Randomized, double-blind, placebo-controlled phase 2a study assessing the efficacy and safety of felzartamab for IgA nephropathy
Bibliographic record
Abstract
INTRODUCTION: Felzartamab is a fully human anti-CD38 monoclonal antibody under investigation for treatment of IgA nephropathy (IgAN). IGNAZ (NCT05065970) is a randomized, double blind, placebo-controlled Phase 2a study that assessed the efficacy and safety of felzartamab in 54 patients with biopsy-confirmed IgAN despite maximal renin angiotensin system blockade. METHODS: In part 1, patients were randomized in the 6-month treatment period to receive intravenous placebo (12 patients) or felzartamab in three arms: two doses in 15 days (2-dose, 12 patients), five doses in 2 months (5-dose, 11 patients), or nine doses in five months (9-dose, 13 patients). In part 2, six Japanese patients received the felzartamab 9-dose schedule open-label. Follow-up in parts 1 and 2 was 24 and 12 months, respectively, after the first dose. The primary endpoint was change in proteinuria (urine protein to creatinine ratio [UPCR]) at nine months. RESULTS: Treatment with felzartamab versus placebo led to rapid (within 3-6 months) reduction in least-squares mean UPCR sustained at nine months (placebo, -5.7%; 2-dose, -12.5%; 5-dose, -12.8%; 9-dose, -29.5%; part 2, -44.8%) and at 18 months after ending treatment (24 months), particularly in the 9-dose arm (-44.5%). Mean decreases in estimated glomerular filtration rate were lower with felzartamab than with placebo through 24 months in part 1 and 12 months in part 2. Felzartamab safety was consistent with prior observations; adverse events were predominantly grade 1 or 2. CONCLUSIONS: Treatment with felzartamab results in sustained reduction of proteinuria, suggesting disease improvement. Further evidence is needed to understand the impact of felzartamab on preservation of kidney function in high-risk patients with IgAN. TRIAL REGISTRATION: Registered at ClinicalTrials.gov with study number NCT05065970.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".