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INGRAIN-MF
Incorporating genetics, risk and associated burden into MF management

MODULE 3: A personalised approach to predicting prognosis in myelofibrosis

Introduction

Myelofibrosis (MF) is a rare form of blood cancer, heterogeneous in both presentation and evolution.1 Survival times from diagnosis for patients with MF can vary significantly.1 Stratifying patients according to their risk allows a more accurate estimation of prognosis, and can inform on disease management and treatment decisions.1-3

In this module, you will learn about:

  • clinical and demographic risk factors, and their influence on survival
  • cytogenetic and genetic risk factors, and their influence on survival
  • different prognostic scoring systems and how they compare
  • the use and implications of risk stratification

Multiple-choice questions (MCQs) to test your current knowledge

These MCQs will help you assess your current knowledge of this topic before you begin to work through the module. Your answers will be marked but will not count towards your final score. You will be asked the same MCQs at the end of the module. You will be able to download a learning certificate for your records upon completion.

CONTINUE TO SECTION 1: DEMOGRAPHIC AND CLINICAL RISK FACTORS IN MF 
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Adverse events should be reported. Reporting forms and information can be found at www.mhra.gov.uk/yellowcard.
Adverse events should also be reported to Novartis online through the pharmacovigilance intake (PVI) tool at www.novartis.com/report or alternatively email medinfo.uk@novartis.com or call 01276 698370

References
  1. Cervantes F, Dupriez B et al. New prognostic scoring system for primary myelofibrosis based on a study of the International Working Group for Myelofibrosis Research and Treatment. Blood 2009;113(13):2895-2901
  2. Guglielmelli P, Lasho T L et al. MIPSS70: Mutation-enhanced International Prognostic Score System for transplantation-age patients with primary myelofibrosis. J Clin Oncol 2018;36(4):310-318
  3. How J, Hobbs G S. A practical guide for using myelofibrosis prognostic models in the clinic. J Natl Compr Canc Netw 2020;18(9):1271-1278