Proposals for revised International Working Group–European LeukemiaNet criteria for anemia response in myelofibrosis
Bibliographic record
Abstract
ABSTRACT: With emerging new drugs in myelofibrosis (MF), a robust and harmonized framework for defining the severity of anemia and response to treatment will enhance clinical investigation and facilitate interstudy comparisons. Accordingly, the lead authors on the 2013 edition of the International Working Group-European LeukemiaNet (IWG-ELN) response criteria in MF were summoned to revise their document with the intent to (1) account for gender-specific differences in determining hemoglobin levels for eligibility criteria; (2) revise the definition of transfusion-dependent anemia (TDA) based on current restrictive transfusion practices; and (3) provide a structurally simple and easy to apply response criteria that are sensitive enough to detect efficacy signals (minor response) and also account for major responses. The initial draft of the 2024 IWG-ELN proposed criteria was subsequently circulated around a wider group of international experts and their feedback incorporated. The proposed articles include new definitions for TDA (≥3 units in the 12 weeks before study enrollment) and hemoglobin thresholds for eligibility criteria (<10 g/dL for women and <11 g/dL for men). The revised document also provides separate (TDA vs non-TDA) and graded (major vs minor response) response criteria while preserving the requirement for a 12-week period of screening and observation on treatment.
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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 | 0.107 | 0.186 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.012 | 0.020 |
| Insufficient payload (model declined to judge) | 0.007 | 0.009 |
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".