Skip to main content
Log in

Cost-effectiveness of Genome and Exome Sequencing in Children Diagnosed with Autism Spectrum Disorder

  • Original Research Article
  • Published:
Applied Health Economics and Health Policy Aims and scope Submit manuscript

Abstract

Background

Genome (GS) and exome sequencing (ES) could potentially identify pathogenic variants with greater sensitivity than chromosomal microarray (CMA) in autism spectrum disorder (ASD) but are costlier and result interpretation can be uncertain. Study objective was to compare the costs and outcomes of four genetic testing strategies in children with ASD.

Methods

A microsimulation model estimated the outcomes and costs (in societal and public payer perspectives in Ontario, Canada) of four genetic testing strategies: CMA for all, CMA for all followed by ES for those with negative CMA and syndromic features (CMA+ES), ES or GS for all.

Results

Compared to CMA, the incremental cost-effectiveness ratio (ICER) per additional child identified with rare pathogenic variants within 18 months of ASD diagnosis was $CAN5997.8 for CMA+ES, $CAN13,504.2 for ES and $CAN10,784.5 for GS in the societal perspective. ICERs were sensitive to changes in ES or GS diagnostic yields, wait times for test results or pre-test genetic counselling, but were robust to changes in the ES or GS costs.

Conclusion

Strategic integration of ES into ASD care could be a cost-effective strategy. Long wait times for genetic services and uncertain utility, both clinical and personal, of sequencing results could limit broader clinical implementation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data Availability Statement

The TreeAge model and R code for analyzing the data are available at tspace.library.utoronto.ca/handle/1807/80706, a public repository for the University of Toronto.

References

  1. Centers for Disease Control and Prevention. Prevalence and characteristics of autism spectrum disorder among children aged 8 years- Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States. Morb Mortal Wkly Rep. 2012;2016:65.

    Google Scholar 

  2. Tick B, Bolton P, Happé F, Rutter M, Rijsdijk F. Heritability of autism spectrum disorders: a meta-analysis of twin studies. J Child Psychol Psychiatry. 2016;57:585–95.

    Article  PubMed  Google Scholar 

  3. Devlin B, Scherer SW. Genetic architecture in autism spectrum disorder. Curr Opin Genet Dev. 2012;22:229–37.

    Article  PubMed  CAS  Google Scholar 

  4. Carter M, Scherer S. Autism spectrum disorder in the genetics clinic: a review: autism spectrum disorder in the genetics clinic. Clin Genet. 2013;83:399–407.

    Article  PubMed  CAS  Google Scholar 

  5. Schaefer GB, Mendelsohn NJ. Clinical genetics evaluation in identifying the etiology of autism spectrum disorders: 2013 guideline revisions. Genet Med. 2013;15:399–407.

    Article  PubMed  CAS  Google Scholar 

  6. Iossifov I, O’Roak BJ, Sanders SJ, Ronemus M, Krumm N, Levy D, et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature. 2014;515:216–21.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Tammimies K, Marshall CR, Walker S, Kaur G, Thiruvahindrapuram B, Lionel AC, et al. Molecular diagnostic yield of chromosomal microarray analysis and whole-exome sequencing in children with autism spectrum disorder. JAMA. 2015;314:895–903.

    Article  PubMed  CAS  Google Scholar 

  8. Marshall CR, Noor A, Vincent JB, Lionel AC, Feuk L, Skaug J, et al. Structural variation of chromosomes in autism spectrum disorder. Am J Hum Genet. 2008;82:477–88.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Anagnostou E, Zwaigenbaum L, Szatmari P, Fombonne E, Fernandez BA, Woodbury-Smith M, et al. Autism spectrum disorder: advances in evidence-based practice. Can Med Assoc J. 2014;186:509–19.

    Article  Google Scholar 

  10. 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;86:749–64.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Volkmar F, Siegel M, Woodbury-Smith M, King B, McCracken J, State M. Practice parameter for the assessment and treatment of children and adolescents with autism spectrum disorder. J Am Acad Child Adolesc Psychiatry. 2014;53:237–57.

    Article  PubMed  Google Scholar 

  12. Jiang Y, Yuen RKC, Jin X, Wang M, Chen N, Wu X, et al. Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing. Am J Hum Genet. 2013;93:249–63.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Yuen RKC, Thiruvahindrapuram B, Merico D, Walker S, Tammimies K, Hoang N, et al. Whole-genome sequencing of quartet families with autism spectrum disorder. Nat Med. 2015;21:185–91.

    Article  PubMed  CAS  Google Scholar 

  14. Tsiplova K, Zur R, Marshall CR, Stavropoulos DJ, Pereira SL, Merico D, et al. A microcosting and cost-consequence analysis of genomic testing strategies in autism spectrum disorder. Genet Med. 2017;19:1268–75.

