Abstract
Background
Genetic diagnosis of unexplained global developmental delay and intellectual disability (GDD/ID) often ends the diagnostic odyssey and can lead to changes in clinical management.
Objective
The objective of this study was to investigate the cost effectiveness of testing scenarios involving several methods used to diagnose GDD/ID: karyotyping, chromosomal microarray analysis (CMA), and targeted next-generation sequencing (NGS).
Methods
We used decision-tree models to estimate the number of genetic diagnoses, the cost from a payers’ perspective in the USA, and the incremental cost per additional genetic diagnosis. Model parameters were taken from peer-reviewed literature and governmental fee schedules.
Results
CMA testing results in more genetic diagnoses at an incremental cost of US $2692 per additional diagnosis compared with karyotyping, which has an average cost per diagnosis of US $11,033. Performing both tests sequentially results in the same number of diagnoses, but the total cost is less when CMA testing is done first and karyotyping second. Furthermore, when CMA testing yields a variant of unknown significance, additional genetic diagnoses can be obtained at an incremental cost of US $4220 by CMA testing of both parents, and when parents are not available or the patient had a normal CMA result, targeted NGS of the patient can add diagnoses at a further incremental cost of US $12,295.
Conclusion
These results provide a cost effectiveness rationale for the use of CMA as the first-tier test for the genetic diagnosis of unexplained GDD/ID and further indicate that testing of both parents may be cost effective when a variant of unknown significance is detected in the patient.
Similar content being viewed by others
References
Shevell M, Ashwal S, Donley D, Flint J, Gingold M, Hirtz D, et al. Practice parameter: evaluation of the child with global developmental delay: report of the Quality Standards Subcommittee of the American Academy of Neurology and The Practice Committee of the Child Neurology Society. Neurology. 2003;60(3):367–80.
Maulik PK, Mascarenhas MN, Mathers CD, Dua T, Saxena S. Prevalence of intellectual disability: a meta-analysis of population-based studies. Res Dev Disabil. 2011;32(2):419–36.
Coulter ME, Miller DT, Harris DJ, Hawley P, Picker J, Roberts AE, et al. Chromosomal microarray testing influences medical management. Genet Med. 2011;13(9):770–6.
Ellison JW, Ravnan JB, Rosenfeld JA, Morton SA, Neill NJ, Williams MS, et al. Clinical utility of chromosomal microarray analysis. Pediatrics. 2012;130(5):e1085–95.
Riggs ER, Wain KE, Riethmaier D, Smith-Packard B, Faucett WA, Hoppman N, et al. Chromosomal microarray impacts clinical management. Clin Genet. 2014;85(2):147–53.
Peabody J, Martin M, DeMaria L, Florentino J, Paculdo D, Paul M, et al. Clinical utility of a comprehensive, whole genome CMA testing platform in pediatrics: a prospective randomized controlled trial of simulated patients in physician practices. PLoS One. 2016;11(12):e0169064.
Miller DT, Adam MP, Aradhya S, Biesecker LG, Brothman AR, Carter NP, et al. Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. Am J Hum Genet. 2010;86(5):749–64.
Kaminsky EB, Kaul V, Paschall J, Church DM, Bunke B, Kunig D, et al. An evidence-based approach to establish the functional and clinical significance of copy number variants in intellectual and developmental disabilities. Genet Med. 2011;13(9):777–84.
Hochstenbach R, van Binsbergen E, Engelen J, Nieuwint A, Polstra A, Poddighe P, et al. Array analysis and karyotyping: workflow consequences based on a retrospective study of 36,325 patients with idiopathic developmental delay in the Netherlands. Eur J Med Genet. 2009;52(4):161–9.
Moeschler JB, Shevell M, Committee on G. Comprehensive evaluation of the child with intellectual disability or global developmental delays. Pediatrics. 2014;134(3):e903–18.
Manning M, Hudgins L, Professional P, Guidelines C. Array-based technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities. Genet Med. 2010;12(11):742–5.
Michelson DJ, Shevell MI, Sherr EH, Moeschler JB, Gropman AL, Ashwal S. Evidence report: Genetic and metabolic testing on children with global developmental delay: report of the Quality Standards Subcommittee of the American Academy of Neurology and the Practice Committee of the Child Neurology Society. Neurology. 2011;77(17):1629–35.
Peabody J, DeMaria L, Tamandong-LaChica D, Florentino J, Acelajado MC, Burgon T. Low rates of genetic testing in children with developmental delays, intellectual disability, and autism spectrum disorders. Glob Pediatr Health. 2015;2:2333794X15623717.
Sagoo GS, Mohammed S, Barton G, Norbury G, Ahn JW, Ogilvie CM, et al. Cost effectiveness of using array-CGH for diagnosing learning disability. Appl Health Econ Health Policy. 2015;13(4):421–32.
