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Clinical Policy Title: Chromosomal microarray analysis

Clinical Policy Number: CCP.1024

Effective Date: September 1, 2015

Initial Review Date: May 13, 2013

Most Recent Review Date: September 4, 2018

Next Review Date: September 2019

Related policies:

CCP.1045 Gene expression profile testing for breast cancer

CCP.1124 Genetic testing for autism spectrum disorders

CCP.1153 Genetic testing for cystic fibrosis

CCP.1175 Genetic testing for cytochrome p450 polymorphisms

CCP.1176 Genetic testing for G1691A polymorphisms factor V Leiden

CCP.1037 Genetic testing for long QT syndrome

CCP.1171 Genetic tests in neurology

CCP.1198 Genetic testing in sensorineural hearing loss

CCP.1374 Genetic testing for maple syrup urine disease

CCP.1233 Genetic testing for Alzheimer’s disease

CCP.1002 Maternal genetic testing

CCP.1012 Genetic testing for breast and ovarian cancer

CCP.1050 Familial polyposis gene testing

CCP.1060 Genetic and genomic testing criteria

CCP.1121 Genetic testing for prostate cancer prognosis

ABOUT THIS POLICY: AmeriHealth Caritas has developed clinical policies to assist with making coverage determinations. AmeriHealth Caritas’

clinical policies are based on guidelines from established industry sources, such as the Centers for Medicare & Medicaid Services (CMS), state regulatory agencies, the American Medical Association (AMA), medical specialty professional societies, and peer-reviewed professional literature. These clinical policies along with other sources, such as plan benefits and state and federal laws and regulatory requirements, including any state- or plan-specific definition of “medically necessary,” and the specific facts of the particular situation are considered by AmeriHealth Caritas when making coverage determinations. In the event of conflict between this clinical policy and plan benefits and/or state or federal laws and/or regulatory requirements, the plan benefits and/or state and federal laws and/or regulatory requirements shall control. AmeriHealth Caritas’ clinical policies are for informational purposes only and not intended as medical advice or to direct treatment. Physicians and other health care providers are solely responsible for the treatment decisions for their patients. AmeriHealth Caritas clinical policies are reflective of evidence-based medicine at the time of review. As medical science evolves, AmeriHealth Caritas will update its clinical policies as necessary. AmeriHealth Caritas’ clinical policies are not guarantees of payment.

Coverage policy

AmeriHealth Caritas considers chromosomal genomic hybridization testing to be clinically proven and,

Policy contains:

Array comparative genomic hybridization.

Autism spectrum disorders.

Chromosomal microarray analysis.

Comparative genomic hybridization.

Developmental delay.

G-band karyotyping.

Intellectual delay.

Karyotyping.

Single nucleotide polymorphism.

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therefore, medically necessary when:

A patient with a fetus with one or more major structural abnormalities identified on

ultrasonographic examination is undergoing invasive prenatal diagnosis.

A patient with a structurally normal fetus is undergoing invasive prenatal diagnostic testing.

After fetal death or stillbirth, testing fetal tissue to conduct further cytogenetic analysis to

improve detection of causative abnormalities is conducted.

An obstetrician-gynecologist or other health care provider with expertise in genetics provides

pre-test and post-test genetic counseling to the patient on benefits, limitations, and results of

chromosomal microarray analysis.

Informed consent, including discussion of the potential to identify findings of uncertain

significance, nonpaternity, consanguinity, and adult-onset disease, is given along with the

chromosomal microarray analysis (American College of Obstetricians and Gynecologists, 2016).

Limitations:

Routine use of whole-genome or whole-exome sequencing for prenatal diagnosis is not recommended

outside of the context of clinical trials until sufficient peer-reviewed data and validation studies are

published (American College of Obstetricians and Gynecologists, 2016).

All requests should be looked at individually in accordance with direction from appropriate authority

[e.g., Commonwealth of Pennsylvania Genetic Framework document (Appendix A)].

Alternative covered services:

Clinical evaluation by a network medical geneticist, neurologist, and other qualified specialist or by the

primary care physician constitutes covered services.

Background

Chromosomal microarray analysis is a diagnostic application suitable for identifying congenital

anomalies under certain conditions (e.g., abnormal fetal ultrasound, advanced maternal age, or positive

maternal serum aneuploidy screening); and for evaluating individuals with unexplained developmental

delay, autism spectrum disorder, or intellectual disability (i.e., intellectual developmental delay or

mental retardation) (Centre for Genetics Education, 2015). Deletions or extra copies of chromosomal

segments are known to be the cause of these disorders (Ahn, 2015).

