Efficacy and Safety of Intra-Articular Cell-Based Therapy for Osteoarthritis: Systematic Review and Network Meta-Analysis
Bibliographic record
Abstract
ObjectiveOsteoarthritis (OA) is a chronic joint disease characterized by degeneration of articular cartilage and secondary osteogenesis. Cell-based agents, such as mesenchymal stem cells, have turned into the most extensively explored new therapeutic agents for OA. However, evidence-based research is still lacking.MethodsWe searched public databases up to February 2020 and only included randomized controlled trials. The outcomes included the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the Knee Injury and Osteoarthritis Outcome Score (KOOS), the visual analogue scale (VAS) score, and serious adverse events (SAEs). A network meta-analysis was also performed in this work.ResultsWe included 13 studies in the meta-analysis. The effect size showed that cell-based therapy did not significantly reduce the WOMAC score at the 6-month follow-up (standard mean difference [SMD] −3.6; 95% confidence interval [CI] −0.90 to 0.18; <i>P</i> = 0.1928). However, cell-based therapy significantly improved the KOOS at the 12-month follow-up (SMD 0.68; 95% CI 0.07-1.30; <i>P</i> = 0.0288) and relieved pain (SMD −1.05; 95% CI −1.46 to −0.64; <i>P</i> < 0.0001). The findings also indicated that high-dosage adipose-derived mesenchymal stem cells (ADMSCs) may be more advantageous in terms of long-term effects.ConclusionsCell-based therapy had a better effect on KOOS improvement and pain relief without safety concerns. However, cell-based therapy did not show a benefit in terms of the WOMAC. Allogeneic cells might have advantages compared to controls in the WOMAC and KOOS scores. The long-term effect of high-dose ADMSC treatment for OA is worthy of further study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".