<p>Relationship Between Pain Reduction and Improvement in Health-Related Quality of Life in Patients with Knee Pain Due to Osteoarthritis Receiving Duloxetine: Exploratory Post Hoc Analysis of a Japanese Phase 3 Randomized Study</p>
Bibliographic record
Abstract
PURPOSE: This post hoc analysis of a Japanese phase 3 randomized study (ClinicalTrials.gov identifier: NCT02248480) investigated relationships between changes in pain severity and changes in health-related quality of life (HRQoL) in duloxetine-treated patients with knee osteoarthritis (OA). PATIENTS AND METHODS: Patients with knee OA and Brief Pain Inventory (BPI) average pain score ≥4 received duloxetine 60 mg/day or placebo for 14 weeks. Spearman rank correlation coefficients were calculated for change in pain severity, as assessed by the BPI, and change in HRQoL, as assessed by the items of the (i) 36-item Short-Form Health Survey (SF-36; a generic measure of HRQoL) and (ii) Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC; an OA-specific measure of HRQoL). RESULTS: After 14 weeks of treatment, there was a significantly greater improvement (p<0.001) for duloxetine (n=177) vs placebo (n=176) in BPI average pain severity score and significantly greater improvements (p<0.01) for duloxetine vs placebo for 5 of the 8 SF-36 domains (including the Role-Physical, Bodily Pain, and Physical Functioning domains) and all 24 individual WOMAC items. The correlation between BPI change from baseline and SF-36 item change from baseline was statistically significant (p<0.05) for 2 of the 8 SF-36 items (Bodily Pain, Physical Functioning) in duloxetine-treated patients. The correlation between BPI change from baseline and WOMAC item change from baseline was statistically significant for 22 of the 24 WOMAC items in duloxetine-treated patients. CONCLUSION: This post hoc analysis suggested that the pain reduction observed in duloxetine-treated patients with knee OA was associated with improvements in OA-specific aspects of HRQoL, ie, pain and physical functioning.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".