A fault tree analysis of early treatment failure in Acute myeloid leukemia
Specific mutation patterns now identify AML patients at highest risk of treatment failure, enabling earlier intervention decisions.
Applied to the BeatAML2 cohort (n=805), fault tree analysis identified actionable extreme-risk factor combinations that predicted early AML treatment failure independently of existing risk classifications. RUNX1/TP53 mutations with low platelets predicted induction failure, while advanced age with low albumin or impaired renal function predicted 60-day mortality, with the combined extreme-risk constellation (32.6% of patients) showing HR 2.03 for overall survival.
What the study was
- Study design
- Retrospective cohort analysis with fault tree analysis
- Population
- AML patients in BeatAML2 cohort
- Sample size
- 805
- Category
- Diagnostics
- Maturity
- Exploratory
- Journal
- Current Research in Translational Medicine
Why it surfaced
Novel application of fault tree analysis to AML risk stratification in a large cohort (n=805). Identifies clinically actionable extreme-risk constellations beyond existing classification systems. Curr Res Transl Med.
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