Hassan Raza: A Smarter Risk Prediction in MPNs Using AI
Hassan Raza, Consultant Hematologist and Transfusion Medicine Specialist, shared on LinkedIn about a recent article by Xuezi Hu et al, published in Blood, adding:
”AI Enhancing Risk Prediction in MPNs
A recent American Society of Hematology (Blood 2025) study introduces MEAM – an AI model analyzing bone marrow morphology in ET and PV.
What it does:
Predicts multiple outcomes:
• Thrombosis/bleeding
• Myelofibrosis progression
• AML transformation
• Overall survival
Why it stands out:
Matches or exceeds traditional models (IPSET, R-IPSET-T)
Improves prediction when combined with clinical scores
Detects high-risk patients missed by conventional tools, especially younger patients
Clinical relevance:
Moves morphology from subjective assessment to a quantifiable, dynamic prognostic tool
Takeaway:
AI-integrated morphology may significantly refine risk stratification and treatment decisions in MPNs.”
Title: Multi-endpoint AI morphology model (MEAM) enhances risk prediction for vascular events and disease progression in MPNs
Authors: Xuezi Hu, Alan Aberdeen, Sharon Ruane, Rosalin Cooper, Timothy Ebsworth, Sanam Loghavi, David Ross, Diana Iarossi, Markus Tiemann, Amin Turki, Andrew Sung, Mingyi Chen, Zijun Xu-Monette, Ken Young, Anna Godfrey, Jyoti Nangalia, Joanna Baxter, Anthony Green, Mary Frances McMullin, Adam Mead, Claire Harrison, Jens Rittscher, Korsuk Sirinukunwattana, Daniel Royston
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