A Comparison of Preference-Based, Generic and Disease-Specific Health-Related Quality of Life in Pediatric Inflammatory Bowel Disease
Bibliographic record
Abstract
Objective: Generic preference-based HRQOL assessments used expressly for economic evaluation have not been examined in pediatric Crohn's disease (CD) and ulcerative colitis (UC). The objective was to further assess the construct validity of preference-based HRQOL measures in pediatric IBD by comparing the Child Health Utility 9 Dimensions (CHU9D) and Health Utilities Index (HUI) to the disease-specific IMPACT-III and to the generic PedsQL in children with CD and with UC. Methods: The CHU9D, HUI, IMPACT-III and/or PedsQL were administered to Canadian children aged 6 to 18 years with CD and UC. CHU9D total and domain utilities were calculated using adult and youth tariffs. HUI total and attribute utilities were determined for the HUI2 and HUI3. Total scores for IMPACT-III and PedsQL were determined. Spearman correlations were calculated between generic preference-based utilities and the IMPACT-III and PedsQL scores. Results: The questionnaires were administered to 157 children with CD and 73 children with UC. Moderate to strong correlations were observed between the CHU9D, HUI2, HUI3 and the disease-specific IMPACT-III or generic PedsQL. As hypothesized, domains with similar constructs demonstrated stronger correlations, such as the Pain and Well-being domains. Conclusions: While all questionnaires were moderately correlated with the IMPACT-III and PedsQL questionnaires, the CHU9D using youth tariffs and the HUI3 were most strongly correlated and would be suitable choices to generate health utilities for children with CD or UC for the purpose of economic evaluation of treatments in pediatric IBD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".