Patient acceptable symptom state in scleroderma: results from the tocilizumab compared with placebo trial in active diffuse cutaneous systemic sclerosis
Bibliographic record
Abstract
Objectives: Patient acceptable symptom state (PASS) as an absolute state of well-being has shown promise as an outcome measure in many rheumatologic conditions. We aimed to assess whether PASS may be effective in active diffuse cutaneous SSc differentiating active from placebo. Methods: Data from the phase 2 Safety and Efficacy of Subcutaneous Tocilizumab in Adults with Systemic Sclerosis (faSScinate) trial were used, which compared tocilizumab (TCZ) vs placebo over 48 weeks followed by an open-label TCZ period to 96 weeks. Three different types of PASS questions were evaluated at weeks 8, 24, 48 and 96, including if a current state would be acceptable over time as a yes vs no response and Likert scales about how acceptable a current state is if remaining over time. Additional outcomes assessed included modified Rodnan skin score, HAQ disability index (HAQ-DI), physician and patient global assessments on a visual analogue scale, CRP and ESR. Results: The placebo group consisted of 44 patients and the TCZ group had 43 patients. At baseline, 33% achieved a PASS for all three PASS questions, with the proportion increasing to 69, 71 and 78%, respectively, at 96 weeks. Changes in PASS scores showed a moderately negative correlation with HAQ-DI and patient and physician global assessments visual analogue scales, which indicates expected improvements as PASS improved. The PASS question, 'Considering all of the ways your scleroderma has affected you, how acceptable would you rate your level of symptoms?' showed significant correlations with patient-reported outcomes and differentiating placebo vs TCZ at 48 weeks (P = 0.023). Conclusion: PASS may be used as a patient-centred outcome in SSc, especially as a 7-point Likert scale. Further validation is required to determine the utility as an outcome measure in trials and clinical practice.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".