Clinical applicability of proposed algorithm for identifying individuals at risk for hereditary hematologic malignancies

Maggie Clifford, Sarah Bannon, Erica M. Bednar, Jennifer Czerwinski, Jessica Davis, Leslie Dunnington, S. Shahrukh Hashmi, Courtney D. DiNardo

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Multiple genes have been identified to cause hereditary predispositions to hematologic malignancies, and characterized by an increased risk to develop myelodysplastic syndromes (MDS), acute myeloid leukemia (AML), and/or aplastic anemia (AA). Referral algorithms for patients who may be at higher risk have been proposed, with limited data regarding applicability. Our study aimed to evaluate referral criteria on a population of MDS/AML/AA patients. Demographic information and medical history were obtained from 608 patients referred over a 9-month period. Median age at diagnosis was 67 years (56–73), 387 (64%) were male, and the majority of individuals (54.9%) had AML. Overall, 406 individuals (66.8%) had insufficient documentation to determine whether certain criteria were met. Two hundred and two (33.2%) individuals met at least one criteria for genetic counseling referral; however, only nine (4.5%) were referred. Increased documentation of personal and family history is necessary to better assess and validate the applicability of these criteria.

Original languageEnglish (US)
Pages (from-to)3020-3027
Number of pages8
JournalLeukemia and Lymphoma
Volume60
Issue number12
DOIs
StatePublished - Oct 15 2019

Keywords

  • Hereditary hematologic malignancies
  • cancer genetics risk assessment
  • clinical detection algorithm
  • identifying at risk individuals
  • leukemia

ASJC Scopus subject areas

  • Hematology
  • Oncology
  • Cancer Research

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