A review of the most common patient-reported outcomes in COPD – revisiting current knowledge and estimating future challenges
Bibliographic record
Abstract
Patient-reported outcome (PRO) measures that quantify disease impact have become important measures of outcome in COPD research and treatment. The objective of this literature review was to comprehensively evaluate psychometric properties of available PRO instruments and the ability of each of them to characterize pharmaceutical treatment effects from published clinical trial evidence. Identified in this study were several PRO measures, both those that have been used extensively in COPD clinical trials (St George's Respiratory Questionnaire and Chronic Respiratory Questionnaire) and new instruments whose full value is still to be determined. This suggests a great need for more information about the patient experience of treatment benefit, but this also may pose challenges to researchers, clinicians, and other important stakeholders (eg, regulatory agencies, pharmaceutical companies) who develop new treatment entities and payers (including but not limited to health technology assessment agencies such as the National Institute for Health and Care Excellence and the Canadian Agency for Drugs and Technologies in Health). The purpose of this review is to enable researchers and clinicians to gain a broad overview of PRO measures in COPD by summarizing the value and purpose of these measures and by providing sufficient detail for interested audiences to determine which instrument may be the most suitable for evaluating a particular research purpose.
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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".