Adherence to the OARSI recommendations for designing, conducting, and reporting of clinical trials in knee osteoarthritis: a targeted literature review
Bibliographic record
Abstract
BACKGROUND: The Osteoarthritis Research Society International (OARSI) updated their guideline for clinical trials on knee osteoarthritis (KOA) in 2015, which contains recommendations for the conduct, design, and reporting of clinical trials. The purpose of this study was to assess the quality of clinical trials published between 2010 and 2020 investigating intra-articular interventions in patients with KOA using the OARSI recommendations. METHODS: A targeted literature review was conducted to identify randomized controlled trials in patients with KOA receiving intra-articular interventions, published between 2010 and 2020. Included studies were assessed using the OARSI recommendations. For a comparison between the time periods before and after the introduction of the new OARSI recommendations, the year 2016 was selected as the cut-off. RESULTS: One hundred forty-eight publications, representing 139 unique trials, were included in this review. Included studies adhered to between 9 and 24 recommendations (median: 19). The highest increase in adherence from studies published in 2016 or earlier compared to after 2016 was seen in the reporting and registration of trials and the use of structural outcome measures. Overall, adherence to the recommendations related to the collection of biochemical biomarkers and the use of structural outcome measures remained low. CONCLUSION: An improvement can be made in the conduct, design, and reporting of clinical trials for intra-articular therapies in KOA. Despite proper guidelines, quality of clinical trials varies, and the methodological deficiencies found are preventable and can be corrected. The quality of research should be considered when making treatment decisions for patients with KOA in clinical practice.
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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 | 0.572 | 0.769 |
| Meta-epidemiology (narrow) | 0.002 | 0.005 |
| Meta-epidemiology (broad) | 0.013 | 0.017 |
| Bibliometrics | 0.024 | 0.020 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.014 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".