Dr Eckfeldt on the Implications of Improved MRD Testing in AML

Craig Eckfeldt, MD, PhD, assistant professor, medicine, faculty, Microbiology, Immunology, and Cancer Biology PhD Graduate Program, Division of Hematology, Oncology, and Transplantation, the University of Minnesota Medical School, discusses how improved minimal residual disease (MRD) testing methods have impacted the acute myeloid leukemia (AML) treatment paradigm, improved treatment outcomes, clarified risk-stratification measures, and contributed to individualized patient care.

At an OncLive^® State of the Science Summit on hematologic malignancies, Eckfeldt and colleagues participated in a discussion about the evolution of the AML treatment paradigm, during which they reflected on emerging agents, the role of MRD testing, and unanswered questions that future research may address.

The advent of MRD detection is significantly impacting the management of hematologic malignancies, as well as other cancers, Eckfeldt begins. In the treatment of patients with acute lymphoblastic leukemia, MRD detection has become crucial for prognostication and guiding treatment goals, he says. Although the application of MRD testing in AML has lagged comparatively, modern technologies, such as improved multiparameter flow cytometry and advanced genetic tests like polymerase chain reaction–based assays, have made MRD an important end point when evaluating new AML treatment approaches, he explains.

MRD detection has proven valuable both before and after transplantation, aiding treatment decisions for patients who may have traditionally been considered to have favorable-risk disease, Eckfeldt elaborates. Although many patients achieve their therapeutic goals, some still relapse, he notes. The use of MRD testing to identify patients who are at higher risk of relapse and may benefit from more intensive treatments or novel therapies has revolutionized patient care, he emphasizes. The expanding repertoire of markers for MRD evaluation will further enhance the utility of MRD as a critical tool for assessing disease status and guiding clinical decisions. This will ultimately improve patient outcomes by enabling better risk stratification and personalization of treatment plans, Eckfeldt concludes.