Monitoring Minimal Residual Disease in Acute Myeloid Leukemia: Ready for Prime Time?

Predicting the outcome of therapy in patients with acute myeloid leukemia (AML) is currently necessary for making treatment decisions. Pretreatment covariates, such as clinical and molecular predictors, have helped identify which patients are more or less likely to survive their disease using the currently available regimens. Progress in establishing optimized flow cytometry and quantitative polymerase chain reaction assays for detecting minimal residual leukemia has provided new potential tools for predicting outcome. However, the most important next step in using these techniques toward personalized treatment of AML would be developing effective and safe strategies for eradicating the residual leukemic cells that are likely chemoresistant. With further refinement and standardization of the assays, and the development of novel, effective, and molecularly targeted agents, monitoring of minimal residual disease is likely to be incorporated into AML guidelines.

Target Audience

This activity has been designed to meet the educational needs of physicians and nurses involved in the management of patients with cancer.

Learning Objectives

Upon completion of this activity, participants will be able to:

  • Describe the benefits and limitations of MRD monitoring in AML
  • Outline how pretreatment covariates, such as clinical and molecular predictors, can determine prognosis/survival
Additional information
Supporters: 

No commercial support was received for this article.

Course summary
Available credit: 
  • 1.00 Participation
  • 1.00 Nurse
  • 1.00 Physician
Course opens: 
08/01/2012
Course expires: 
08/01/2013
Cost:
$0.00

Farhad Ravandi, MD
The University of Texas MD Anderson Cancer Center

Jeffrey L. Jorgensen, MD, PhD
The University of Texas MD Anderson Cancer Center

Available Credit

  • 1.00 Participation
  • 1.00 Nurse
  • 1.00 Physician

Accreditation Period

Course opens: 
08/01/2012
Course expires: 
08/01/2013

Price

Cost:
$0.00
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