Chronic Active Antibody-mediated Rejection: Opportunity to Determine the Role of Interleukin-6 Blockade
Bibliographic record
Abstract
Chronic active antibody-mediated rejection (caAMR) is arguably the most important cause of late kidney allograft failure. However, there are no US Food and Drug Administration (FDA)-approved treatments for acute or chronic AMR and there is no consensus on effective treatment. Many trials in transplantation have failed because of slow and/or inadequate enrollment, and no new agent has been approved by the FDA for transplantation in over a decade. Several lines of evidence suggest that interleukin-6 is an important driver of AMR, and clazakizumab, a humanized monoclonal antibody that neutralizes interleukin-6, has shown promising results in phase 2 studies. The IMAGINE trial (Interleukin-6 Blockade Modifying Antibody-mediated Graft Injury and Estimated Glomerular Filtration Rate Decline) (NCT03744910) is the first to be considered by the FDA using a reasonably likely surrogate endpoint (slope of estimated glomerular filtration rate decline >1 y) for accelerated approval and is the only ongoing clinical trial for the treatment of chronic rejection. This trial offers us the opportunity to advance the care for our patients in need, and this article is a call to action for all transplant providers caring for patients with caAMR.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".