Two-year Results of an Open Pilot Study of a 2-treatment Course with Rituximab in Patients with Early Systemic Sclerosis with Diffuse Skin Involvement
Bibliographic record
Abstract
OBJECTIVE: To study safety and potential efficacy of a 2-treatment course (month 0/6) with rituximab (RTX) in early diffuse systemic sclerosis (dcSSc). METHODS: Two years' followup (open-label study) was done of 8 patients with early dcSSc. Patients received an infusion of 1000 mg RTX 2 times at months 0 and 6, with 100 mg methylprednisolone. Clinical measurements, Disease Activity Score, functional status, and CD19+ peripheral blood count were performed at months 0, 3, 6, 12, 15, 18, and 24 and histopathological evaluation of the skin at months 0, 3, 12, and 24. RESULTS: There was a clinically significant change in skin score, with a mean Modified Rodnan skin score of 24.8 at baseline (SD 3.4) and 13.6 at Month 24 [SD 5.6; mixed models analyses (MMA) p < 0.0001] and a significant decrease in Disease Activity Score (DAS), with a median of 4.5 at baseline (range 1.5-7.5) and 0.5 at Month 24 (range 0.0-5.5; MMA p < 0.0001). Indices of internal organ involvement remained stable throughout the study. RTX induced effective B cell depletion at baseline and Month 6 (< 5 CD19+ cells/μl blood). The blindly assessed hyalinized collagen score changed significantly over time (MMA p = 0.009), with a mean of 69.3 at baseline (SD 22.8) and 33.1 at 24 months (SD 27.0). Five serious adverse events were considered unrelated to the RTX treatment. CONCLUSION: A 2-treatment course (months 0/6) with RTX appears to be well tolerated and may have potential efficacy for skin disease and stabilization of internal organ status in early dcSSc. Clinical Trials Registration NCT00379431.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".