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Real-World Electronic Medical Records Data Identify Risk Factors for Myelofibrosis and Can Be Used to Validate Established Prognostic Scores

Max Kappenstein, Nikolas von Bubnoff*

*Corresponding author for this work

Abstract

Myelofibrosis (MF) is a myeloproliferative neoplasia arising de novo as primary myelofibrosis (PMF) or secondary to polycythemia vera or essential thrombocythemia. Patients experience a high symptom burden and a marked reduction in life expectancy. Despite progress in molecular understanding and treatment, the clinical and prognostic heterogeneity of MF complicates treatment decisions. The International Prognostic Scoring System (IPSS) integrates clinical factors for risk stratification in MF. This study leverages the TriNetX database with more than 64,000 MF patients to assess the impact of accessible parameters on survival and complicating events, including AML transformation, cachexia, increased systemic inflammation, thrombosis and hemorrhage. Age over 65 years correlated with increased risks of death, AML transformation, thrombosis and hemorrhage. Anemia (Hb < 10 g/dL), leukocytosis (>25 × 103/µL) and thrombocytopenia (<150 × 103/µL) reduced survival and increased risks across all assessed events. Monocytosis is associated with decreased survival, whereas eosinophilia and basophilia were linked to improved survival. Further, as proof of concept for the applicability of TriNetX for clinical scores, we devised a simplified IPSS, and confirmed its value in predicting outcomes. This comprehensive study underscores the importance of age, anemia, leukocytosis and thrombocytopenia in predicting disease trajectory and contributes to refining prognostic models, addressing the challenges posed by the disease’s heterogeneity.

Original languageEnglish
Article number1416
JournalCancers
Volume16
Issue number7
ISSN2072-6694
DOIs
Publication statusPublished - 04.2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Areas and Centers

  • Research Area: Luebeck Integrated Oncology Network (LION)

DFG Research Classification Scheme

  • 2.22-14 Hematology, Oncology

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