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Chromosomal microarray analysis is also known as cytogenomic microarray analysis and collectively

describes two different laboratory techniques:

Array comparative genomic hybridization.

Single nucleotide polymorphism arrays (Miller, 2010).

Testing by chromosomal microarray can sometimes find a copy variant that may or may not explain a

health concern. It may also detect a variant with one or more genes related to health problems that

were not the reason for testing (Centre for Genetics Education, 2015).

In the prenatal setting, chromosomal microarray analysis requires an invasive procedure to collect intact

fetal cells (e.g., amniocentesis or chorionic villous sampling) (Van den Veyver, 2009). Blood samples can

be used for infants and children (Miller, 2010).

While conventional karyotyping detects large changes in the structure or number of whole

chromosomes (e.g., translocations, aneuploidy), chromosomal microarray analysis identifies genomic

copy number variations.

For decades, G-banded karyotyping has been the accepted first-line test for detecting genetic

imbalances in newborns. Chromosomal microarray analysis is a newer approach of detecting such

imbalances, beginning in the mid-2000s, and has replaced G-based karotyping for detecting genomic

copy number variants (Ahn, 2015). Chromosomal microarray analysis detects genomic imbalances at a

much higher resolution than does G-banded karyotyping (Ahn, 2015; Miller, 2010).

Copy number variations are chromosomal imbalances created as a result of the deletion and/or

duplication of one or more sections of deoxyribonucleic acid.

Single nucleotide polymorphism is distinguished from array comparative genomic hybridization in the

specificity of its application. In single nucleotide polymorphism, specific known deoxyribonucleic acid

sequence variants are evaluated. Array comparative genomic hybridization detects copy number

variations for relatively large deletions or duplications, including whole chromosome duplications, as in

trisomy.

Chromosomal microarray analysis does not detect balanced chromosome rearrangements in which

there is no gain or loss of deoxyribonucleic acid (e.g., balanced inversions or balanced translocations).

Searches

AmeriHealth Caritas searched PubMed and the databases of:

• UK National Health Services Center for Reviews and Dissemination.

• Agency for Healthcare Research and Quality’s National Guideline Clearinghouse and other

evidence-based practice centers.

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• The Centers for Medicare & Medicaid Services.

Searches were conducted on May 2, 2018. Search terms were: "comparative genomic hybridization,"

"chromosomal microassay analysis," and "single nucleotide polymorphisms."

We included:

• Systematic reviews, which pool results from multiple studies to achieve larger sample sizes and

greater precision of effect estimation than in smaller primary studies. Systematic reviews use

predetermined transparent methods to minimize bias, effectively treating the review as a

scientific endeavor, and are thus rated highest in evidence-grading hierarchies.

• Guidelines based on systematic reviews.

• Economic analyses, such as cost-effectiveness, and benefit or utility studies (but not simple cost

studies), reporting both costs and outcomes — sometimes referred to as efficiency studies —

which also rank near the top of evidence hierarchies.

Findings

A 2010 guideline that followed a systematic review of 33 studies, endorsed chromosomal microarray

testing, as opposed to G-banded karyotyping, as a first-line diagnostic method for developmental

delay/intellectual disabilities, autism spectrum disorder, or multiple congenital anomalies (Miller, 2010).

The following year, the Canadian College of Medical Geneticists recommended that chromosomal

microarray testing not be performed on women at low risk for chromosomal abnormalities (Duncan,

2011). An American College of Medical Genetics and Genomics work group produced a guideline stating

array comparative genomic hybridization testing will lead to improved therapeutics from improved

detection of congenital anomalies in fetuses and infants due to its higher resolution (Cooley, 2013).

A December 2016 Committee Opinion from the American College of Obstetricians and Gynecologists

recommended prenatal chromosomal microarray analysis for women of all ages, for fetuses with one or

more major structural abnormalities found on ultrasound, in structurally normal fetuses undergoing

diagnostic testing, and in evaluation of intrauterine fetal death or stillbirth to better understand cause

(American College of Obstetricians and Gynecologists, 2016).

