MP130AURION STUDY: MULTI-TARGET THERAPY WITH VOCLOSPORIN, MMF AND STEROIDS FOR LUPUS NEPHRITIS
Bibliographic record
Abstract
Introduction and Aims: In lupus nephritis (LN), complete (CR) or partial remission (PR) is associated with better patient and renal survival. Studies demonstrate that subjects who did not achieve an early reduction in proteinuria of ≥25% were unlikely to achieve even PR. Recent studies suggest that a combination of calcineurin inhibitors (CNis), MMF and steroids may be effective in LN patients. Voclosporin is a next generation CNi with a predictable pharmacokinetic-pharmacodynamic profile. The ongoing AURA-LV (AURA) study is a global double-blind, prospective study comparing 2 doses of VCS with placebo for the treatment of LN. This study, AURION, is the first reported pilot study of VCS in active LN assessing the ability of biomarkers at 8 weeks to predict clinical response over 24 and 48 weeks in subjects taking voclosporin in combination with MMF and steroids. We report preliminary data. Methods: Eligibility criteria includes: biopsy-proven LN; SLE by ACR criteria; UPCR of >1.0 mg/mg (Class III and IV) or >1.5 mg/mg (Class V); and CKD-EPI eGFR >45 ml/min/1.72m2.. VCS 23.7 mg po BID is administered in combination with MMF 1-2g and a reducing course of corticosteroids. UPCR assessments are made at each visit, together with biomarker (C3, C4 and anti-ds DNA) data at regular intervals. Proteinuria reduction over time is presented for the first 7 subjects enrolled in this pilot study, together with C3, C4 and anti-dsDNA plots.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".