Brentuximab vedotin for skin involvement in refractory diffuse cutaneous systemic sclerosis, an open-label trial
Bibliographic record
Abstract
OBJECTIVE: We explored the efficacy and safety of brentuximab vedotin, a chimeric anti-CD30 antibody drug conjugate, in patients with severe active diffuse cutaneous systemic sclerosis (dcSSc). METHODS: This phase II proof-of-concept, single centre, open-label, single arm, investigator-initiated trial included patients ≥18 years, with dcSSc, modified Rodnan skin score (mRSS) ≥15 with <5 years since the first non-Raynaud's symptom and/or skin worsening despite immunosuppression who were treated with intravenous brentuximab vedotin 0.6 mg/kg q3 weeks for 45 weeks. The primary end point was a decrease in mRSS of ≥8 points at 48 weeks. RESULTS: Eleven patients were treated with brentuximab vedotin, with nine completing the study. The mean mRSS reduction at week 48 was 11.3 (95% CI 6.9, 15.8; P = 0.001), meeting the primary end point in the intention to treat analysis (7/11 had a decrease in mRSS ≥8). The % forced vital capacity increased by 7.8% (12.5). The Composite Response Index in dcSSc (CRISS) suggested a beneficial treatment effect (86% ≥0.6). Most adverse events were mild. No SAEs were attributed to brentuximab vedotin. CONCLUSION: In dcSSc, brentuximab vedotin improved skin and FVC without safety concerns. A placebo-controlled trial is warranted to corroborate these initial findings. TRIAL REGISTRATION: ClinicalTrials.gov, http://clinicaltrials.gov, NCT03198689.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".