Immunosuppressive treatment in diffuse cutaneous systemic sclerosis is associated with an improved composite response index (CRISS)
Bibliographic record
Abstract
BACKGROUND: Outcomes of therapeutic studies in diffuse cutaneous systemic sclerosis (dcSSc) have mainly been measured for specific organs, particularly the skin and lungs. A new composite response index in dcSSc (CRISS) has been developed for clinical trials. The goal of this study was to determine whether, in an observational dcSSc cohort, immunosuppression was associated with global disease improvement measured with the CRISS. METHODS: We conducted a retrospective cohort study in a multi-centered SSc registry comparing 47 patients newly exposed to immunosuppression for ≥ 1 year to 254 unexposed patients. Inverse probability of treatment weighting (IPTW) was performed to create comparable exposed and unexposed groups by balancing for age, sex, disease duration, modified Rodnan skin score (mRSS), forced vital capacity, patient and physician global assessments, and Health Assessment Questionnaire score. A CRISS score ≥ 0.6 at 1 year was defined as improvement. RESULTS: Exposed patients had shorter disease duration (5.5 versus 11.7 years, p < 0.01), more interstitial lung disease (67.4% versus 40.3%, p < 0.01), and worse physician global severity scores (4.2 versus 2.5 points, p < 0.01) compared to unexposed patients. Improvement in CRISS scores was more common in exposed patients after IPTW (odds ratio 1.85, 95% confidence interval 1.11, 3.09). Of the individual CRISS variables, only mean patient global assessment scores were significantly better among exposed than unexposed patients (- 0.4 versus 0 points, p = 0.03) while other variables including mRSS were similar. CONCLUSION: Using a composite response measure, immunosuppression was associated with better outcomes at 1 year in a dcSSc cohort. These results provide real-world data that align with clinical trials to support our current use of immunosuppression.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".