AB0970 GREAT DIVERSITY IN B/TSDMARD TREATMENT IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS AROUND THE WORLD AND THE COMPARISONS WITH THE 2022 UPDATED ASAS-EULAR RECOMMENDATIONS
Bibliographic record
Abstract
Background The 2022 updated ASAS-EULAR recommendations for the management of axial spondyloarthritis (SpA) uses the Ankylosing Spondylitis Disease Activity Scores(ASDAS) ≥2.1 as the single disease activity index indicated for the using of b/tDMARDs. Unlike the care of rheumatoid arthritis, there is a diversity in the disease activity criteria for b/tsDMARDs in axSpA worldwide, which is worthy of note. Objectives This study aimed to investigate the diversity of b/tsDMARDs using in axSpA care worldwide in the light of the 2022 ASAS-EULAR recommendations for SpA, by comparing the population fulfilled each disease activity criteria indicated for b/tsDMARDs. Methods Biologic-naïve patients fulfilled the ASAS axSpA criteria were recruited in the rheumatology clinic in the Shuang-Ho Hospital from 2018 to 2020. In each visit, disease activity including BASDAI, ASDAS-CRP, ESR and CRP were recorded and the fulfillment of different disease activity criteria indicated for b/tsDMARDs were labelled, including the latest two versions of ASAS-EULAR recommendations and the reimbursement criteria of Australia, Singapore, Korea, Hong Kong, Canada and Taiwan. The data having the highest disease activity of each patient were selected for analysis, and the complete data including every visit recorded were also analyzed as sensitivity test. The population size fulfilled different activity criteria were compared. Results This study recruited 396 biologic-naive patients with axSpA with 1390 disease activity data totally. The mean age was 41 years, and among the cohort, 129(32.6%) were female. In the 396 disease activity measures, there were 262(66.2%) patients met the disease activity criteria for b/tsDMARDs according to the 2022 ASAS-EULAR recommendations, which was more than twice the population (121) indicated by the activity criteria of the prior version. In comparison with the 2022 recommendations, the disease activity criteria of many countries are stricter leading to less b/tsDMARDs using. Using the population indicated by the 2022 recommendations as reference, the rate of patients eligible by the disease activity criteria in different countries varied greatly, which ranged from as low as 8.40% in Taiwan to 100% in Singapore. The result was consistent in analyzing the whole 1390 dataset. Conclusion There is a great expansion of the population indicated for b/tsDMARDs brought by the 2022 update, in comparison with the 2016 version. There is a great diversity for b/tsDMARDs using in axSpA care around the world. In some countries, a surprisingly huge disparity in b/tsDMARDs using was noted. Only less than 10% patients indicated for b/tsDMARDs using by the 2022 ASAS-EULAR recommendation met the reimbursement criteria in Taiwan, analyzed in the single measure setting. REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests None Declared.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".