Benefit of biologics initiation in moderate versus severe rheumatoid arthritis: evidence from a United States registry
Bibliographic record
Abstract
Objectives: To compare clinical outcomes and treatment patterns among patients with moderate vs severe RA following biologic DMARD initiation. Methods: Biologics-naive patients with moderate to severe RA [Clinical Disease Activity Index (CDAI) >10] who initiated a biologic DMARD were selected from the Corrona registry (2001-13). CDAI, functional status [modified HAQ (mHAQ)] and patterns of drug use were compared at 1 and 2 years post-initiation between patients with moderate (CDAI >10⩽22) vs severe (CDAI >22) baseline disease activity. Results: A total of 1596 patients (817 severe, 779 moderate) had ⩾1 year of follow-up and 1269 (635 severe, 634 moderate) had ⩾2 years of follow-up. Patients with severe vs moderate baseline disease activity experienced greater improvements in disease activity [mean change in CDAI -18.9 vs -6.0 at year 1; -21.0 vs -7.1 at year 2 ( P < 0.0001)] and physical function [mean change in mHAQ -0.2 vs -0.1 ( P < 0.0001) at year 1; -0.2 vs -0.1 ( P = 0.0013) at year 2]. Greater proportions of patients with moderate vs severe disease activity achieved remission (CDAI ⩽2.8) [22.7 vs 15.8% ( P = 0.0003) at year 1; 25.9 vs 20.9% ( P = 0.0396) at year 2] or low disease activity (CDAI <10) [60.1 vs 41.2% at year 1; 66.7 vs 49.4% at year 2 ( P < 0.0001)]. Most patients remained on the original biologic drug (>70% at year 1; >62% at year 2). Conclusion: With biologic therapy, RA patients with higher baseline disease activity achieved greater improvements in measures of disease activity than those with lower levels of disease, but less often achieved the common targets of remission or low disease activity.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".