MO230A PHASE 3, RANDOMIZED, DOUBLE-BLIND, PLACEBO CONTROLLED STUDY OF ATRASENTAN IN PATIENTS WITH IGA NEPHROPATHY (THE ALIGN STUDY)
Bibliographic record
Abstract
Abstract Background and Aims IgA nephropathy (IgAN) is the most common primary glomerulonephritis globally and an important cause of chronic kidney disease (CKD). Up to 40% of IgAN patients are at risk of progressing to end-stage kidney disease (ESKD) and proteinuria is the strongest predictor of progression. There are no approved therapies for IgAN, leaving an important need for new strategies to lower proteinuria and preserve kidney function in high-risk patients. Endothelin A (ETA) receptor activation drives proteinuria, along with kidney inflammation and fibrosis. Atrasentan, a potent and selective ETA antagonist, has been studied extensively in >5,000 patients with type 2 diabetes and kidney disease (DKD), demonstrating clinically significant and sustained reductions in proteinuria when administered on top of a maximum tolerated dose of RAS inhibitor (RASi). In a global Phase 3 outcome study in DKD (SONAR), atrasentan demonstrated a 35% reduced risk of the primary composite outcome of doubling of serum creatinine or end stage kidney disease (95% CI: 0.49, 0.88; P = 0.005). The most common adverse event was fluid retention. Selective ETA blockade represents a promising approach to reduce proteinuria and preserve kidney function in high risk IgAN patients. This is a presentation of a global, phase 3, double-blind, placebo-controlled trial to determine the effect of atrasentan in IgAN patients at high risk of kidney function loss. Method Approximately 320 patients across North America, South America, Europe, and Asia-Pacific with biopsy-proven IgAN will be randomized to receive 0.75 mg atrasentan or placebo daily for 132 weeks. Patients will continue receiving a maximally tolerated and stable dose of a RAS inhibitor as standard of care. The study will also include patients that are unable to tolerate RAS inhibitor therapy. Additional eligibility criteria include urine protein creatinine ratio (UPCR) ≥1 g/g and eGFR ≥30 mL/min/1.73 m2. Participants will have study assessments over two and a half years with options for remote study visits using telemedicine and home health visits. The primary objective is to evaluate the effect of atrasentan versus placebo on proteinuria at Week 24. Secondary objectives include evaluating the change from baseline in eGFR, safety, and tolerability, and quality of life. Results N/A Conclusion N/A
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.002 | 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".