Chromosomal microarray impacts clinical management

Clin Genet. 2014 Feb;85(2):147-53. doi: 10.1111/cge.12107. Epub 2013 Feb 21.

Abstract

Chromosomal microarray analysis (CMA) is standard of care, first-tier clinical testing for detection of genomic copy number variation among patients with developmental disabilities. Although diagnostic yield is higher than traditional cytogenetic testing, management impact has not been well studied. We surveyed genetic services providers regarding CMA ordering practices and perceptions about reimbursement. Lack of insurance coverage because of perceived lack of clinical utility was cited among the most frequent reasons why CMA was not ordered when warranted. We compiled a list of genomic regions where haploinsufficiency or triplosensitivity cause genetic conditions with documented management recommendations, estimating that at least 146 conditions potentially diagnosable by CMA testing have published literature supporting specific clinical management implications. Comparison with an existing clinical CMA database to determine the proportion of cases involving these regions showed that CMA diagnoses associated with such recommendations are found in approximately 7% of all cases (n = 28,526). We conclude that CMA impacts clinical management at a rate similar to other genetic tests for which insurance coverage is more readily approved. The information presented here can be used to address barriers that continue to contribute to inequities in patient access and care in regard to CMA testing.

Keywords: array comparative genomic hybridization; chromosomal microarray analysis; genetic testing; patient care management.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • DNA Copy Number Variations / genetics*
  • Developmental Disabilities / diagnosis*
  • Developmental Disabilities / genetics
  • Disease Management*
  • Genetic Services / economics*
  • Genetic Services / statistics & numerical data
  • Humans
  • Insurance, Health, Reimbursement / economics*
  • Insurance, Health, Reimbursement / statistics & numerical data
  • Microarray Analysis / economics*
  • Microarray Analysis / methods
  • Physicians / statistics & numerical data*
  • Practice Patterns, Physicians' / statistics & numerical data