BlueCross and BlueShield of Montana Medical Policy/Codes
Non-BRCA (Breast Cancer) Risk Assessment
Chapter: Genetic Testing
Current Effective Date: October 25, 2013
Original Effective Date: June 07, 2010
Publish Date: October 25, 2013
Revised Dates: December 1, 2011; October 19, 2012; September 24, 2013
Description

Breast cancer risk increases with age, environmental factors and genetics.  The modern era of breast cancer risk assessment began with the identification of highly penetrant mutations of BRCA1 (breast cancer 1) and BRCA2 (breast cancer 2) genes that are found in strong family histories.  However, BRCA1 and BRCA2 mutations, along with a few others, account for less than 25% of inherited breast cancers.  The majority of breast cancer occurs sporadically in women with little or no family history. 

OncoVue® is a genetic test that is intended to provide predictive information about breast cancer risk in asymptomatic women.  Current methods of assessing breast cancer risk, e.g. the Gail Model, are imperfect and genetic testing may offer improvements on current ability to assess breast cancer risk. 

OncoVue Breast Cancer Risk Test, produced by InterGenetics®, is a proprietary test that evaluates multiple-risk single nucleotide polymorphism (SNPs) associated with breast cancer.  The test does not detect known high-risk genetic factors such as BRCA mutations (associated with hereditary breast and ovarian cancer).  OncoVue synthesizes the various genetic and medical history risk measures into a personalized single-risk estimate for premenopause, perimenopause, and postmenopause for each patient, with comparison to the average population risk at each of these life stages.  The test is stated to be “an aid in the qualitative assessment of breast cancer risk…not intended as a stand-alone test for the determination of breast cancer risk in women.”

For women without a strong family history of breast cancer and at average risk prior to testing, OncoVue purports to estimate a woman’s individual risk and place her in standard-, moderate-, or high-risk groups.  The results are intended to help a woman and her physician decide if more frequent exams and/or more sophisticated surveillance techniques are indicated.  For women already known to be at high-risk based on a family history consistent with hereditary breast cancer, the test is represented as having added value by indicating greater or lesser risk at different life stages.

The OncoVue test is available only through the Breast Cancer Risk Testing Network (BCRTN), described as a network of Breast Care Centers engaged in frontline genetic identification of breast cancer risk levels in their patients.  BCRTN member centers will provide genetic breast cancer risk testing for their patients using OncoVue as part of a comprehensive education program to help OncoVue “at-risk” women understand their risk level and intervention strategies. BCRTN members will be selected for the network, based on a number of criteria, including quality standards of care, level of breast cancer surveillance technology, and the capability of providing patient education on genetic testing and future risk management protocols.  As of August 2011, 36 Breast Care Centers, located in 20 states, were listed on the InterGenetics web site.

Policy

Each benefit plan, summary plan description or contract defines which services are covered, which services are excluded, and which services are subject to dollar caps or other limitations, conditions or exclusions.  Members and their providers have the responsibility for consulting the member's benefit plan, summary plan description or contract to determine if there are any exclusions or other benefit limitations applicable to this service or supply.  If there is a discrepancy between a Medical Policy and a member's benefit plan, summary plan description or contract, the benefit plan, summary plan description or contract will govern.

Coverage

Non-BRCA (breast cancer) risk assessment testing, (i.e., OncoVue®) as a method of estimating individual patient risk for developing breast cancer is considered experimental, investigational and unproven.

Policy Guidelines

There are no specific CPT codes for non-BRCA risk assessment testing.  Testing has typically been coded using a series of CPT codes describing the individual steps in the testing process. 

Rationale

OncoVue was developed based on an analysis of 117 genetic markers in candidate genes likely to reveal a risk of breast cancer.  In 2007, Ralph et al. published a study on the age-specific relationship of steroid hormone pathway gene polymorphisms with breast cancer risk.    This was a large case-controlled study from six geographic regions of the United States; cases were defined as women with a self-reported diagnosis of breast cancer, whereas the controls had never been diagnosed with any cancer.  The study focused on Caucasian women, age range of 30 years to 69 years.  The primary discovery set consisted of over 5,000 women (1671 breast cancer cases and 3351 cancer-free controls) who were age-matched to within one year.  The model was then validated in two independent populations consisting of Caucasian women (400 cases and 793 controls) and African American women (164 cases and 417 controls).  The study authors admit further studies are needed to determine the relevance of age-specific genetic associations in breast cancer and in other cancers.  The conclusion was, “The identification of age-specific genetic associations may have profound implications for future etiologic studies of BC (breast cancer) and for the use of SNP genotyping to accurately predict the risk of BC in women.”

InterGenetics’ product information notes their OncoVue test limitations.  They state, “The OncoVue test examines 22 SNPs in 19 genes.  There may be other genes or additional variants in these 19 genes that contribute to breast cancer risk that are not a part of the OncoVue test.  Thus, the absence of risk estimated by this test does not guarantee that other breast cancer risk markers are not present in the sample being analyzed.  The OncoVue test does not take the place of BRCA1 and BRCA2 gene testing for women considered at high risk due to strong family history of breast cancer.”