The following systematic reviews, meta-analyses, and other large-scale studies offered evidence on the

efficacy of chromosomal genomic hybridization tests:

In a systematic review and meta-analysis of 23 studies including 5,507 pregnancy losses under

20 weeks, chromosomal microarray analysis provided informative results on copy number

variants in 95 percent of cases, almost significantly greater than karyotyping 68 percent (Pauta,

2018).

A systematic review and meta-analysis of 10 studies indicated a four percent incremental yield

of chromosomal microarray analysis over karyotyping in non-malformed growth-restricted

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fetuses, rising to 10 percent in fetal growth restriction for fetal malformations (Borrell, 2018).

A systematic review and meta-analysis was undertaken to assay the most frequent and

potentially significant copy number alterations in oral carcinogenesis. Gains were more frequent

than losses in the entire dataset. High-frequency gains were identified in chromosomes 5p, 14q,

11q, 7p, 17q, 20q, 8q, and 3q, whereas high-frequency losses were identified in chromosomes

3p, 8p, 6p, 18q, and 4q. Ingenuity pathway analysis showed that the top biological function was

associated with immortalization of the epithelial cells (p = 1.93E-04). The authors identified

multiple recurrent copy number alterations that are involved in various biological annotations

associated with oral carcinogenesis (Vincent-Chong, 2016).

In a meta-analysis of 17 studies of fetuses with increased nuchal translucency, genomic

microarray had an incremental yield of 5.0 percent more copy number variants than karotyping

(Grande, 2015).

In a meta-analysis of 13 studies of 1,131 prenatal cases with congenital heart disease, array

comparative genomic hybridization had an incremental yield of 7.0 percent than karotyping

(Jansen, 2015).

A systematic review and meta-analysis of nine papers addressed detection of chromosomal

abnormalities. Agreement between chromosomal microarray analysis and karyotyping was

observed in 86 percent of cases. Chromosomal microarray analysis detected 13 percent

additional chromosome abnormalities, versus three percent for karotyping (Dhillon, 2014).

A systematic review and meta-analysis included six studies of pregnant women who received

chorionic villus biopsies, amniocentesis, or cordocentesis. Subsequent tests for genetic

abnormalities showed that comparative genomic hybridization had sensitivity and specificity of

0.939 and 0.999, significantly greater — for sensitivity — than karotyping (0.626 and 0.999)

(Saldarriaga, 2014).

In a study of 4,406 high-risk pregnant women at 29 medical centers, microarray analysis

detected clinically relevant deletions or duplications in 6.0 percent, and in women with a normal

karyotype (Wapner, 2012).

In a systematic review of 10 articles, array comparative genomic hybridization detected 3.6

percent more genomic imbalances compared to conventional karyo-typing, rising to 5.2 percent

when the referral indication was a structural malformation on ultrasound (Hillman, 2011).

In a large controlled study that compared genetic tests for autism spectrum disorder,

comparative microarray analysis produced significantly more abnormal results than did karotype

(59/848, or 7.0 percent versus 19/852, or 2.23 percent) (Shen, 2010).

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A systematic review and meta-analysis of 19 studies (n = 13,926) addressed patients with

learning disabilities or congenital anomalies in whom conventional genetic tests were negative,

then tested with comparative genomic hybridization. The diagnostic yield of causal

abnormalities was 10 percent, with false-positive yield of noncausal abnormalities of seven

percent (Sagoo, 2009).

Although genomic microarray detects more chromosomal abnormalities than does karyotyping, a study

comparing these methods showed that better detection more than offset the higher costs, and thus

genomic microarray was more cost-effective than karotyping (Harper, 2014).

A literature review identified greater than 99 percent sensitivity and specificity of array comparative

genomic hybridization or single nucleotide polymorphism chips among pediatric patients with

developmental and intellectual disabilities, multiple congenital anomalies, and autistic spectrum

disorders. A diagnostic yield of 12 to 20 percent was observed, and approximately 60 percent of these

abnormalities were recurrent genomic disorders (Wei, 2013).

Studies have been conducted evaluating the efficacy of array comparative genomic hybridization to

detect abnormalities in populations other than fetuses. A meta-analysis of four studies (n = 159) of

persons with hepatocellular carcinoma who underwent the test found significant correlations between

chromosomal aberrations on the same chromosome or different chromosomes (Guo, 2011).

Policy updates:

A total of three guidelines/other and 11 peer-reviewed references were added to, and one

guideline/other were removed from this policy in July 2018.

