Assessing bias in osteoarthritis trials included in Cochrane reviews: protocol for a meta-epidemiological study
Bibliographic record
Abstract
INTRODUCTION: The validity of systematic reviews and meta-analysis depends on methodological quality and unbiased dissemination of trials. Our objective is to evaluate the association of estimates of treatment effects with different bias-related study characteristics in meta-analyses of interventions used for treating pain in osteoarthritis (OA). From the findings, we hope to consolidate guidance on interpreting OA trials in systematic reviews based on empirical evidence from Cochrane reviews. METHODS AND ANALYSIS: Only systematic reviews that compare experimental interventions with sham, placebo or no intervention control will be considered eligible. Bias will be assessed with the risk of bias tool, used according to the Cochrane Collaboration's recommendations. Furthermore, center status, trial size and funding will be assessed. The primary outcome (pain) will be abstracted from the first appearing forest plot for overall pain in the Cochrane review. Treatment effect sizes will be expressed as standardised mean differences (SMDs), where the difference in mean values available from the forest plots is divided by the pooled SD. To empirically assess the risk of bias in treatment benefits, we will perform stratified analyses of the trials from the included meta-analyses and assess the interaction between trial characteristics and treatment effect. A relevant study-level covariate is defined as one that decreases the between-study variance (τ(2), estimated as Tau-squared) as a consequence of inclusion in the mixed effects statistical model. ETHICS AND DISSEMINATION: Meta-analyses and randomised controlled trials provide the most reliable basis for treatment of patients with OA, but the actual impact of bias is unclear. This study will systematically examine the methodological quality in OA Cochrane reviews and explore the effect estimates behind possible bias. Since our study does not collect primary data, no formal ethical assessment and informed consent are required. TRIAL REGISTRATION NUMBER: PROSPERO (CRD42013006924).
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchMeta-epidemiology (broad)Meta-epidemiology (narrow) Domain: Methods · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| gpt | MetaresearchMeta-epidemiology (narrow)Meta-epidemiology (broad) Domain: Methods · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.160 | 0.307 |
| Meta-epidemiology (narrow) | 0.011 | 0.010 |
| Meta-epidemiology (broad) | 0.027 | 0.030 |
| Bibliometrics | 0.015 | 0.020 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.013 | 0.021 |
| Insufficient payload (model declined to judge) | 0.107 | 0.023 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".