2025 update on MRD in acute myeloid leukemia: a consensus document from the ELN-DAVID MRD Working Party
Bibliographic record
Abstract
ABSTRACT: Measurable residual disease (MRD) monitoring has become a critical component in the management of acute myeloid leukemia (AML), to inform prognosis, guide therapy, and serve as a key end point in clinical trials. The 2025 update of the MRD guideline provides a comprehensive and refined framework for MRD assessment, aligned with the European LeukemiaNet (ELN) 2022 genetic risk classification. Developed by members of the ELN AML MRD Working Party, the guidelines incorporate expert consensus determined through a 2-stage Delphi round. They address the clinical implementation of MRD methodologies, technical considerations, integration into clinical trials, and future directions. Importantly, MRD recommendations are tailored to individual prognostic and genetic subgroups. A new qualitative MRD response category, designated as optimal, warning, or high risk of treatment failure, has been introduced to facilitate contextual interpretation of the MRD burden and its clinical relevance. Notably, ultrahigh-sensitivity next-generation sequencing-based MRD assessment is now recommended for FLT3 internal tandem duplication-mutated AML after intensive chemotherapy and before allogeneic hematopoietic cell transplantation. A total of 56 recommendations were formulated, with 53 achieving a high level of consensus (≥90%). These updated guidelines represent a major step forward toward harmonizing MRD assessments in AML and enhancing its clinical utility across diverse treatment settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.059 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".