questionnaire as proxy respondents for patients and for themselves. RESULTS: Mean (SD) global utility scores for patients were lower on the HUI3 (0.22[0.26]) than on the HUI2 (0.53 [0.21]). Patient HUI3 utility scores ranged from 0.47(0.24) for questionable AD to -0.23 (0.08) for terminal AD, compared with a range of 0.73 (0.15) to 0.14 (0.07) for the HUI2. Among the 203 patients in the severe, profound, and terminal stages, 96 (48%) had negative global HUI3 utility scores, while none had a negative HUI2 score. The utility scores for caregivers were similar on the HUI3 (0.87 [0.14]) and HUI2 (0.87 [0.11]). Cost-effectiveness analysis of a new medication to treat AD showed somewhat more favorable results using the HUI3. CONCLUSIONS: The HUI2 and HUI3 discriminate well across AD stages. Compared with the HUI2, the HUI3 yields lower global utility scores for patients with AD, and more scores for states judged worse than dead. The HUI3 may yield substantially different results from the HUI2, particularly for persons who have serious cognitive impairments such as AD.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".