Disease Activity, Physical Function, and Radiographic Progression After Longterm Therapy with Adalimumab Plus Methotrexate: 5-Year Results of PREMIER
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy and safety of initial combination treatment with adalimumab (ADA) and methotrexate (MTX) versus monotherapy with ADA or MTX during an open-label extension of PREMIER. METHODS: Patients with early rheumatoid arthritis (RA) received blinded ADA plus MTX, ADA alone, or MTX alone for 2 years in PREMIER. At Year 2, patients could enroll in an open-label extension and receive ADA monotherapy; MTX could be added at the investigator's discretion. Longterm efficacy results are presented as observed data. RESULTS: In the open-label period, 497 of the original 799 randomized patients had ≥ 1 dose of ADA (by original randomization: ADA plus MTX, n = 183; ADA, n = 159; MTX, n = 155). In the completers cohort [patients with available Year-5 ACR responses and modified total Sharp scores (mTSS)], the Year-5 mean change from baseline in mTSS for the ADA+MTX arm (n = 124) was 2.9, compared with 8.7 and 9.7 in the ADA (n = 115) and MTX (n = 115) arms. Comprehensive disease remission, defined as the combination of DAS28 remission, normal function (Health Assessment Questionnaire ≤ 0.5), and radiographic nonprogression (ΔmTSS ≤ 0.5), was achieved by more patients in the initial ADA+MTX arm (35%) than in the ADA (13%) or MTX (14%) arms. CONCLUSION: Initial combination treatment with ADA plus MTX, followed by open-label ADA, led to better longterm clinical, functional, and radiographic outcomes than either initial ADA or MTX monotherapy during 5 years of treatment.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".