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Updated: Jun 6, 2026

Identifying Bone Marrow Microenvironmental Populations in Myelodysplastic Syndrome and Acute Myeloid Leukemia
Published on: November 10, 2023
Hematogones: a new prognostic factor for acute myeloblastic leukemia
Sylvain P Chantepie1, Véronique Salaün, Jean-Jacques Parienti
1Service d'Hématologie Clinique, Centre Hospitalier Universitaire, Côte de Nacre, Caen Cedex, France. chantepie-s@chu-caen.fr
Detecting hematogones (HGs) in acute myeloid leukemia (AML) patients can predict better survival outcomes. Higher HG levels are linked to improved leukemia-free survival and overall survival, aiding in relapse risk assessment.
Area of Science:
- Hematology
- Oncology
- Immunology
Background:
- Acute myeloid leukemia (AML) patient outcomes are highly variable.
- Novel prognostic markers are crucial for predicting AML relapse.
- Hematogones (HGs), normal B-lymphocyte precursors, can increase in hematologic malignancies.
Purpose of the Study:
- To investigate the prognostic significance of hematogones in AML patients.
- To assess the impact of HG presence on leukemia-free survival (LFS) and overall survival (OS).
- To determine if HG levels can serve as a predictive tool for AML relapse risk.
Main Methods:
- Flow cytometry was used to analyze HG levels in 120 AML patients in first complete remission.
- Patients were stratified based on HG detection thresholds.
- Cox regression analysis was employed to identify independent predictors of survival.
Main Results:
- Patients with HG levels > 0.01% demonstrated significantly better median LFS (29.2 vs 11.7 months, P = .001).
- Overall survival was also significantly improved in patients with HG levels > 0.01% (not reached vs 23.5 months, P = .011).
- HG level > 0.01% independently predicted better LFS (HR=0.5, P < .03) after adjusting for clinical and molecular factors.
Conclusions:
- Hematogone analysis is a potential prognostic tool for AML.
- Detectable HG levels correlate with improved LFS and OS in AML patients.
- HG assessment may assist in refining risk stratification and predicting relapse in AML.
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