225.3: Randomized phase 2 trial of felzartamab in humoral transplant rejection.
Bibliographic record
Abstract
Felzartamab Study Group. Background: Antibody-mediated rejection (ABMR) is a leading cause of renal allograft failure. Targeting CD38 to inhibit alloantibody- and natural killer (NK) cell−driven injury may be a therapeutic option. Methods: In a double-blind, placebo-controlled phase 2 trial, patients with ABMR ≥180 days post-transplant were randomized 1:1 to receive nine infusions of the CD38 monoclonal antibody felzartamab (16 mg/kg) or placebo over 6 months, followed by a 6-month observational period. The primary outcome was felzartamab safety and tolerability. Secondary outcomes included 24- and 52-week renal biopsies, donor-specific antibody (DSA) levels, peripheral NK cell counts, and donor-derived cell-free DNA (dd-cfDNA). Results: Of 22 patients randomized (felzartamab, n=11; placebo, n=11), eight had mild to moderate infusion reactions (felzartamab, n=8; placebo, n=0) and five had serious adverse events (felzartamab, n=1; placebo, n=4). One patient who received placebo had graft loss. After week 24, resolution of morphologic ABMR activity was more frequent with felzartamab (9 of 11 [81.8%]) versus placebo (2 of 10 [20%]; P=0.009). Felzartamab decreased median (interquartile range) microvascular inflammation scores (0 [0−1] versus 2.5 [2−3]; P=0.001), molecular ABMR activity (ABMRProb: 0.17 [0.09−0.51] versus 0.77 [0.37−0.86]; P=0.007), CD16bright NK cell counts (16 [8−41] versus 54 [38-170] cells/ml; P=0.004), and dd-cfDNA (0.31 [0.21−0.49] versus 0.82 [0.34−2.90)%]; P=0.036). DSA changed minimally. At week 52, ABMR activity recurrence was observed in 3 of 9 felzartamab responders, with molecular activity and biomarker levels increasing towards baseline. Conclusion: Felzartamab exhibited favorable safety and efficacy, underscoring its potential as a novel therapeutic option in ABMR.
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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 | 0.001 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".