Efficacy and safety of plant-derived products for the treatment of osteoarthritis
Bibliographic record
Abstract
\nLaura L Laslett, Xingzhong Jin, Graeme Jones Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia Background: Plant-derived therapies are traditionally used as medicines, but they have generally not been studied with the same rigor as pharmaceutical agents. This review summarizes the use of plant-derived products for osteoarthritis. Methods: Sixty-three identified trials were summarized for pain, function, and safety outcomes using standardized mean differences (SMDs) and relative risks. Results: Plant-derived therapies are effective for treating pain compared to placebo, as assessed using visual analog scores and numerical rating scales (SMD, 1.08; 95% confidence interval [CI]: 0.72–1.44), or Western Ontario and McMaster University Osteoarthritis Index (WOMAC)/Knee injury and Osteoarthritis Outcome Score (KOOS) pain scales (SMD, 0.98; 95% CI: 0.62–1.35). Classes demonstrating overall efficacy in more than one trial for either visual analog scores or WOMAC pain included Boswellia serrata, capsaicin, and ginger; there was single-trial evidence of the efficacy of another nine agents. Plant-derived therapies have similar efficacy to an active comparator (SMD, 0.32; P=0.08; -0.08; P=0.14). Therapies are also effective for functional outcomes compared to placebo (SMD, 0.92; P<0.001). However, significant heterogeneity remains for all pain and function outcomes, indicating that the results need to be interpreted with caution. Risk of adverse events was similar to placebo (relative risk =1.13; P=0.1), but reduced compared to an active comparator (relative risk, 0.75; P<0.001). Conclusion: Plant-derived therapies may be efficacious in treating osteoarthritic pain and functional limitations, and they appear to be safer than other active therapies. However, quality trials and long-term data are lacking, and the number of trials for each therapy is limited. Comparisons would be assisted by trial standardization. Keywords: phytotherapy, plant extract, herbal, review, meta-analysis, osteoarthritis
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".