Cut-Offs for Disease Activity States in Axial Spondyloarthritis With Ankylosing Spondylitis Disease Activity Score (ASDAS) Based on C-Reactive Protein and ASDAS Based on Erythrocyte Sedimentation Rate: Are They Interchangeable?
Bibliographic record
Abstract
OBJECTIVE: Ankylosing Spondylitis Disease Activity Score based on C-reactive protein (ASDAS-CRP) is recommended over ASDAS based on erythrocyte sedimentation rate (ASDAS-ESR) to assess disease activity in axial spondyloarthritis (axSpA). Although ASDAS-CRP and ASDAS-ESR are not interchangeable, the same disease activity cut-offs are used for both. We aimed to estimate optimal ASDAS-ESR values corresponding to the established ASDAS-CRP cut-offs (1.3, 2.1, and 3.5) and investigate the potential improvement of level of agreement between ASDAS-ESR and ASDAS-CRP disease activity states when applying these estimated cut-offs. METHODS: We used data from patients with axSpA from 9 European registries initiating a tumor necrosis factor inhibitor. ASDAS-ESR cut-offs were estimated using the Youden index. The level of agreement between ASDAS-ESR and ASDAS-CRP disease activity states was compared against each other. RESULTS: In 3664 patients, mean ASDAS-CRP was higher than ASDAS-ESR at both baseline (3.6 and 3.4, respectively) and aggregated follow-up at 6, 12, or 24 months (1.9 and 1.8, respectively). The estimated ASDAS-ESR values corresponding to the established ASDAS-CRP cut-offs were 1.4, 1.9, and 3.3. By applying these cut-offs, the proportion of discordance between disease activity states according to ASDAS-ESR and ASDAS-CRP decreased from 22.93% to 19.81% in baseline data but increased from 27.17% to 28.94% in follow-up data. CONCLUSION: We estimated the optimal ASDAS-ESR values corresponding to the established ASDAS-CRP cut-off values. However, applying the estimated cut-offs did not increase the level of agreement between ASDAS-ESR and ASDAS-CRP disease activity states to a relevant degree. Our findings did not provide evidence to reject the established cut-off values for ASDAS-ESR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".