A comparison of the Child Health Utility 9D and the Health Utilities Index for estimating health utilities in pediatric inflammatory bowel disease
Bibliographic record
Abstract
PURPOSE: Health utilities are challenging to ascertain in children and have not been studied in pediatric Crohn's disease (CD) and ulcerative colitis (UC). The objective was to assess discriminative validity by comparing utilities elicited using the Child Health Utility-9 Dimension (CHU9D) to the Health Utilities Index (HUI) across multiple disease activity scales in pediatric UC and CD. METHODS: Preference-based instruments were administered to 188 children with CD and 83 children with UC aged 6 to 18 years. Utilities were calculated using CHU9D adult and youth tariffs, and HUI2 and HUI3 algorithms in children with inactive (quiescent) and active (mild, moderate, and severe) disease. Differences between instruments, tariff sets and disease activity categories and were tested statistically. RESULTS: In CD and UC, all instruments detected significantly higher utilities for inactive compared to active disease (p < 0.05). Mean utilities for quiescent disease ranged from 0.810 (SD 0.169) to 0.916 (SD 0.121) in CD and from 0.766 (SD 0.208) to 0.871 (SD 0.186) in UC across instruments. Active disease mean utilities ranged from 0.694 (SD 0.212) to 0.837 (SD 0.168) in CD and from 0.654 (SD 0.226) to 0.800 (SD 0.128) in UC. CONCLUSION: CHU9D and HUI discriminated between levels of disease activity in CD and UC regardless of the clinical scale used, with the CHU9D youth tariff most often displaying the lowest utilities for worse health states. Distinct utilities for different IBD disease activity states can be used in health state transition models evaluating the cost-effectiveness of treatments for pediatric CD and UC.
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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 | 0.012 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".