Triple therapy in early active rheumatoid arthritis: A randomized, single‐blind, controlled trial comparing step‐up and parallel treatment strategies
Bibliographic record
Abstract
OBJECTIVE: The Tight Control of Rheumatoid Arthritis study previously demonstrated that an intensive step-up disease-modifying antirheumatic drug (DMARD) treatment strategy targeting persistent disease activity was superior to routine care in the management of early rheumatoid arthritis (RA). We undertook this study to test the hypothesis that early parallel triple therapy achieves better outcomes than step-up therapy within an intensive disease management regimen. METHODS: Ninety-six patients with early RA (mean disease duration 11.5 months) were randomized to receive step-up therapy (sulfasalazine [SSZ] monotherapy, then after 3 months, methotrexate [MTX] was added, and when the maximum tolerated dosage of MTX was reached, hydroxychloroquine [HCQ] was added) or parallel triple therapy (SSZ/MTX/HCQ). All patients were assessed monthly for 12 months. If their disease activity score in 28 joints (DAS28) was > or =3.2, the dosage of DMARDs was increased according to protocol, and swollen joints were injected with triamcinolone acetonide (maximum dosage 80 mg per month). A metrologist who was blinded to the treatment allocation performed assessments every 3 months. The primary outcome measure was the mean decrease in the DAS28 score at 12 months. RESULTS: Both groups showed substantial improvements in disease activity and functional outcome. At 12 months, the mean decrease in the DAS28 score was -4.0 (step-up therapy group) versus -3.3 (parallel therapy group) (P = 0.163). No significant differences in the percentages of patients with DAS28 remission (step-up therapy group 45% versus parallel triple therapy group 33%), DAS28 good response (60% versus 41%, respectively), or American College of Rheumatology criteria for 20% improvement (ACR20) (77% versus 76%, respectively), ACR50 (60% versus 51%, respectively), or ACR70 (30% versus 20%, respectively) responses were seen. Radiologic progression was similar in both groups. CONCLUSION: This study confirms that highly effective control of disease activity can be achieved using conventional DMARDs as part of an intensive disease management strategy. Within this setting, step-up therapy is at least as effective as parallel triple therapy.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".