Summary of clinical evidence:

Citation Content, Methods, Recommendations

Pauta (2018) Comparison of detecting pathogenic copy number variants after early pregnancy loss

Key points:

Systematic review and meta-analysis of 23 studies of 5,507 pregnancy losses

up to 20 weeks.

Chromosomal microarray analysis provided informative results in 95% of

cases (95% confidence interval 94% – 96%, compared with 68% (95%

confidence interval, 66% – 70%) for karotyping.

Incremental yields of chromosomal microarray analysis over karyotyping were

2% (95% confidence interval, 1% – 2%) for pathogenic copy number variants

and 4% (95% confidence interval, 3% – 6%) for variants of unknown

significance.

Vincent-Chong (2016) Immortalization of epithelial cells in

Key points:

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Citation Content, Methods, Recommendations

oral carcinogenesis as revealed by genome-wide array comparative genomic hybridization

A systematic review and meta-analysis was undertaken to assay the most

frequent and potentially significant copy number alterations in oral

carcinogenesis.

Gains were more frequent than losses in the entire dataset. High-frequency

gains were identified in chromosomes 5p, 14q, 11q, 7p, 17q, 20q, 8q, and 3q,

whereas high-frequency losses were identified in chromosomes 3p, 8p, 6p,

18q, and 4q. Ingenuity pathway analysis showed that the top biological

function was associated with immortalization of the epithelial cells (p = 1.93E-

04).

The authors identified multiple recurrent copy number alterations that are

involved in various biological annotations associated with oral carcinogenesis.

Dhillon (2014) Effectiveness comparison of techniques in diagnosis of chromosomal abnormalities

Key points:

Systematic review and meta-analysis of nine studies to detect chromosomal

abnormalities in fetuses after spontaneous miscarriage.

Agreement between chromosomal microarray analysis and karyotyping

observed in 86.0% of cases (95% confidence interval was 77.0% – 96.0%).

Chromosomal microarray analysis detected 13% (95% confidence interval

8.0% – 21.0%) additional chromosome abnormalities over conventional

karyotyping.

Conventional karyotyping detected 3% (95% confidence interval 1.0% –

10.0%) additional abnormalities over chromosomal microarray analysis.

Authors conclude that chromosomal microarray analysis has increased ability

to detect chromosomal deformities, compared to karotyping.

Saldarriaga (2014) Karyotype versus genomic hybridization for the prenatal diagnosis of chromosomal abnormalities: a meta-analysis

Key points:

Systematic review and meta-analysis inclusive of six randomized controlled trials.

Subjects were pregnant women who received chorionic villus biopsies, amniocentesis, or cordo-centesis and then underwent comparative genomic hybridization and karyotype analysis.

Sensitivity of genomic hybridization versus karyotype were 0.939 and 0.626.

Specificity of genomic hybridization and karyotype were both 0.999.

Authors concluded comparative genomic hybridization enjoys an advantage in the prenatal diagnosis of chromosomal and structural abnormalities over karyotyping.

Wapner (2012) Chromosomal microarray versus karyotyping for prenatal diagnosis

Key points:

Large multi-center observational study of 4,406 pregnant women published in The New England Journal of Medicine.

Chromosomal microarray analysis revealed chromosomal deletions or duplications in 6% of fetuses with an abnormal ultrasound and 1.7% of fetuses of pregnant women of advanced maternal age or positive aneuploidy serum screening result.

Hillman (2011) Additional information from array comparative genomic hybridization

Key points:

Systematic review and meta-analysis.

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Citation Content, Methods, Recommendations

technology over conventional karyotyping in prenatal diagnosis

Of the 135 potential articles, 10 were included in this systematic review and eight were included in the meta-analysis.

Array comparative genomic hybridization detected 3.6% (95% confidence interval, 1.9 – 13.9) more than karyotyping when the referral indication was a structural malformation on ultrasound.

The authors concluded there is an increased detection rate of chromosomal imbalances, compared with conventional karyotyping, when array comparative genomic hybridization techniques are employed in the prenatal population.

However, some are copy number imbalances that are not clinically significant.

The results carry implications for prenatal counseling and maternal anxiety.

Sagoo (2009) Array comparative genomic hybridization in patients with learning disability (mental retardation) and congenital anomalies

Key points:

Systematic review and meta‐analysis inclusive of 19 studies and 13,926 subjects.

