Assessing Disease Activity in Axial Spondyloarthritis: Finding the Balance Between the Bath Ankylosing Spondylitis Disease Activity Index and Axial Spondyloarthritis Disease Activity Score
Bibliographic record
Abstract
Axial spondyloarthritis (axSpA) is a chronic inflammatory condition that significantly affects patients’ quality of life.1 Accurate assessment of disease activity is critical for both clinical decision making and evaluating treatment response. The 2 most widely used measures of disease activity, the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and the Axial Spondyloarthritis Disease Activity Score (ASDAS), have been extensively studied for their clinical utility, correlation with other disease outcomes, and sensitivity to response to treatments.2 In this editorial, the findings of Alonso et al in their study, “Performance of disease activity indices used in axial spondyloarthritis in real-world clinical settings,”3 are reviewed and their results compared with previous research evaluating ASDAS and BASDAI. The study by Alonso et al aimed to assess the comparative performance of ASDAS and BASDAI in real-world clinical practice.3 This cross-sectional study analyzed 330 patients meeting the Assessment of SpondyloArthritis international Society (ASAS) criteria for axSpA.4 The study found a high correlation between ASDAS and BASDAI (Pearson r ≥ 0.73), with substantial concordance in activity classification (weighted κ ≥ 0.61). BASDAI cutoffs of 3.95 and 5.85 corresponded to ASDAS high and very high activity categories, respectively, whereas ASDAS ≥ 2.1 and BASDAI ≥ 3 accurately identified high-impact disease according to the ASAS Health Index (ASAS HI). The findings suggest that both indices perform similarly in routine clinical settings and may be used interchangeably. This result is also supported by previous studies showing high correlation between the 2 indices.5,6 Several studies have previously examined the comparative accuracy, sensitivity, and correlation of ASDAS and BASDAI in axSpA.6,7 Both indices show good correlation with patient and physician global assessments.8 In this study by Alonso et al, ASDAS and BASDAI demonstrate similar discriminative ability between high disease activity … Address correspondence to Prof. A.T.Y. Chan, University Department of Rheumatology, Royal Berkshire NHS Foundation Trust, Craven Road, Reading, Berkshire, RG1 5AN, UK. Email: antoni.chan{at}nhs.net.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".