Myeloid Neoplasms With Oligomonocytosis Exhibit Heterogenous Pathologic and Genetic Features

Area of Science:

• Hematology
• Oncology
• Genetics

Background:

• Classification criteria for myeloid neoplasms, including chronic myelomonocytic leukemia (CMML), have been updated in the fifth edition of the World Health Organization classification (WHO5) and the International Consensus Classification (ICC).
• Both WHO5 and ICC lowered the absolute monocyte count threshold to 0.5 × 10⁹/L for CMML diagnosis.
• The ICC introduced new morphologic criteria for CMML, distinct from WHO5.

Purpose of the Study:

• To evaluate the impact of WHO5 and ICC classification changes on a cohort of myeloid neoplasms previously classified under WHO4r.
• To assess how the revised monocyte count and new morphologic criteria affect the reclassification of myelodysplastic syndrome (MDS) to myelodysplastic-type CMML (MD-CMML).

Main Methods:

• Analysis of a large cohort of myeloid neoplasms (WBC < 13 × 10⁹/L, blasts <20%) initially classified using WHO4r.
• Comparison of case numbers and reclassification rates under WHO5 and ICC criteria, focusing on MD-CMML.
• Evaluation of genetic signatures and their correlation with outcomes in relation to classification criteria.

Main Results:

• The lower monocyte threshold potentially reclassifies ~20% of WHO4r-defined MDS to MD-CMML.
• WHO5 criteria led to an 84% increase in MD-CMML cases compared to WHO4r.
• ICC criteria, due to morphologic changes, reduced MD-CMML cases significantly (107 by WHO5 to 40 by ICC) and left 55% of WHO4r-defined MD-CMML unclassifiable.
• ICC-defined CMML showed enrichment for CMML-like genetic signatures.
• Genetic classification and risk models proved superior to monocyte counts or morphology in predicting patient outcomes.

Conclusions:

• Revised classification criteria for myeloid neoplasms, particularly CMML, have a substantial impact on diagnostic rates.
• ICC criteria, while reducing MD-CMML diagnoses, align better with genetic profiles.
• Genomic information offers a more robust approach to risk stratification and outcome prediction in CMML than traditional morphologic or monocyte count criteria.