Megakaryocytic Clustering in Chronic Myeloid Leukemia: Can it be a Predictor of Clinical Outcome?

Zunairah Mughal1, Hira Babar2, Sobia Ashraf1

  • 1Department of Pathology, King Edward Medical University, Lahore, Pakistan.

Insights

Megakaryocytic clustering in chronic myeloid leukemia (CML) patients is linked to poorer clinical outcomes. This finding highlights the importance of monitoring this specific bone marrow characteristic for better CML patient management.

Area of Science:

  • Hematology
  • Oncology
  • Pathology

Background:

  • Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm.
  • Megakaryocytic clustering in bone marrow is a pathological finding.
  • The clinical significance of megakaryocytic clustering in CML requires further elucidation.

Purpose of the Study:

  • To compare the clinical outcomes of chronic myeloid leukemia (CML) patients with and without megakaryocytic clustering.
  • To assess the association between megakaryocytic clustering and treatment response markers in CML.

Main Methods:

  • A cross-sectional comparative study was conducted involving 94 patients with chronic phase CML.
  • Bone marrow trephine biopsies were analyzed for megakaryocytic clustering.
  • Clinical outcomes, including complete hematological response (CHR) and major molecular response (MMR) at 6 months and 1 year, were evaluated alongside Sokal scores.

Main Results:

  • Megakaryocytic clustering was observed in 60.6% of patients.
  • Patients with megakaryocytic clustering showed significantly higher rates of absent CHR, absent MMR at 6 months, and absent MMR at 1 year compared to those without clustering.
  • A statistically significant correlation was found between megakaryocytic clustering and high Sokal scores (p<0.001).

Conclusions:

  • Megakaryocytic clustering in CML is associated with poor clinical outcomes.
  • The presence of megakaryocytic clustering predicts lower rates of complete hematological response and major molecular response.
  • Sokal score, CHR, and MMR are important indicators influenced by megakaryocytic clustering in CML management.
Abstract