Frequency of difficult-to-manage and treatment-refractory axial SpA: insights from the German RABBIT-SpA register using recent ASAS definitions
Bibliographic record
Abstract
OBJECTIVES: To determine the frequency of axial SpA (axSpA) patients fulfilling the recently proposed Assessment of SpondyloArthritis International Society (ASAS) definitions for difficult-to-manage (D2M) and treatment-refractory (TR) axSpA, and to characterize these patients at initiation of their first advanced therapy. METHODS: Data were derived from the ongoing prospective, multicentre, longitudinal German RABBIT-SpA registry. Patients were eligible if they were biologic and targeted synthetic (b/ts) DMARD-naïve, had initiated a b/tsDMARD and had ≥12 months of follow-up. ASAS definitions were applied to identify cases of D2M and TR. RESULTS: Of 1850 patients with axSpA, 881 (48%) were b/tsDMARD-naïve at the start of observation. A total of 75/881 patients (8.5%) fulfilled the ASAS criteria for D2M and 22/881 (2.5%) additionally met the criteria for TR. At baseline, D2M patients were more frequently female, more often HLA-B27-negative, and more commonly presented with arthritis and enthesitis compared with not-D2M (nD2M) patients. In addition, they exhibited fewer objective inflammatory markers such as elevated CRP or MRI lesions. Opioid use was higher across D2M patients compared with nD2M patients. In the TR group compared with the D2M/nTR, the proportion of female and of obesity was lower. Even at initiation of first-line b/tsDMARD, these patients showed more frequently signs of inflammation, including sacroiliac/spinal MRI lesions and elevated CRP, while peripheral arthritis was less frequent. CONCLUSION: Applying the ASAS definitions in a large real-world cohort identified clinically relevant subgroups with D2M and TR. These findings support their clinical utility and highlight the need for phenotype-specific management strategies.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".