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Related Experiment Video

Updated: Jan 6, 2026

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Beyond Hemoglobin: When and How to Work Up Possible Polycythemia Vera.

Gene Shaw1, Richard Berg2

  • 1Department of Lab-Pathology, Marshfield Clinic, Marshfield, Wisconsin shaw.gene@marshfieldclinic.org.

Clinical Medicine & Research
|October 5, 2019
PubMed
Summary

This study identifies key clinical and lab markers to help diagnose polycythemia vera (PV) and differentiate it from secondary erythrocytosis. Accessible data can guide PV workups, suggesting a need for a formal risk scoring system.

Keywords:
ErythropoietinJAK2 mutationsMyeloproliferative neoplasmsPolycythemia veraSecondary erythrocytosis

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Area of Science:

  • Hematology
  • Oncology
  • Clinical Diagnostics

Background:

  • The 2017 World Health Organization (WHO) guidelines lowered hemoglobin cutoffs for polycythemia vera (PV) diagnosis but were not intended for initial screening.
  • Differentiating PV from secondary erythrocytosis (SE) is crucial for appropriate patient management.

Purpose of the Study:

  • To evaluate the utility of clinical and laboratory parameters in guiding the diagnostic workup for PV.
  • To explore the role of bone marrow morphology in distinguishing PV from SE.

Main Methods:

  • Evaluated 200 patients using JAK2 V617F testing and WHO criteria to compare PV and SE.
  • Assessed clinical features (age, obesity, smoking) and laboratory parameters (hemoglobin, platelets, RBC count, erythropoietin, MCV, ferritin).
  • Examined bone marrow morphology in a subset of patients (111 cases).

Main Results:

  • Myeloproliferative neoplasms (MPN) were uncommon in patients under 40 or with obesity (BMI ≥ 30 kg/m²).
  • Current smoking history was more indicative of SE; these patients rarely had platelet counts ≥ 450 × 10³/µL.
  • Laboratory indicators for PV included high RBC counts (men > 6.8 × 10⁶/µL, women > 5.9 × 10⁶/µL), low erythropoietin, low MCV, or low ferritin.
  • Bone marrow in PV cases generally showed increased cellularity compared to SE, aiding disease progression assessment.

Conclusions:

  • Accessible clinical and laboratory data can effectively aid in determining the need for a PV diagnostic workup.
  • A preliminary diagnostic algorithm is proposed, highlighting the need for larger studies to develop a formal PV risk-scoring system.