Clinical Outcomes of Tanezumab With Different Dosages for Patient With Osteoarthritis: Network Meta-Analysis
Bibliographic record
Abstract
Background: Osteoarthritis (OA) high disability rate will increase as people getting older, and is the most prevalent form of arthritis in the future. This study identified the clinical effects of optimum doses of tanezumab for patients with OA. Method: Three electronic databases were searched up until January 15, 2021. The mean difference (MD) or odds ratio (OR) was considered an effect measure. The design-by-treatment interaction model was adopted for network meta-analyses. Analyses were conducted using WinBUGS 1.4.3 and R 4.0.5 software. Results: nine publications with 10 studies were included. Compared with placebo in network meta-analysis, except the outcomes of Western Ontario and McMaster Universities Osteoarthritis (WOMAC) stiffness subscale and joints replaced, all dosages of tanezumab in the other effectiveness outcome were superior to placebo, and the difference was statistically significant. However, there was no statistical difference among all different doses of tanezumab. Compared with placebo, except the outcomes of adverse events (AEs) and AEs of abnormal peripheral sensation, all different dosages of tanezumab weren’t superior to placebo in the other effectiveness outcome, and the difference was statistically significant. The 10 mg of tanezumab with highest SUCRA had the best effect, but it was associated with a higher safety event. Compared with placebo, except the outcomes of WOMAC stiffness subscale and joints replaced, all dosages of tanezumab in the other effectiveness outcome were superior to placebo, and the difference was statistically significant. Compared with placebo, except for the outcomes of AEs and AEs of abnormal peripheral sensation, all dosages of tanezumab in the other effectiveness outcome were superior to placebo, and the difference was statistically significant. Other direct comparisons showed no statistical difference. Conclusion: This study recommended that clinicians should give priority to the treatment of OA patients with a low dose of 2.5 mg according to the patient’s condition and actual situation. If the effect using tanezumab with 2.5 mg is not satisfactory, the increase up to 10 mg should be carefully pondered, because of a more unbalanced risk/benefit ratio.
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.044 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".