Content validity of preference-based measures for economic evaluation in chronic obstructive pulmonary disease
Bibliographic record
Abstract
BACKGROUND: Generic preference-based measures (GPBMs) are health-related quality of life (HRQoL) measures commonly used to evaluate the cost-utility of interventions in healthcare. However, the degree to which the content of GPBMs reflect the HRQoL of individuals with chronic obstructive pulmonary disease (COPD) has not yet been assessed. The purpose of this study was to examine the content and convergent validity of GPBMs in people with COPD. METHODS: COPD patients were recruited from healthcare centers in Ontario, Canada. The Patient-Generated Index (PGI) (an individualized HRQoL measure) and the RAND-36 (to obtain SF-6D scores; a GPBM) were administered. Life areas nominated with the PGI were coded using the International Classification of Functioning Disability and Health and mapped onto GPBMs. RESULTS: We included 60 participants with a mean age of 70 and FEV1% predicted of 43. The mean PGI score was 34.55/100 and the top three overarching areas that emerged were: 'mobility' (25.93%), 'recreation and leisure' (25.19%) and 'domestic life' (19.26%). Mapping of the nominated areas revealed that the Quality of Well-Being scale covered the highest number of areas (84.62%), Health Utilities Indices covered the least (15.38% and 30.77%) and other GPBMs covered between 46 and 62%. A correlation of 0.32 was calculated between the SF-6D and the PGI. CONCLUSIONS: The majority of GPBMs covered approximately half of the areas reported as being important to individuals with COPD. When areas relevant to COPD are not captured, HRQoL scores generated by these measures may inaccurately reflect patients' values and affect cost-effectiveness decisions.
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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 | 0.080 | 0.286 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".