Quality appraisal of clinical practice guidelines and consensus statements on the use of biologic agents in rheumatoid arthritis: A systematic review
Bibliographic record
Abstract
OBJECTIVE: To evaluate the quality of clinical practice guidelines (CPGs) and consensus statements (CS) for the treatment of rheumatoid arthritis with tumor necrosis factor alpha (TNFalpha) antagonists. METHODS: We searched for CPGs and CS on the use of infliximab, etanercept, and/or adalimumab for the treatment of rheumatoid arthritis, published through October 10, 2006. Sources included electronic databases (Medline, EMBase, BIOSIS, etc.), guideline registries, and pertinent Web sites. Review of 4,915 citations revealed 16 CPGs and 20 CS. Two independent reviewers evaluated development methods of selected studies using the 23-item Appraisal of Guidelines for Research and Evaluation (AGREE) instrument and compared recommendations between guidelines. RESULTS: Of the 16 guidelines, only 5 (31%) were based on a systematic review of relevant research evidence. Only 4 (25%) of the guidelines fulfilled > or = 60% of the AGREE criteria. AGREE scores were lower for guidelines from rheumatology societies than government agencies when reporting scope and purposes (P = 0.03), stakeholder involvement (P = 0.03), and clarity and presentation (P = 0.01). Guidelines scored higher than CS in most domains. Overall, guideline recommendations were consistent with respect to the use of biologic agents after failure of disease-modifying antirheumatic drugs, but differed or did not provide specific guidance on tests for screening. CONCLUSION: Guidelines for introducing TNFalpha antagonists in rheumatoid arthritis often fail to meet expected methodologic criteria and therefore vary significantly in quality and with respect to some recommendations for patient assessment and management.
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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 | 0.213 | 0.596 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.010 |
| Bibliometrics | 0.026 | 0.024 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".