Golimumab, a human antibody to tumour necrosis factor α given by monthly subcutaneous injections, in active rheumatoid arthritis despite methotrexate therapy: the GO-FORWARD Study
Bibliographic record
Abstract
OBJECTIVE: The phase III GO-FORWARD study examined the efficacy and safety of golimumab in patients with active rheumatoid arthritis (RA) despite methotrexate therapy. METHODS: Patients were randomly assigned in a 3 : 3 : 2 : 2 ratio to receive placebo injections plus methotrexate capsules (group 1, n = 133), golimumab 100 mg injections plus placebo capsules (group 2, n = 133), golimumab 50 mg injections plus methotrexate capsules (group 3, n = 89), or golimumab 100 mg injections plus methotrexate capsules (group 4, n = 89). Injections were administered subcutaneously every 4 weeks. The co-primary endpoints were the proportion of patients with 20% or greater improvement in the American College of Rheumatology criteria (ACR20) at week 14 and the change from baseline in the health assessment questionnaire-disability index (HAQ-DI) score at week 24. RESULTS: The proportion of patients who achieved an ACR20 response at week 14 was 33.1% in the placebo plus methotrexate group, 44.4% (p = 0.059) in the golimumab 100 mg plus placebo group, 55.1% (p = 0.001) in the golimumab 50 mg plus methotrexate group and 56.2% (p<0.001) in the golimumab 100 mg plus methotrexate group. At week 24, median improvements from baseline in HAQ-DI scores were 0.13, 0.13 (p = 0.240), 0.38 (p<0.001) and 0.50 (p<0.001), respectively. During the placebo-controlled portion of the study (to week 16), serious adverse events occurred in 2.3%, 3.8%, 5.6% and 9.0% of patients and serious infections occurred in 0.8%, 0.8%, 2.2% and 5.6%, respectively. CONCLUSION: The addition of golimumab to methotrexate in patients with active RA despite methotrexate therapy significantly reduced the signs and symptoms of RA and improved physical function.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".