Concluded array comparative genomic hybridization could be used to identify genetic abnormalities in patients with learning disabilities or congenital anomalies in which cytogenetic tests were negative.

Noted a risk of false‐positive results.

Unclear reporting, potential publication bias, and failure to appropriately consider study quality were limitations of the work.

References

Professional society guidelines/other:

American College of Obstetricians and Gynecologists/Society for Maternal Fetal Medicine. Committee

Opinion No. 682: Microarrays and Next-Generation Sequencing Technology: The Use of Advanced

Genetic Diagnostic Tools in Obstetrics and Gynecology. December, 2016. Obstet Gynecol.

2016;128e:262-268. https://www.acog.org/-/media/Committee-Opinions/Committee-on-

Genetics/co682.pdf?dmc=1&ts=20170705T0003145503. https://www.acog.org/-/media/Committee-

Opinions/Committee-on-Genetics/co682.pdf?dmc=1&ts=20170705T0003145503. Accessed July 26,

2018.

Centre for Genetics Education. Fact Sheet 16: Chromosome Microarray (CMA) Testing in Children &

Adults. Sydney, New South Wales, September 30, 2015. http://www.genetics.edu.au/publications-and-

resources/facts-sheets/fact-sheet-16-chromosome-microarray-cma-testing-in-children-and-adults.

Accessed July 25, 2018.

Cooley LD, Lebo M, Li MM, et al. Working Group of the American College of Medical Genetics and

Genomics (ACMG) Laboratory Quality Assurance Committee. American College of Medical Genetics and

Genomics technical standards and guidelines: microarray analysis for chromosome abnormalities in

neoplastic disorders. Genet Med. 2013;15(6):484-94. Doi: 10.1038/gim.2013.49.

Genomics Research. Handbook: Single Nucleotide Polymorphism. Bethesda MD: National Institutes of

Health. http://ghr.nlm.nih.gov/handbook/genomicresearch/snp. Accessed May 2, 2018.

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Miller DT, Adam MP, Aradhya S, 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):749-764. http://www.cell.com/ajhg/pdf/S0002-9297(10)00208-9.pdf.Accessed May

2, 2018.

Schaefer G, Mendelsohn N . Clinical genetics evaluation in identifying the etiology of autism spectrum

disorders: 2013 guideline revisions. Genet Med 2013:15(5):399–407. Website:

http://www.nature.com/gim/journal/v15/n5/full/gim201332a.html. Accessed May 2, 2018.

Peer-reviewed references:

Ahn JW, Coldwell M, Blint S, Ogilvie CM. Array comparative genomic hybridization (array CGH) for detection of genomic copy number variants. J Vis Exp. 2015;(96):51718. Doi: 10.3791/51718.

Borrell A, Grande M, Pauta M, Rodriguez-Revenga L, Figueras F. Chromosomal microarray analysis in

fetuses with growth restriction and normal karyotype: A systematic review and meta-analysis. Fetal

Diagn Ther. 2018;44(1):1-9. Doi: 10.1159/000479506.

Dhillon RK, Hillman SC, Morris RK, et al. Additional information from chromosomal microarray analysis

(CMA) over conventional karyotyping when diagnosing chromosomal abnormalities in miscarriage: a

systematic review and meta-analysis. BJOG. 2014;121(1):11-21. Doi: 10.1111/1471-0528.12382.

Duncan A, Langlois S, SOCG Genetics Committee, CCMG Prenatal Diagnosis Committee. Use of array

genomic hybridization technology in prenatal diagnosis in Canada. Canadian Journal of Obstetrics and

Gynecology. 2011;33(12):1256-1259.

Grande M, Jansen FA, Blumenfeld YJ, et al. Genomic microarray in fetuses with increased nuchal

translucency and normal karyotype: a systematic review and meta-analysis. Ultrasound Obstet Gynecol.

2015;46(6):650-658. Doi: 10.1002/uog.14880.

Guo X,Yanna, Ma X, et al. A meta-analysis of array-CGH studies implicates antiviral immunity pathways in the development of hepatocellular carcinoma. PLoS One. 2011;6(12):e28404. Doi: 10.1371/journal.pone.0028404.

Harper LM, Sutton AL, Longman RE, Odibo AO. An economic analysis of prenatal cytogenetic

technologies for sonographically detected fetal anomalies. Am J Med Genet A. 2014;164A(5):1192-1197.