Satya-Murti S, Cohen BH, Michelson D. Chromosomal microarray analysis for intellectual disabilities. Template coverage policy. American Academy of Neurology. https://www.aan.com/Guidelines/Home/GetGuidelineContent/640. Accessed 20 April 2017.
Wordsworth S, Buchanan J, Regan R, Davison V, Smith K, Dyer S, et al. Diagnosing idiopathic learning disability: a cost-effectiveness analysis of microarray technology in the National Health Service of the United Kingdom. Genom Med. 2007;1(1–2):35–45.
Trakadis Y, Shevell M. Microarray as a first genetic test in global developmental delay: a cost-effectiveness analysis. Dev Med Child Neurol. 2011;53(11):994–9.
Regier DA, Friedman JM, Marra CA. Value for money? Array genomic hybridization for diagnostic testing for genetic causes of intellectual disability. Am J Hum Genet. 2010;86(5):765–72.
de Ligt J, Willemsen MH, van Bon BW, Kleefstra T, Yntema HG, Kroes T, et al. Diagnostic exome sequencing in persons with severe intellectual disability. N Engl J Med. 2012;367(20):1921–9.
Sabatini LM, Mathews C, Ptak D, Doshi S, Tynan K, Hegde MR, et al. Genomic sequencing procedure microcosting analysis and health economic cost-impact analysis: a report of the Association for Molecular Pathology. J Mol Diagn. 2016;18(3):319–28.
Shen Y, Dies KA, Holm IA, Bridgemohan C, Sobeih MM, Caronna EB, et al. Clinical genetic testing for patients with autism spectrum disorders. Pediatrics. 2010;125(4):e727–35.
Pfundt R, Kwiatkowski K, Roter A, Shukla A, Thorland E, Hockett R, et al. Clinical performance of the CytoScan Dx Assay in diagnosing developmental delay/intellectual disability. Genet Med. 2016;18(2):168–73.
US Census Bureau and the US. Bureau of Labor Statistics. 2016 current population survey annual social and economic supplement. https://www.census.gov/newsroom/press-releases/2016/cb16-192.html. Accessed 15 April 2017.
Redin C, Gerard B, Lauer J, Herenger Y, Muller J, Quartier A, et al. Efficient strategy for the molecular diagnosis of intellectual disability using targeted high-throughput sequencing. J Med Genet. 2014;51(11):724–36.
Grozeva D, Carss K, Spasic-Boskovic O, Tejada MI, Gecz J, Shaw M, et al. Targeted next-generation sequencing analysis of 1,000 individuals with intellectual disability. Hum Mutat. 2015;36(12):1197–204.
Watson M. Downstream outcomes of new molecular diagnostics CPT coding system. Center for Medicare and Medicaid Services clinical diagnostic laboratory fee schedule. As reported in the Watson presentation. The majority of children live with two parents, census bureau reports. https://www.hrsa.gov/advisorycommittees/mchbadvisory/heritabledisorders/meetings/2014/fourth/watsonpresentation.pdf. Accessed 23 Mar 2017.
Center for Medicare and Medicaid Services. Clinical diagnostic laboratory fee schedule. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ClinicalLabFeeSched/Clinical-Laboratory-Fee-Schedule-Files.html. Accessed 23 Mar 2017.
Medi-Cal (California Department of Health Care Services). Genetic counseling and screening (gene coun). http://www.medi-cal.ca.gov/serp.asp?q=Genetic+Counseling+&cx=001779225245372747843%3Ajl7cpn-0my4&cof=FORID%3A10&ie=UTF-8. Accessed 4 Apr 2017.
Cohen DJ, Reynolds MR. Interpreting the results of cost-effectiveness studies. J Am Coll Cardiol. 2008;52(25):2119–26.
Giorgio E, Ciolfi A, Biamino E, Caputo V, Di Gregorio E, Belligni EF, et al. Whole exome sequencing is necessary to clarify ID/DD cases with de novo copy number variants of uncertain significance: two proof-of-concept examples. Am J Med Genet A. 2016;170(7):1772–9.
Acknowledgements
We thank Andre Arellano for technical assistance and Joseph Higgins and Jeff Radcliff for helpful comments on the manuscript.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
Yonghong Li, Lori A. Anderson, Edward I. Ginns, and James J. Devlin are employed by Quest Diagnostics.
Funding
All funding was provided by Quest Diagnostics
Ethical approval and informed consent
No patients were enrolled and nor was protected health information used in this study.
Rights and permissions
About this article
Cite this article
Li, Y., Anderson, L.A., Ginns, E.I. et al. Cost Effectiveness of Karyotyping, Chromosomal Microarray Analysis, and Targeted Next-Generation Sequencing of Patients with Unexplained Global Developmental Delay or Intellectual Disability. Mol Diagn Ther 22, 129–138 (2018). https://doi.org/10.1007/s40291-017-0309-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40291-017-0309-5