ORIGIN 3: A Phase 3 Trial of Atacicept in IgAN
Bibliographic record
Abstract
Background: IgA nephropathy (IgAN) is a B-cell mediated immune complex glomerulonephritis. Atacicept is a native human TACI-Fc fusion protein that binds and inhibits B-cell Activating Factor (BAFF) and A PRoliferation-Inducing Ligand (APRIL), key immunoregulatory cytokines central to the pathophysiology of IgAN, thereby modulating B-cell activity. Methods: In this ongoing double-blind, placebo-controlled, multinational Phase 3 trial, patients with biopsy-proven IgAN were randomized 1:1 to 150 mg of atacicept, self-administered subcutaneously once weekly at home, or placebo. The primary endpoint was percentage change from baseline (BL) at Week 36 in the urinary protein-to-creatinine ratio (UPCR) from a 24-hour collection. Secondary endpoints of galactose-deficient IgA1 (Gd-IgA1) percentage change from BL, hematuria resolution, and safety were also evaluated. Results: The interim analysis included 203 patients (atacicept n=106; placebo n=97). At Week 36, atacicept treatment resulted in a 45.7% UPCR reduction from BL vs. a 6.8% reduction with placebo, with a statistically significant 41.8% (95% CI, 28.9%–52.3%; P<0.0001) treatment difference (Figure). Significant improvements were also observed in Gd-IgA1 and hematuria with atacicept (Figure). The incidence of adverse events was similar between both groups, and most were mild or moderate. Conclusion: Atacicept treatment resulted in a statistically significant proteinuria reduction compared with placebo at Week 36, as well as Gd-IgA1 reduction, hematuria improvement, and a favorable safety profile. The results demonstrate the potential for atacicept to address the underlying pathophysiology of IgAN and provide a targeted, disease-modifying therapy. Funding: Commercial Support - Vera Therapeutics, Inc.
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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 | 0.002 |
| 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".