Genetic Testing for Autism Spectrum Disorder is Lacking Evidence of Cost-effectiveness^[*]

Summary

Background: Autism Spectrum Disorder (ASD) is a highly heritable neural development disorder characterized by social impairment. The earlier the diagnosis is made, the higher are the chances of obtaining relief of symptoms. A very early diagnosis uses molecular genetic tests, which are also offered commercially.

Objective: Systematic review of the economic impact of genetic tests in ASD.

Methods: We performed a systematic search of databases Pubmed, Medline, Cochrane, Econlit and the NHS Center for Reviews and Dissemination for articles in English and German from January 1, 2000 to December 31, 2015. Original articles published in peer- reviewed journals were screened in a two- step process. First, we focused our search on economic evaluations of genetic tests for ASD. Second, we searched for any economic evaluation (EE) of genetic tests.

Results: We identified 185 EE of genetic tests for various diseases. However, not a single EE of genetic tests has been found for ASD. The outcomes used in the EE of the genetic tests were heterogeneous, and results were generally not comparable.

Conclusion: There is no evidence for cost-effectiveness of any genetic diagnostic test for ASD, although such genetic tests are available commercially. Cost-effectiveness analyses for genetic diagnostic tests for ASD are urgently required. There is a clear lack in research for EE of genetic tests.