    Article  PubMed  Google Scholar 

  15. Ziegler A, Rudolph-Rothfeld W, Vonthein R. Genetic testing for autism spectrum disorder is lacking evidence of cost-effectiveness: a systematic review. Methods Inf Med. 2017;56:268–73.

    Article  PubMed  Google Scholar 

  16. Sanders GD, Neumann PJ, Basu A, Brock DW, Feeny D, Krahn M, et al. Recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses: second panel on cost-effectiveness in health and medicine. JAMA. 2016;316:1093.

    Article  PubMed  Google Scholar 

  17. Green RC, Berg JS, Grody WW, Kalia SS, Korf BR, Martin CL, et al. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. 2013;15:565–74.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Kalia SS, Adelman K, Bale SJ, Chung WK, Eng C, Evans JP, et al. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med. 2016;19:249–55.

    Article  PubMed  Google Scholar 

  19. Filipek PA, Accardo PJ, Ashwal S, Baranek GT, Cook EH, Dawson G, et al. Practice parameter: screening and diagnosis of autism: report of the Quality Standards Subcommittee of the American Academy of Neurology and the Child Neurology Society. Neurology. 2000;55:468–79.

    Article  PubMed  CAS  Google Scholar 

  20. Johnson CP, Myers SM, the Council on Children With Disabilities. Identification and evaluation of children with autism spectrum disorders. Pediatrics. 2007;120:1183–215.

    Article  PubMed  Google Scholar 

  21. Vermeesch JR, Fiegler H, de Leeuw N, Szuhai K, Schoumans J, Ciccone R, et al. Guidelines for molecular karyotyping in constitutional genetic diagnosis. Eur J Hum Genet. 2007;15:1105–14.

    Article  PubMed  CAS  Google Scholar 

  22. Statistics Canada. Table 282-0074. Labour force survey estimates (LFS), wages of employees by job permanence, union coverage, sex and age group [Internet]. 2015 [cited 2016 Jan 19]. http://www5.statcan.gc.ca/cansim/a26?lang=eng&id=2820074. Accessed Jan 2016.

  23. Software TreeAge. TreeAge Pro 2015. Williamstown: TreeAge Software; 2015.

    Google Scholar 

  24. Rossi M, El-Khechen D, Black MH, Farwell Hagman KD, Tang S, Powis Z. Outcomes of diagnostic exome sequencing in patients with diagnosed or suspected autism spectrum disorders. Pediatr Neurol. 2017;70(34–43):e2.

    Google Scholar 

  25. Laupacis A, Feeny D, Detsky AS, Tugwell PX. How attractive does a new technology have to be to warrant adoption and utilization? Tentative guidelines for using clinical and economic evaluations. CMAJ. 1992;146:473–81.

    PubMed  PubMed Central  CAS  Google Scholar 

  26. Monroe GR, Frederix GW, Savelberg SMC, de Vries TI, Duran KJ, van der Smagt JJ, et al. Effectiveness of whole-exome sequencing and costs of the traditional diagnostic trajectory in children with intellectual disability. Genet Med. 2016;18:949–56.

    Article  PubMed  CAS  Google Scholar 

  27. Ungar WJ. Next generation sequencing and health technology assessment in autism spectrum disorder. J Can Acad Child Adolesc Psychiatry. 2015;24:123–7.

    PubMed  PubMed Central  Google Scholar 

  28. Health Quality Ontario. Ontario Genetic Advisory Committee terms of reference [Internet]. Health Quality Ontario; 2016. http://www.hqontario.ca/portals/0/documents/evidence/reports/ogac-terms-of-reference-en.pdf. Accessed May 2017.

  29. Grosse SD, Wordsworth S, Payne K. Economic methods for valuing the outcomes of genetic testing: beyond cost-effectiveness analysis. Genet Med. 2008;10:648–54.

    Article  PubMed  Google Scholar 

  30. Gray E, Eden M, Vass C, McAllister M, Louviere J, Payne K. Valuing preferences for the process and outcomes of clinical genetics services: a pilot study. Patient. 2016;9:135–47.

    Article  PubMed  Google Scholar 

  31. Payne K, McAllister M, Davies LM. Valuing the economic benefits of complex interventions: when maximising health is not sufficient. Health Econ. 2013;22:258–71.

    Article  PubMed  Google Scholar 

  32. Oosterhoff M, van der Maas ME, Steuten LMG. A systematic review of health economic evaluations of diagnostic biomarkers. Appl Health Econ Health Policy. 2016;14:51–65.

    Article  PubMed  Google Scholar 

  33. Coo H, Ouellette-Kuntz H, Lam M, Yu CT, Dewey D, Bernier FP, et al. Correlates of age at diagnosis of autism spectrum disorders in six Canadian regions. Chronic Dis Inj Can. 2012;32:90–100.

