Tanezumab for the Treatment of Pain from Osteoarthritis of the Knee
Bibliographic record
Abstract
BACKGROUND: Increased expression of nerve growth factor in injured or inflamed tissue is associated with increased pain. This proof-of-concept study was designed to investigate the safety and analgesic efficacy of tanezumab, a humanized monoclonal antibody that binds and inhibits nerve growth factor. METHODS: We randomly assigned 450 patients with osteoarthritis of the knee to receive tanezumab (administered at a dose of 10, 25, 50, 100, or 200 μg per kilogram of body weight) or placebo on days 1 and 56. The primary efficacy measures were knee pain while walking and the patient's global assessment of response to therapy. We also assessed pain, stiffness, and physical function using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC); the rate of response using the criteria of the Outcome Measures for Rheumatology Committee and Osteoarthritis Research Society International Standing Committee for Clinical Trials Response Criteria Initiative (OMERACT-OARSI); and safety. RESULTS: When averaged over weeks 1 through 16, the mean reductions from baseline in knee pain while walking ranged from 45 to 62% with various doses of tanezumab, as compared with 22% with placebo (P<0.001). Tanezumab, as compared with placebo, was also associated with significantly greater improvements in the response to therapy as assessed with the use of the patients' global assessment measure (mean increases in score of 29 to 47% with various doses of tanezumab, as compared with 19% with placebo; P≤0.001). The rate of response according to the OMERACT-OARSI criteria ranged from 74 to 93% with tanezumab treatment, as compared with 44% with placebo (P<0.001). The rates of adverse events were 68% and 55% in the tanezumab and placebo groups, respectively. The most common adverse events among tanezumab-treated patients were headache (9% of the patients), upper respiratory tract infection (7%), and paresthesia (7%). CONCLUSIONS: In this proof-of-concept study, treatment with tanezumab was associated with a reduction in joint pain and improvement in function, with mild and moderate adverse events, among patients with moderate-to-severe osteoarthritis of the knee. (Funded by Rinat Neuroscience; ClinicalTrials.gov number, NCT00394563.).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".