Keywords

Autism - ASD - genetic test - cost-effectiveness - JEL Classification I11

• References

• 1 Marshall ES. Increasing prevalence of autism: implications for school nursing. NASN Sch Nurse. 2014; 29: 241-243.
• 2 Autism and Developmental Disabilities Monitoring Network Surveillance Year 2010 Principal Investigators. Prevalence of Autism Spectrum Disorders - Autism and Developmental Disabilities Monitoring Network. United States, 2010. MMWR Surveill Summ. 2014; 63: 1-21.
• 3 Buescher AV, Cidav Z, Knapp M, Mandell DS. Costs of autism spectrum disorders in the United Kingdom and the United States. JAMA Pediatr. 2014; 168: 721-728.
• 4 Amendah D, Grosse SD, Peackock G, Mandell DS. The Economic Cost of Autism: A Review. Amaral D, Geschwind D, Dawson G. Autism Spectrum Disorders.. Oxford: Oxford University Press; 2011: 1347-1360.
• 5 Peacock G, Amendah D, Ouyang L, Grosse SD. Autism spectrum disorders and health care expenditures: the effects of co-occurring conditions. J Dev Behav Pediatr. 2012; 33: 2-8.
• 6 Bradshaw J, Steiner AM, Gengoux G, Koegel LK. Feasibility and effectiveness of very early intervention for infants at-risk for autism spectrum disorder: a systematic review. J Autism Dev Disord. 2015; 45: 778-794.
• 7 Dawson G, Rogers S, Munson J, Smith M, Winter J, Greenson J. et al. Randomized, controlled trial of an intervention for toddlers with autism: the Early Start Denver Model. Pediatrics. 2010; 125: e17-23.
• 8 Estes A, Munson J, Rogers SJ, Greenson J, Winter J, Dawson G. Long-Term Outcomes of Early Intervention in 6-Year-Old Children With Autism Spectrum Disorder. J Am Acad Child Adolesc Psychiatry. 2015; 54: 580-587.
• 9 Dawson G, Jones EJ, Merkle K, Venema K, Lowy R, Faja S. et al. Early behavioral intervention is associated with normalized brain activity in young children with autism. J Am Acad Child Adolesc Psychiatry. 2012; 51: 1150-1159.
• 10 Fakhoury M. Autistic spectrum disorders: A review of clinical features, theories and diagnosis. Int J Dev Neurosci. 2015; 43: 70-77.
• 11 Watson LR, Baranek GT, Crais ER, Steven Reznick J, Dykstra J, Perryman T. The first year inventory: retrospective parent responses to a questionnaire designed to identify one-year-olds at risk for autism. J Autism Dev Disord. 2007; 37: 49-61.
• 12 Wiggins LD, Baio J, Rice C. Examination of the time between first evaluation and first autism spectrum diagnosis in a population-based sample. J Dev Behav Pediatr. 2006; 27: S79-87.
• 13 Daniels AM, Halladay AK, Shih A, Elder LM, Dawson G. Approaches to enhancing the early detection of autism spectrum disorders: a systematic review of the literature. J Am Acad Child Adolesc Psychiatry. 2014; 53: 141-152.
• 14 Bolte S, Westerwald E, Holtmann M, Freitag C, Poustka F. Autistic Traits and Autism Spectrum Disorders: The Clinical Validity of Two Measures Presuming a Continuum of Social Communication Skills. J Autism Dev Disord. 2011; 41: 66-72.
• 15 Falkmer T, Anderson K, Falkmer M, Horlin C. Diagnostic procedures in autism spectrum disorders: a systematic literature review. Eur Child Adolesc Psychiatry. 2013; 22: 329-340.
• 16 Oosterling I, Roos S, de Bildt A, Rommelse N, de Jonge M, Visser J. et al. Improved diagnostic validity of the ADOS revised algorithms: a replication study in an independent sample. J Autism Dev Disord. 2010; 40: 689-703.
• 17 DiLavore PC, Lord C, Rutter M. The pre-linguistic autism diagnostic observation schedule. J Autism Dev Disord. 1995; 25: 355-379.
• 18 Abrahams BS, Geschwind DH. Advances in autism genetics: on the threshold of a new neurobiology. Nat Rev Genet. 2008; 9: 341-355.
• 19 Eapen V. Genetic basis of autism: is there a way forward?. Curr Opin Psychiatry. 2011; 24: 226-236.
• 20 Lauritsen MB, Pedersen CB, Mortensen PB. Effects of familial risk factors and place of birth on the risk of autism: a nationwide register-based study. J Child Psychol Psychiatry. 2005; 46: 963-971.
• 21 Risch N, Hoffmann TJ, Anderson M, Croen LA, Grether JK, Windham GC. Familial recurrence of autism spectrum disorder: evaluating genetic and environmental contributions. Am J Psychiatry. 2014; 171: 1206-1213.
• 22 Skafidas E, Testa R, Zantomio D, Chana G, Everall IP, Pantelis C. Predicting the diagnosis of autism spectrum disorder using gene pathway analysis. Mol Psychiatry. 2014; 19: 504-510.
• 23 De Rubeis S, Buxbaum JD. Genetics and genomics of autism spectrum disorder: embracing complexity. Hum Mol Genet. 2015; 24: R24-31.
• 24 Bauer SC, Msall ME. Genetic testing for autism spectrum disorders. Dev Disabil Res Rev. 2011; 17: 3-8.
• 25 Persico AM, Napolioni V. Autism genetics. Behav Brain Res. 2013; 251: 95-112.
• 26 Gaugler T, Klei L, Sanders SJ, Bodea CA, Goldberg AP, Lee AB. et al. Most genetic risk for autism resides with common variation. Nat Genet. 2014; 46: 881-885.
• 27 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.
• 28 Szego MJ, Zawati MH. Whole genome sequencing as a genetic test for autism spectrum disorder: from bench to bedside and then back again. J Can Acad Child Adolesc Psychiatry. 2016; 25: 116-121.
• 29 Carayol J, Schellenberg GD, Dombroski B, Amiet C, Genin B, Fontaine K. et al. A scoring strategy combining statistics and functional genomics supports a possible role for common polygenic variation in autism. Front Genet. 2014; 5: 33.
• 30 Matsunami N, Hadley D, Hensel CH, Christensen GB, Kim C, Frackelton E. et al. Identification of rare recurrent copy number variants in high-risk autism families and their prevalence in a large ASD population. PLoS One. 2013; 8: e52239.
• 31 Sun F, Oristaglio J, Levy SE, Hakonarson H, Sullivan N, Fontanarosa J. et al. Genetic Testing for Developmental Disabilities, Intellectual Disability, and Autism Spectrum Disorder.. Rockville (MD): Agency for Healthcare Research and Quality; 2015
• 32 Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol. 2009; 62: 1006-1012.
• 33 Husereau D, Drummond M, Petrou S, Carswell C, Moher D, Greenberg D. et al. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. Int J Technol Assess Health Care. 2013; 29: 117-122.
• 34 Centre for Reviews and Dissemination. Systematic Reviews: CRD’s Guidance for Undertaking Reviews in Health Care.. 3rd ed. University of York: NHS Centre for Reviews and Dissemination; 2009
• 35 Drummond M, Sculpher M, Torrance G, O’Brien B, Stoddart G. Methods for the Economic Evaluation of Health Care Programmes.. 3rd ed. Oxford: Oxford Medical Publications, Oxford University Press; 2015
• 36 Philips Z, Bojke L, Sculpher M, Claxton K, Golder S. Good practice guidelines for decision-analytic modelling in health technology assessment: a review and consolidation of quality assessment. Pharmacoeconomics. 2006; 24: 355-371.
• 37 Siebert U. Entscheidungsanalytische Modelle zur Sicherung der Übertragbarkeit internationaler Evidenz von HTA auf den Kontext des deutschen Gesundheitssystems. DIMDI. 2005: 107 German.:
• 38 Drummond M, Sculpher M, Torrance G, O’Brien B, Stoddart G. Methods for the Economic Evaluation of Health Care Programmes.. 3rd ed. Oxford: Oxford Medical Publications, Oxford University Press; 2005: 380.
• 39 Bölte S. Autismus: Spektrum, Ursachen, Diagnostik, Intervention, Perspektiven.. Bern: Huber; 2009. German.
• 40 Food and Drug Administration. Nucleic acid based tests. 2015 [cited 2015 Aug 11]. Available from: www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/InVitroDiagnostics/ucm330711.htm.
• 41 Antonanzas F, Rodriguez-Ibeas R, Hutter MF, Lorente R, Juarez C, Pinillos M. Genetic testing in the European Union: does economic evaluation matter?. Eur J Health Econ. 2012; 13: 651-661.
• 42 Assasi N, Schwartz L, Tarride JE, Goeree R, Xie F. Economic evaluations conducted for assessment of genetic testing technologies: a systematic review. Genet Test Mol Biomarkers. 2012; 16: 1322-1335.
• 43 Djalalov S, Musa Z, Mendelson M, Siminovitch K, Hoch J. A review of economic evaluations of genetic testing services and interventions (20042009). Genet Med. 2011; 13: 89-94.
• 44 Vegter S, Boersma C, Rozenbaum M, Wilffert B, Navis G, Postma MJ. Pharmacoeconomic evaluations of pharmacogenetic and genomic screening programmes: a systematic review on content and adherence to guidelines. Pharmacoeconomics. 2008; 26: 569-587.