Utilities for asthma and COPD according to category of severity: a comprehensive literature review
Bibliographic record
Abstract
BACKGROUND: Asthma and chronic obstructive pulmonary disease (COPD) are incurable diseases that impact quality-of-life. OBJECTIVE: To summarize original research articles that measured or utilized preference-based utilities or disutilities according to disease severity. METHODS: Medline and Embase were searched from inception until the end of November 2014. Two reviewers independently searched the literature with differences settled through discussion. Data extracted included utility scores as determined in original research categorized according to disease severity as well as disutilities associated with exacerbations or comorbidities. Data were tabulated and analyzed descriptively. RESULTS: In total, 862 articles were identified, 790 were rejected, and 69 analyzed. There were 44 dealing with COPD and 25 with asthma. Average utilities determined by research were 0.828 ± 0.062, 0.765 ± 0.090, 0.711 ± 0.120, and 0.607 ± 0.120 for mild, moderate, severe, and very severe COPD, respectively. Utilities used in economic analyses were 0.866 ± 0.038, 0.770 ± 0.024, 0.739 ± 0.045, and 0.596 ± 0.075, respectively. Disutilities (annual) ranged from 0.002-0.378; major and minor exacerbations had respective disutilities of 0.287 and 0.108. For asthma patients, utilities were for 0.86 ± 0.32, 0.83 ± 0.065, and 0.74 ± 0.029, for mild, moderate, and severe disease, respectively. CONCLUSIONS: Utilities have been summarized according to severity category of asthma and COPD. These values should be useful for researchers undertaking economic analyses of these diseases.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.024 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| 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".