A phase III placebo- and oxycodone-controlled study of tanezumab in adults with osteoarthritis pain of the hip or knee
Bibliographic record
Abstract
Tanezumab is a humanized monoclonal antinerve growth factor antibody in development for treatment of chronic pain. In a phase III, placebo- and active-controlled study, we investigated the efficacy and safety of tanezumab for osteoarthritis (OA) hip or knee pain. Patients (N=610) received up to 2 doses of intravenous tanezumab (5 or 10mg in 8-week intervals), controlled-release oral oxycodone (10 to 40 mg every 12 hours), or placebo. The primary endpoint was mean change from baseline to week 8 in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Pain score for tanezumab versus placebo and oxycodone. Secondary endpoints included change from baseline in WOMAC Physical Function and Stiffness scores, Patient's Global Assessment (PGA) of OA, and patient response, defined as ≥ 30%, ≥ 50%, ≥ 70%, and ≥ 90% improvement from baseline in WOMAC Pain score. Tolerability and safety also were assessed. Both tanezumab groups demonstrated significant improvements in WOMAC Pain score versus placebo (P<.001) and oxycodone (P ≤.018). Tanezumab also provided significant improvements versus placebo and oxycodone for WOMAC Physical Function and Stiffness scores and PGA of OA (P ≤.002 for all) at week 8. For all analyses, oxycodone did not differ from placebo. Adverse event frequency was higher with oxycodone (63.3%) than tanezumab (40.7% to 44.7%) or placebo (35.5%); serious adverse event frequency was similar among treatments. The adverse event profile for tanezumab was similar to previous tanezumab studies. Results indicate that tanezumab is efficacious in the treatment of OA pain; no new safety signals were identified.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".