The Minimum Clinically Important Improvement and Patient-acceptable Symptom State in the BASDAI and BASFI for Patients with Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: To establish cutoffs for the minimum clinically important improvement (MCII) and the patient-acceptable symptom state (PASS) for the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and the Bath Ankylosing Spondylitis Functional Index (BASFI) in patients with ankylosing spondylitis (AS). METHODS: Patients with AS who started nonsteroidal antiinflammatory drugs were included. After 4 weeks, the PASS and the MCII were defined using external anchor questions (for the PASS, patients considering their condition of AS over the prior 48 h as "acceptable" forever; and for the MCII, those reporting moderate or slightly important improvement). Consistency of the MCII and PASS were tested according to HLA-B27 status, presence/absence of SpA extraarticular manifestations, age, sex, disease duration, and baseline BASDAI/BASFI score. The 75th percentile of the cumulative distribution was used to determine the MCII and PASS. RESULTS: In total, 283 patients from a multinational cohort were included. Overall cutoffs for the PASS were 4.1 in the BASDAI and 3.8 in the BASFI. Cutoffs for the MCII were 0.7 and 0.4 for the BASDAI and BASFI, respectively. Subgroup analyses revealed that disease duration and baseline BASDAI/BASFI were significantly associated with the PASS and MCII. In a subanalysis limited to patients with active disease (baseline BASDAI ≥ 4), the MCII was 1.1 for the BASDAI and 0.6 for the BASFI. CONCLUSION: The conceptual viability of the PASS for the BASDAI is questionable because levels approach those required for the start of biological therapy. Because the MCII is less variable than the PASS, we propose its exclusive use, with cutoffs of 1.1/0.6 for the BASDAI/BASFI in patients with active disease. Because these values are based on a subset of the study population, we recommend confirmation in larger studies focused on patients with baseline BASDAI ≥ 4.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".