A real-world analysis of clinical outcomes in AML with myelodysplasia-related changes: a comparison of ICC and WHO-HAEM5 criteria
Bibliographic record
Abstract
ABSTRACT: The proposed fifth edition of the World Health Organization classification of hematolymphoid tumors (WHO-HAEM5) and International Consensus Classification (ICC) provide different definitions of acute myeloid leukemia with myelodysplasia-related genetics (AML-MR). We conducted a retrospective study which included a cohort of 432 patients, with 354 patients fulfilling WHO-HAEM5 criteria for WHO-AML-MR or 276 patients fulfilling ICC criteria for ICC-AML-MR by gene mutation or cytogenetics (ICC-AML-MR-M/CG). The clinicopathological features were largely similar, irrespective of the classification used, except for higher rates of complex karyotype, monosomy 17, TP53 mutations, and fewer RUNX1 mutations in the WHO-AML-MR group. TP53 mutations were associated with distinct clinicopathological features and dismal outcomes (hazard ratio [HR], 2.98; P < .001). ICC-AML-MR-M/CG group had superior outcome compared with the WHO-AML-MR group (HR, 0.80, P = .032), largely in part due to defining TP53 mutated AML as a standalone entity. In the intensively-treated group, WHO-AML-MR had significantly worse outcomes than AML by differentiation (HR, 1.97; P = .024). Based on ICC criteria, ICC-AML-MR-M/CG had more inferior outcomes compared to AML not otherwise specified (HR, 2.11; P = .048 and HR, 2.55; P = .028; respectively). Furthermore, changing the order of genetic abnormalities defining AML-MR (ie, by gene mutations or cytogenetics) did not significantly affect clinical outcomes. ICC-AML-MR-M/CG showed similar outcomes regardless of the order of assignment. We propose to harmonize the 2 classifications by excluding TP53 mutations from WHO-HAEM5 defined AML-MR group and combining AML-MR defined by gene mutations and cytogenetics to form a unified group.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".