Zanubrutinib (zanu) in Anti-Phospholipase A2 Receptor (PLA2R)-Associated Primary Membranous Nephropathy (PMN): Preliminary Results of a Phase 2/3, Multicenter, Randomized, Open-Label Study
Bibliographic record
Abstract
Background: BTK plays a role in B-cell modulation and is a potential target in PMN. Zanu (BTK inhibitor) is being evaluated in a 2-part study in PMN (NCT05707377). Part 1 data are shown. Methods: After a 12-wk run-in, pts with PLA2R antibody >50 RU/mL and urinary protein-creatinine ratio (UPCR) >3.5 g/g received zanu 160 mg twice daily for 64 wks, followed by 40-wk observation. The efficacy endpoints include change from baseline in anti-PLA2R antibody titer, UPCR, clinical remission rate and safety. Results: As of March 7, 2025, 30 pts were treated; median age: 46.5 (range 32-74) yrs, 66.7% male, 90.0% were from Asia. At baseline, mean UPCR was 7.8 mg/mg (SD 3.0), median serum anti-PLA2R antibody was 161.0 RU/mL (range 51.4-1219.8), mean serum albumin was 25.4 g/L (SD 7.2), median eGFR was 85.2 mL/min/1.73m2 (range 39.8-123.0). Median exposure: 57 wks. At 52 wks, mean UPCR change from baseline: -4.9 mg/mg (SD 2.5), a 70.4% reduction overall (Fig 1). 5 pts had complete remission (UPCR ≤0.3 mg/mg and stable eGFR) and 8 pts had partial remission (UPCR of >0.3 to ≤3.5 mg/mg, with ≥50% decrease from baseline, and stable eGFR), resulting in a total remission rate of 43.3%. Fig 2: change in PLA2R antibody. Immunological response rate (anti-PLA2R titer reduction to <14 RU/mL) was 56.7%. 27 pts (90.0%) had treatment-emergent adverse events (TEAEs); most common: upper respiratory tract infection (30.0%), rash, anemia (both 23.3%). Four pts (13.3%) had severe TEAEs (two treatment-related). Conclusion: Zanu is generally well tolerated with promising efficacy in pts with primary PMN; continued evaluation in pts with PMN is supported. Funding: Commercial Support - BeOne Medicines Ltd
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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 | 0.003 | 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 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".