Simplified Ankylosing Spondylitis Disease Activity Score (SASDAS) Versus ASDAS: A Post Hoc Analysis of a Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To compare the Simplified Ankylosing Spondylitis Disease Activity Score (SASDAS) against the Ankylosing Spondylitis Disease Activity Score (ASDAS) for measuring and categorizing disease activity using data from the EMBARK trial (ClinicalTrials.gov: NCT01258738), a randomized controlled trial of etanercept (ETN) for axial spondyloarthritis (axSpA). METHODS: Patients with early active axSpA received ETN 50 mg once weekly (n = 106) or placebo (PBO; n = 109) for 12 weeks in a double-blind manner; they then received open-label ETN for 92 weeks. For this analysis, ASDAS-C-reactive protein (CRP) and SASDAS-CRP were calculated at baseline, week 12, and week 24. The SASDAS was calculated by the linear addition of the ASDAS components without adjustment. RESULTS: A very strong correlation, as determined by the Spearman correlation coefficient, was observed between the ASDAS and SASDAS for continuous variables at baseline and during treatment. For pooled categorical data at baseline, the SASDAS placed 69.9% of patients in the same disease categories as the ASDAS but overestimated for 17.8% of patients and underestimated for 12.2% of patients. A similar pattern was seen postbaseline. Cohen weighted [Formula: see text] statistics for all individual and pooled treatments and timepoints (0.54-0.73) reflected moderate to substantial agreement. The capacity to differentiate between treatments (ie, ETN and PBO/ETN) was higher with the ASDAS (effect size -0.74, 95% CI -1.03 to -0.46) compared with the SASDAS (effect size -0.51, 95% CI -0.79 to -0.23), but sensitivity to change was generally similar. CONCLUSION: A very strong correlation between the SASDAS and ASDAS was observed when considering continuous variables; however, moderate to substantial agreement was observed for categorical data, and the SASDAS classified a lower proportion of patients as being in the inactive and low disease activity categories.
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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 | 0.019 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".