Doi: 10.1002/ajmg.a.36435.

Jansen FA, Blumenfeld YJ, Fisher A, et al. Array comparative genomic hybridization and fetal congenital heart defects: a systematic review and meta-analysis. Ultrasound Obstet Gynecol. 2015;45(1):27-35. Doi: 10.1002/uog.14695.

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Hillman S, Pretlove S, Coomarasamy A, et. al. Additional information from array comparative genomic

hybridization technology over conventional karyotyping in prenatal diagnosis: a systematic review and

meta‐analysis. Ultrasound in Obstetrics and Gynecology. 2011;37(1):6‐14.

Miller DT, Adam MP, Aradhya S, 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):749-764. Doi: 10.1016/j.ajhg.2010.04.006.

Pauta M, Grande M, Rodriguez-Revenga L, Kolomietz E, Borrell A. Added value of chromosomal

microarray analysis over karyotyping in early pregnancy loss: systematic review and meta-analysis.

Ultrasound Obstet Gynecol. 2018;51(4):453-462. Doi: 10.1002/uog.18929.

Sagoo G, Butterworth A, Sanderson S, Shaw-Smith C, Higgins J P, Burton H. Array CGH in patients with

learning disability (mental retardation) and congenital anomalies: updated systematic review and meta-

analysis of 19 studies and 13,926 subjects. Genetics in Medicine.2009;11(3):139-146.

Saldarriaga W, Garcia-Perdomo H, Arango-Pineda J, Fonseca J. Karyotype versus genomic hybridization

for the prenatal diagnosis of chromosomal abnormalities: a metaanalysis. Am J Obstet Gynecol.

2015;212(3):330.e1-10. Doi: 10.1016/j.ajog.2014.10.011. http://www.ajog.org/article/S0002-

9378(14)01053-9/pdfSummary. Accessed May 2, 2018.

Shen Y, Dies K, Holm I, Bridgemohan C, et. al. Autism consortium clinical genetics/DNA diagnostics

collaboration. Clinical genetic testing for patients with autism spectrum disorders.

Pediatrics.2010;125(4):e727-735.

http://pediatrics.aappublications.org/content/pediatrics/125/4/e727.full.pdf Accessed May 2, 2018.

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 Spring;25(2)S:116-121.

Tammimies K, Marshall CR, Walker S, et al. Molecular diagnostic yield of chromosomal microarray

analysis and whole-exome sequencing in children with autism spectrum disorder. JAMA.

2015;314(9):895-903.

Van den Veyver IB, Patel A, Shaw CA, et al. Clinical use of array comparative genomic hybridization (aCGH) for prenatal diagnosis in 300 cases. Prenat Diagn. 2009; 29(1): 29-39. Doi: 10.1002/pd.2127.

Vincent-Chong VK, Salahshourifar I, Razali R, Anwar A, Zain RB. Immortalization of epithelial cells in oral

carcinogenesis as revealed by genome-wide array comparative genomic hybridization: A meta-analysis.

Head Neck. 2016 Apr;38 Suppl 1:E783-797.

Wapner R, Martin C, Levy B, Ballif C, et.al. Chromosomal microarray versus karyotyping for prenatal

fiagnosis. N Engl J Med. 2012; 367:2175-2184.

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Wei Y, Xu F, Li P. Technology-driven and evidence-based genomic analysis for integrated pediatric and

prenatal genetics evaluation. J Genet Genomics. 2013;40(1):1-14. Doi: 10.1016/j.jgg.2012.12.004.

Center for Medicare and Medicaid Services National Coverage Determinations:

National Coverage Determination for Cytogenetic Studies (190.3)

Benefit Category

Diagnostic Tests (other)

Note: This may not be an exhaustive list of all applicable Medicare benefit categories for this item or

service.

Item/Service Description

The term cytogenetic studies are used to describe the microscopic examination of the physical

appearance of human chromosomes.

Indications and Limitations of Coverage

Medicare covers these tests when they are reasonable and necessary for the diagnosis or treatment of

any of the following conditions:

Genetic disorders (e.g., mongolism) in a fetus. (See the Medicare Benefit Policy Chapter 15,

"Covered Medical and Other Health Services," §20.1.)

Failure of sexual development.

Chronic myelogenous leukemia.

Acute leukemias lymphoid (FAB L1-L3), myeloid (FAB M0-M7), and unclassified.

