Assessing responsiveness of generic and specific health related quality of life measures in heart failure
Bibliographic record
Abstract
BACKGROUND: Responsiveness, or sensitivity to clinical change, is an important consideration in selection of a health-related quality of life (HRQL) measure for trials or clinical applications. Many approaches can be used to assess responsiveness, which may affect the interpretation of study results. We compared the relative responsiveness of generic and heart failure specific HRQL instruments, as measured both by common psychometric indices and by external clinical criteria. METHODS: We analyzed data collected at baseline and 6-weeks in 298 subjects with heart failure on the following HRQL measures: EQ-5D (US, UK, and VAS Scoring), Kansas City Cardiomyopathy Questionnaire (KCCQ) (Clinical and Overall Summary Score), and RAND12 (Physical and Mental Component Summaries). Three external indicators of clinical change were used to classify subjects as improved, deteriorated, or unchanged: 6-minute walk test, New York Heart Association (NYHA) class, and physician global rating of change. Four responsiveness statistics (T-test, effect size, Guyatt's responsiveness statistic, and standardized response mean) were used to evaluate the responsiveness of the select measures. The median rank of each HRQL measure across responsiveness indices and clinical criteria was then determined. RESULTS: Average age of subjects was 60 years, 75 percent were male, and had moderate to severe heart failure symptoms. Overall, the KCCQ Summary Scores had the highest relative ranking, irrespective of the responsiveness index or external criterion used. Importantly, we observed that the relative ranking of responsiveness of the generic measures (i.e. EQ-5D, RAND12) was influenced by both the responsive indices and external criterion used. CONCLUSION: The disease specific KCCQ was the most responsive HRQL measure assessing change over a 6-week period, although generic measures provide information for which the KCCQ is not suitable. The responsiveness of generic HRQL measures may be affected by the index used, as well as the external criterion to classify patients who have clinically change or remained stable.
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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 | 0.052 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".