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December 8, 2025BloodOpen Access

Identification of red cell distribution width as a key predictor of leukemic transformation in polycythemia vera and essential thrombocythemia: A machine learning approach involving 10,560 cases

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Authors

KRKaaren K. ReichardATAyalew Tefferi

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Overview

Machine learning identifies increased leukemic transformation risk in polycythemia vera patients, suggesting RDW may serve as a critical prognostic marker.

Key Points

  • Increased leukemic transformation risk correlates with elevated RDW levels in both polycythemia vera and essential thrombocythemia.
  • Median follow-up for the discovery cohorts was 6.1 years, with 4.1% of polycythemia vera patients developing acute myeloid leukemia.
  • Validation cohorts confirmed that high RDW and age above 60 years are significant independent risk factors for leukemic transformation.
  • Red cell distribution width emerges as a vital prognostic marker, emphasizing the need for risk stratification in clinical practice.

Cite This Study

Reichard et al. (2025) studied this question.

synapsesocial.com/papers/69362f3a4fa91c937236d463https://doi.org/10.1182/blood-2025-2021
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