Thresholds of patient‐reported outcomes that define the patient acceptable symptom state in ankylosing spondylitis vary over time and by treatment and patient characteristics
Bibliographic record
Abstract
OBJECTIVE: The patient acceptable symptom state (PASS) is a single-question outcome tool to assess the level of symptoms at which patients with rheumatic diseases consider themselves well. We evaluated whether ankylosing spondylitis (AS) patient characteristics were associated with attaining the PASS and whether these characteristics influenced PASS thresholds for patient-reported outcome (PRO) tools. METHODS: The Adalimumab Trial Evaluating Long-term Efficacy and Safety for Ankylosing Spondylitis was a randomized, placebo-controlled study that evaluated the efficacy and safety of adalimumab in treating AS. The PASS and PROs were assessed over 24 weeks. PASS thresholds for PROs were set as either the 25th or 75th percentiles of the PRO response score. Logistic regression analyses were conducted to determine the associations of particular patient characteristics with the PASS and other response outcomes at 12 weeks (ASessment in Ankylosing Spondylitis International Working Group criteria for 20% improvement [ASAS20], ASAS40, ASAS5/6, ASAS partial remission, and Bath Ankylosing Spondylitis Disease Activity Index 50% improvement). RESULTS: Age >40 years, disease duration >10 years, female sex, placebo treatment, and English-speaking site were consistently associated with greater PASS thresholds for PROs. Age, male sex, disease duration, and treatment were each independently associated with attainment of the PASS at 12 weeks. Only age and treatment were independently associated with other response outcomes. PASS thresholds also decreased over 24 weeks. CONCLUSION: PASS thresholds for PROs changed over time. These thresholds, as well as the attainment of the PASS, were affected by covariates unrelated to treatment. If confirmed in other studies, these results cast doubt on using the PASS to assess absolute health status in clinical research.
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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 | 0.032 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".