Rheumatoid Arthritis: Are Current Research-based Guidelines Clinically Relevant?
Bibliographic record
Abstract
In this issue of The Journal , Ciubotariu, et al 1 examine joint damage and progression in patients with rheumatoid arthritis during clinical remission. They report less erosion progression in patients receiving biologic disease-modifying antirheumatic drugs (DMARD) compared to nonbiologic DMARD (nbDMARD). In addition, scores on the Health Assessment Questionnaire-Disability Index (HAQ-DI), a secondary outcome of disability, were better for patients taking biologics than for those taking nbDMARD. Despite the statistically significant differences noted, the changes were very small and one might wish to consider whether statistical differences translate into clinically relevant ones. First, there are issues with the meaning of small changes in radiological progress. Second, there are more basic issues regarding the pathogenetic meaning when radiographs do not change. The minimal clinically important difference in radiographic progression is variable depending on the methods used, ranging from 2.3–5.5 units using the Larsen vs the Sharp/van der Heijde methods2. With changes of only 0.9 (adjusted data) in the biologic DMARD and 1.37 in the nbDMARD groups over 3 years in radiographic progression, it is clear that the differences are far below this number. Even if one assumes a linear change per year (not at all guaranteed), this means that using a difference in the rate of erosion of 0.4 units per year, one would need a minimum of 6–13 years of therapy to reach even a minimal clinically significant difference between treatments, radiographically. If not radiographically different, does this study posit a clinically significant … Address correspondence to Dr. Furst. E-mail: defurst{at}mednet.ucla.edu
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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 | 0.103 | 0.322 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.014 | 0.006 |
| Research integrity | 0.036 | 0.038 |
| Insufficient payload (model declined to judge) | 0.007 | 0.010 |
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".