Toward Defining Primary and Secondary Nonresponse in Rheumatoid Arthritis Patients Treated with Anti-TNF: Results from the BioTRAC and OBRI Registries
Bibliographic record
Abstract
OBJECTIVE: Although most patients with rheumatoid arthritis (RA) respond to anti-tumor necrosis factor (anti-TNF) treatment, some present with initial nonresponse (1ry nonresponse) or lose initial responsiveness (2ry nonresponse). We compared the rate of real-world "nonresponse" to first anti-TNF as reported by treating physicians to the nonresponse rate per accepted definitions and recommended treat-to-target strategies. METHODS: Patients were included from the Biologic Treatment Registry Across Canada (BioTRAC) and Ontario Best Practices Research Initiative (OBRI) registries who were taking their first anti-TNF, with ≥ 1 followup visit. Posthoc reclassification of physician-reported nonresponse was based on prior achievement of 28-joint count Disease Activity Score based on erythrocyte sedimentation rate (DAS28-ESR) low disease activity (LDA), Clinical Disease Activity Index (CDAI) LDA, or good/moderate European League Against Rheumatism (EULAR) response, and actual time of physician-reported nonresponse. RESULTS: Among 736 BioTRAC and 640 OBRI patients, 13.7% and 18%, respectively, discontinued their anti-TNF because of physician-reported nonresponse. Based on reclassification using disease activity, 65.6% (BioTRAC) and 87.2% (OBRI) of 1ry nonresponders did not achieve DAS28-ESR LDA, 65.6%/90.7% CDAI LDA, and 46.9%/61.5% good/moderate EULAR response. Among 2ry nonresponders, 50.7%/47.8% did not achieve DAS28-ESR LDA, 37.7%/52.9% CDAI LDA, and 15.9%/19.6% good/moderate EULAR response before treatment discontinuation. Regarding actual time of nonresponse, 18.8% of BioTRAC and 60.8% of OBRI 1ry nonresponders discontinued at ≤ 6 months. In both registries, a high proportion of 2ry nonresponders discontinued their anti-TNF after 12 months (87.0% BioTRAC, 60.9% OBRI). CONCLUSION: Physician-reported 1ry nonresponse was more correlated with non-achievement of DAS28-ESR LDA or CDAI LDA, whereas 2ry nonresponse with actual time of discontinuation. Further work is needed to confirm the importance of response and type of response to the initial anti-TNF in identifying patients most likely to benefit from a second biologic agent 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 | 0.036 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".