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Updated: Jun 15, 2025

Predictive Immune Modeling of Solid Tumors

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Published on: February 25, 2020

Prognostic and Predictive Models in Myelofibrosis.

Barbara Mora¹, Cristina Bucelli¹, Daniele Cattaneo^1,2

¹Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza, 35 - 20122, Milan, Italy.

Current Hematologic Malignancy Reports

|August 23, 2024

Summary

Prognostic models improve survival predictions for myelofibrosis (MF) patients. Applying these models aids treatment planning and enhances personalized care for MF, improving overall survival (OS).

Keywords:

Allogenic-stem cells transplant JAK inhibitors Myelofibrosis Next generation sequencing Prognosis

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Database-guided Flow-cytometry for Evaluation of Bone Marrow Myeloid Cell Maturation

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Published on: November 3, 2018

Area of Science:

Hematology
Oncology
Medical Statistics

Background:

Myelofibrosis (MF) encompasses prefibrotic primary MF (pre-PMF), overt-PMF, and secondary MF (SMF).
Overall survival (OS) differs significantly across MF subtypes, with median OS of 14, 7, and 9 years for pre-PMF, overt-PMF, and SMF, respectively.
Mortality in MF is primarily driven by non-clonal progression and transformation into blast phase.

Purpose of the Study:

To review the impact of biological architecture on OS in MF.
To highlight the development and application of integrated scores and prognostic models for MF.
To emphasize the importance of OS as a clinical trial endpoint and in personalized MF treatment.

Main Methods:

Review of recent discoveries on biological architecture and its impact on OS in MF.
Evaluation of integrated scores and prognostic models for predicting survival in PMF and SMF.
Assessment of multivariable predictive algorithms for treatment decisions in MF.

Main Results:

Integrated scores now predict survival in primary MF (PMF).
The MYSEC-PM (MYelofibrosis SECondary-prognostic model) is recommended for OS estimates in SMF.
Multivariable predictive algorithms can support crucial treatment decisions for MF patients.
Accumulating data clarifies the prognostic role of the molecular landscape in SMF.

Conclusions:

Prognostic models are critical for OS prediction and treatment planning in MF.
Timely application of prognostic models is essential for a personalized approach to MF patient care.
OS should be considered a relevant endpoint in clinical trials for MF.