Mylodysplasia.

http://www.cms.gov/medicare-coverage-database/details/ncd-

details.aspx?NCDId=198&ncdver=1&bc=AAAAgAAAAAAAAApercent 3dpercent 3d&. Accessed May 2,

2018.

Local Coverage Determinations:

Local Coverage Determinations for cytogenetic studies were identified for Noridian and Wisconsin

Physicians Insurance companies:

http://www.cms.gov/medicare-coverage-database/indexes/lcd-alphabetical-

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index.aspx?DocType=All&bc=AgAAAAAAAAAAAApercent 3dpercent 3d&. Accessed May 2, 2018.

Commonly submitted codes

Below are the most commonly submitted codes for the service(s)/item(s) subject to this policy. This is

not an exhaustive list of codes. Providers are expected to consult the appropriate coding manuals and

bill in accordance with those manuals.

CPT Codes Description Comment

81228

Cytogenomic constitutional (genome-wide) microarray analysis; interrogation of genomic regions for copy number variants (e.g., bacterial artificial chromosome [BAC] or oligo-based comparative genomic hybridization [CGH] microarray analysis)

81229 Cytogenomic constitutional (genome-wide) microarray analysis; interrogation of genomic regions for copy number and single nucleotide polymorphism (SNP) variants for chromosomal abnormalities

ICD-10 Codes Description Comment

F70 Mild intellectual disabilities

F71 Moderate intellectual disabilities

F72 Profound intellectual disabilities

F74 Severe intellectual disabilities

F84.0 Autistic disorder

F84.3 Childhood disintegrative disorder

F84.5 Asperger’s disorder

F84.9 Pervasive developmental disorder

Q89.7 Multiple congenital anomalies(unspecified)

HCPCS Level II Codes

Description Comment

S3870 Comparative genomic hybridization (CGH) microarray testing for developmental delay, autism spectrum disorder and/or intellectual disability

Appendix A

Commonwealth of Pennsylvania genetic framework document

Genetic testing encompasses a large number of tests for a variety of indications including diagnosis,

carrier state, predisposition to a specific disease, and therapeutic decision making. There are also

different types of genetic tests, such as looking at single mutations, or multiple mutations. Each

managed care organization has a variety of policies for genetic testing. Some are disease- or condition-

specific and some are more general. It may make more sense for an to make one general policy

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statement or decide to have multiple policies, some of which are disease- specific. Some of these

policies may already have been reviewed and approved, but we are requesting that all

guidelines/policies be reviewed and resubmitted to be sure that the following guidelines are followed in

all policies:

1. The managed care organization may require some form of genetic counseling for each test, but

it does not have to be by a geneticist or genetic counselor who may not be readily accessible to

consumers in certain areas of the state. It can be a requirement that the genetic counseling

done by a specialist or other physician be equivalent to that provided by a genetic counselor,

but it should also be appropriate for the test being requested. For example, genetic testing for a

mutation that directs cancer treatment for acute lymphoblastic leukemia is probably

appropriately done by the oncologist ordering the test.

2. A genetic test is considered medically necessary if the results are expected to make a difference

in the recipient’s care or treatment plan, or the recipient (or a responsible family member/legal

guardian) intends to use the information in making decisions about care or treatment. An

example would be family planning decisions or planning of other indicated testing in light of the

diagnosis.

3. Genetic testing is medically necessary if it is a currently accepted method of diagnosis of a

condition or disease. (The managed care organization may still require that 1 and 2 apply).

Examples are the evaluation of global developmental disabilities, recurrent fetal loss, or multiple

congenital anomalies without an obvious etiology.

4. Genetic testing is medically necessary if by current guidelines it is consistent with the accepted

standards for disease predisposition testing or screening. (The managed care organization may

still require that 1 and 2 apply) Examples would be testing for cystic fibrosis carrier state in

women of reproductive age and BRCA testing.

5. Genetic testing is medically necessary if it is needed to determine appropriate medication or

treatment. (The managed care organization may still require that 1 and 2 apply) An example

would be for non-small cell lung cancer treatment (first line) Tarceva and Gilotrif. Food and Drug

Administration-approved epidermal growth factor receptor mutation test is required.

6. All requests should be considered individually, even if the above guideline criteria are not met.

7. All terms referring to genetic testing should be used correctly. Be careful when using the terms

microarray, comparative genomic hybridization, and single nucleotide polymorphisms.