Patient‐reported outcomes in a randomized trial comparing four different treatment strategies in recent‐onset rheumatoid arthritis
Bibliographic record
Abstract
OBJECTIVE: To investigate the effectiveness of 4 different treatment strategies for recent-onset rheumatoid arthritis (RA) on 2-year patient-reported outcomes, including functioning and quality of life. METHODS: A total of 508 patients with recent-onset RA were randomly assigned to 1) sequential monotherapy, 2) step-up combination therapy, both starting with methotrexate, 3) initial combination therapy, including a tapered high-dose prednisone, or 4) initial combination therapy with methotrexate and infliximab. Treatment was adjusted every 3 months if the Disease Activity Score (DAS) remained >2.4. The McMaster Toronto Arthritis Patient Preference Disability Questionnaire, the Short Form 36 (SF-36), and scores for pain, global health, and disease activity measured on a 100-mm visual analog scale (VAS) were compared between groups at baseline and every 3 months thereafter for 2 years. RESULTS: After 2 years, all patient-reported outcomes had improved significantly from baseline, irrespective of the treatment strategy. SF-36 subscale scores approached population norms for 3 physical components, and achieved population norms (P > 0.05) for bodily pain and 4 mental components. Improvement in functioning, VAS scores, and physical items of the SF-36 occurred significantly earlier in patients treated with initial combination therapies (all comparisons after 3 months: overall P < 0.001; P < 0.05 for groups 1 and 2 versus groups 3 and 4). CONCLUSION: All 4 DAS-driven treatment strategies resulted in substantial improvements in functional ability, quality of life, and self-assessed VAS scores after 2 years. Initial combination therapy led to significantly faster improvement in all patient-reported measures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".