Incidence and Predictors of Biological Antirheumatic Drug Discontinuation Attempts among Patients with Rheumatoid Arthritis in Remission: A CORRONA and NinJa Collaborative Cohort Study
Bibliographic record
Abstract
OBJECTIVE: We conducted a longitudinal observational study of biological disease-modifying antirheumatic drugs (bDMARD) to describe the proportions of patients with rheumatoid arthritis in remission who discontinued these agents, and to assess the potential predictors of the decision to discontinue. METHODS: We used data from the US COnsortium of Rheumatology Researchers Of North America (CORRONA) and the Japanese National Database of Rheumatic Diseases by iR-net in Japan (NinJa) registries, and ran parallel analyses. Patients treated with bDMARD who experienced remission (defined by the Clinical Disease Activity Index ≤ 2.8) were included. The outcome of interest was the occurrence of bDMARD discontinuation while in remission. The predictors of discontinuation were assessed in the Cox regression models. Frailty models were also used to examine the effects of individual physicians in the discontinuation decision. RESULTS: The numbers of eligible patients who were initially in remission were 6263 in the CORRONA and 744 in the NinJa. Among these patients, 10.0% of patients in CORRONA and 11.8% of patients in NinJa discontinued bDMARD while in remission over 5 years, whereas many of the remaining patients lost remission before discontinuing bDMARD. Shorter disease duration was associated with higher rates of discontinuation in both cohorts. In CORRONA, methotrexate use and lower disease activity were also associated with discontinuation. In frailty models, physician random effects were significant in both cohorts. CONCLUSION: Among patients who initially experienced remission while receiving bDMARD, around 10% remained in remission and then discontinued bDMARD in both registries. Several factors were associated with more frequent discontinuation while in remission. Physician preference likely is also an important correlate of bDMARD discontinuation, indicating the need for standardization of practice.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".