What Is Most Important in Rheumatoid Arthritis Treatment — Where You Are, Who You Are, or Where You Are Going?
Bibliographic record
Abstract
The treatment of rheumatoid arthritis (RA) has been revolutionized by the expansion of conventional (c) and biologic (b) disease-modifying antirheumatic drug (DMARD) choices and the early aggressive treatment of RA to a target of remission or low disease activity, an approach endorsed in major RA treatment guidelines1,2. But if you search these guidelines for the words sex, gender, man, woman, men, women, male, and female, you will find these words appear only twice — once in a figure legend describing hepatitis B risk factors and the other in the title of a reference. While sex is not influencing RA treatment recommendations, is it influencing RA treatment choices in the real-world setting? In this issue of The Journal , Bergstra and colleagues asked whether sex differences exist in the selection of initial RA treatments and whether sex influences treatment response3. Bergstra and colleagues used data from the Measurement of Efficacy of Treatment in the Era of Outcome in Rheumatology (METEOR) registry, an international observational registry that records data from routine clinical practice — truly a real-“world” study. The authors selected over 5000 patients with RA diagnosed in the last 3 months who were not in Disease Activity Score (DAS) remission and were initiating their first DMARD. The authors evaluated initial treatment patterns: both general approaches (e.g., monotherapy vs combination therapy ± glucocorticoids) and specific DMARD within these general approaches. Subsequently, they assessed the influence of sex on treatment response, measured by time to switching DMARD and trajectories of the DAS and Health Assessment Questionnaire (HAQ) scores. They found that general approaches in initial RA management were identical between the sexes, but they detected differences in the choice of specific DMARD. Men were more likely than women to start a regimen that contained methotrexate (MTX) or … Address correspondence to Dr. B.R. England, 983025 Nebraska Medical Center, Omaha, Nebraska 68198-3025, USA.
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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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".