Defining and characterizing sustained remission in patients with rheumatoid arthritis
Bibliographic record
Abstract
The objective of this study is to characterize stability and clinical features of patients with rheumatoid arthritis (RA) in sustained remission. Combination therapy with methotrexate and tumor necrosis factor inhibitors (TNFi) has increased remission rates in RA but optimal regimens to maintain remission are unknown. We describe Study of Etanercept And Methotrexate in Combination or as Monotherapy in Subjects with Rheumatoid Arthritis (SEAM-RA) and data from a run-in period of longitudinal observation. Patients in Simplified Disease Activity Index (SDAI) remission (score ≤ 3.3) receiving etanercept and methotrexate were screened and had to maintain remission over 3 run-in visits/24 weeks before randomization to combination therapy or withdrawal of etanercept or methotrexate. Baseline characteristics were examined for predictive factors for maintaining remission. As of November 2016, 141 patients have enrolled; of these, 64 have been randomized, 34 were ineligible after run-in, and 43 are in run-in period; 70% have completed run-in. Enrolled and randomized patients, respectively, had mean (standard deviation [SD]) disease duration 11.0 (8.6) and 12.6 (9.7) years; mean (SD) duration of etanercept use 4.2 (3.8) and 4.9 (4.2) years; mean (SD) methotrexate dose 15.9 (4.8) and 15.5 (4.9) mg/week; and mean (SD) SDAI scores 1.5 (0.9) and 1.4 (0.8). At enrollment, 73% and 63% were in Boolean remission based on 28 joints and 66/68 joints, respectively. No enrollment characteristic predicted successful completion of run-in. Two-thirds of patients considered to be in remission at enrollment sustained remission through 24 weeks. Baseline characteristics of enrolled patients and those who completed run-in were comparable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".