    PubMed  CAS  Google Scholar 

  34. Banach R, Thompson A, Szatmari P, Goldberg J, Tuff L, Zwaigenbaum L, et al. Brief report: relationship between non-verbal IQ and gender in autism. J Autism Dev Disord. 2009;39:188–93.

    Article  PubMed  Google Scholar 

  35. Charman T, Pickles A, Simonoff E, Chandler S, Loucas T, Baird G. IQ in children with autism spectrum disorders: data from the Special Needs and Autism Project (SNAP). Psychol Med. 2011;41:619–27.

    Article  PubMed  CAS  Google Scholar 

  36. Yeargin-Allsopp M, Rice C, Karapurkar T, Doernberg N, Boyle C, Murphy C. Prevalence of autism in a US metropolitan area. JAMA. 2003;289:49–55.

    Article  PubMed  Google Scholar 

  37. Dawson S, Glasson EJ, Dixon G, Bower C. Birth defects in children with autism spectrum disorders: a population-based, nested case-control study. Am J Epidemiol. 2009;169:1296–303.

    Article  PubMed  Google Scholar 

  38. Timonen-Soivio L, Vanhala R, Malm H, Leivonen S, Jokiranta E, Hinkka-Yli-Salomäki S, et al. The association between congenital anomalies and autism spectrum disorders in a Finnish national birth cohort. Dev Med Child Neurol. 2015;57:75–80.

    Article  PubMed  Google Scholar 

  39. Wier ML, Yoshida CK, Odouli R, Grether JK, Croen LA. Congenital anomalies associated with autism spectrum disorders. Dev Med Child Neurol. 2006;48:500–7.

    Article  PubMed  Google Scholar 

  40. Fombonne E, Rogé B, Claverie J, Courty S, Frémolle J. Microcephaly and macrocephaly in autism. J Autism Dev Disord. 1999;29:113–9.

    Article  PubMed  CAS  Google Scholar 

  41. Lainhart JE, Bigler ED, Bocian M, Coon H, Dinh E, Dawson G, et al. Head circumference and height in autism: a study by the Collaborative Program of Excellence in Autism. Am J Med Genet A. 2006;140:2257–74.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Ontario Genetics Secretariat. Clinical genetics wait time study report. Toronto: Hospital for Sick Children; 2014.

  43. McGrew SG, Peters BR, Crittendon JA, Veenstra-Vanderweele J. Diagnostic yield of chromosomal microarray analysis in an autism primary care practice: which guidelines to implement? J Autism Dev Disord. 2012;42:1582–91.

    Article  PubMed  Google Scholar 

  44. 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:e727–35.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Hospital for Sick Children. Molecular genetic lab- Billing and CPT codes. Toronto: Hospital for Sick Children; 2015.

  46. Ministry of Health and Long-Term Care. Schedule of benefits for physician services under the Health Insurance Act [Internet]. 2015 [cited 2015 Nov 9]. http://www.health.gov.on.ca/english/providers/program/ohip/sob/physserv/physserv_mn.html. Accessed Nov 2015.

  47. Régie de l’assurance maladie du Québec. Manuel de facturation. rémunération à l’acte. Table B-Tarification des visites. [Internet]. Régle de l’assurance maladie Quebec; 2015 [cited 2016 Apr 25]. http://www.ramq.gouv.qc.ca/fr/professionnels/medecins-specialistes/manuels/Pages/facturation.aspx. Accessed April 2016.

Download references

Acknowledgements

The authors would like to acknowledge inputs from Robyn Hayeems, Ny Hoang, Cheryl Shuman and Kate Tsiplova on the parameters used in the model.

Author information

Authors and Affiliations

Authors

Contributions

All authors (TY, MTC, PS, WJU) contributed to the conceptualization of model, interpretation of findings, editing of the manuscript and provided final approval of the paper. TY and WJU were responsible for model building, data analysis and drafting the manuscript.

Corresponding author

Correspondence to Wendy J. Ungar.

Ethics declarations

Funding

TY was supported through the Canada Institutes of Health Research Autism Research Training Program, Doctoral Autism Scholars Award, Ontario Graduate Scholarship and RestraComp Hospital for Sick Children Foundation Student Scholarship Program. No other funding was received for this study.

Conflict of interest

All authors (TY, MTC, PS, WJU) declare no conflicts of interest.

Human and animal rights statement

This article does not contain studies with human participant or animals performed by any of the authors.

Informed consent

For this type of study formal consent is not required.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 27 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yuen, T., Carter, M.T., Szatmari, P. et al. Cost-effectiveness of Genome and Exome Sequencing in Children Diagnosed with Autism Spectrum Disorder. Appl Health Econ Health Policy 16, 481–493 (2018). https://doi.org/10.1007/s40258-018-0390-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40258-018-0390-x

Navigation