OncoVue has not been approved by the U.S. Food and Drug Administration (FDA).  Currently, FDA approval is not a requirement to market OncoVue; however, InterGenetics filed for future FDA approval under the upcoming new category for laboratory developed testing, known as the In-Vitro Diagnostic Multivariate Index Assays (IVDMIA).  OncoVue is performed in the InterGenetics’ CLIA-certified cytogenetics laboratory.

Summary

The available evidence published in the peer-reviewed literature is inadequate to conclude that OncoVue captures all the gene and variant markers contributing to breast cancer risk.  The limited scientific data suggests that some patients may obtain partial and incomplete breast cancer risk information from only 19 genes.  Therefore, utilization of OncoVue as a method of testing for sporadic inherited breast cancer is considered experimental, investigational and unproven.

2011 Update

A search of peer reviewed literature through August 2010 was completed, with the following results, for the OncoVue® breast cancer risk test.

The OncoVue® test was developed by evaluating samples from a large case-control study for 117 common, functional polymorphisms, mostly SNPs, in candidate genes likely to influence breast carcinogenesis.  A model using 22 SNPs in 19 genes together with Gail Model (personal and family history characteristics) risk factors was subsequently identified by multiple linear regression analysis.  OncoVue improved individual sample risk estimation, compared to the Gail Model alone (p<0.0001), by correctly placing more cases and fewer controls at elevated risk.  In the same study, the model was validated on an independent sample set with similarly significant results.  This study has only been published in a meeting abstract; no details of the study or its results are available.  Note that the Gail model has been shown to accurately estimate the proportion of women (without a strong family history) who will develop cancer in large groups but is a poor discriminator of risk among individuals. 

Using the same case-control validation data, OncoVue was also compared to risk estimation determined by seven SNPs reported in other genome-wide association studies (GWAS); the GWAS risk scores were unable to stratify individuals by risk for breast cancer, whereas OncoVue significantly stratified patients by risk.  This study has not been published.  Independently, SNPs derived from GWAS are known to result in only low-level estimates of risk at best; in one example, a 14-SNP polygenic risk score yielded an odds ratio of only 1.3 for estrogen receptor (ER)-positive breast cancer and 1.05 for ER-negative breast cancer.

An additional analysis of the same case-control data was reported at the 2010 San Antonio Breast Cancer Symposium.  The OncoVue risk score was calculated in the same discovery (4768 Caucasian women,1592 cases and 3176 controls) and independent validation sets (1137 Caucasian women,376 cases and 761 controls; 494 African American women,149 cases and 345 controls).  For both OncoVue and Gail Model risk scores, positive likelihood ratios (proportion of patients with breast cancer with an elevated risk estimate [≥20%] divided by the proportion of disease-free individuals with an elevated risk estimate) were calculated.  OncoVue exhibited a 1.6- to 1.8-fold improvement compared to the Gail Model in more accurately assigning elevated risk estimates to breast cancer cases rather than controls.  At higher risk thresholds, the fold improvement increased and exceeded 2.5 in some sample sets.

Does OncoVue testing improve the accuracy of breast cancer risk prediction beyond standard risk prediction methods?

The performance of OncoVue has also been studied in women from the Marin County, California, breast cancer adolescent risk factor study.  A retrospective case-control study was developed within the cohort, and samples were evaluated with OncoVue testing.  OncoVue assigned high-risk status to 19 more women who had had breast cancer (of 169 cases) than did the Gail model, which represented an approximately 50% improvement.  OncoVue was also more effective at stratifying risk in the high-risk Marin County population than the seven SNPs reported in the other GWAS.  These studies have not yet been published in a peer-reviewed journal.

Several supportive studies are listed on the InterGenetics, Inc. website; most are meeting abstracts.  These address conceptual aspects of the OncoVue test but do not appear to report data using the final OncoVue test configuration.  One fully published study characterizes SNPs that exhibit breast cancer risk associations that vary with age.  This study stratified breast cancer cases and normal controls into three age groups, then determined breast cancer risk for SNP homozygotes and heterozygotes for each of 18 candidate SNPs within each age group.  Of these, five SNP variants had statistically significant odds ratios for at least one age group.  In a separate validation sample, only one had a statistically significant odds ratio but not in a pattern similar to that of the discovery set.  The other four SNPs, although not significant, were judged to have patterns of results similar to that of the discovery set and were investigated further by a sliding ten-year window strategy; the results, of which the authors suggest, clarify age-specific breast cancer risk associations.  The authors note the need for additional validation in other populations and non-white ethnicities.

Additional published studies evaluated seven to 17 common, candidate SNPs in a large number of breast cancer cases and normal controls to determine whether breast cancer risk associations with various SNP combinations were different than predicted by a model of independent gene action.  Aston et al. concluded that SNP combinations were significantly associated with wide variation in breast cancer risk that for many combinations there is significant deviation from a model of independent action, and that compared to individual SNPs these combinations can stratify risk over a broader range.  Mealiffe et al. concluded that combining seven validated SNPs with the Gail Model resulted in a modest improvement in classification of breast cancer risks, but area under the curve only increased from 0.557 to 0.594 (0.50 represents no discrimination, 1.0 perfect discrimination).  Zheng et al. found that eight SNPs, combined with other clinical predictors, were significantly associated with breast cancer risk; the full model gave an area under the curve of 0.63.  Campa et al. evaluated 17 SNP breast cancer susceptibility loci for any interaction with established risk factors for   breast cancer but found no evidence that the SNPs modified the associations between established risk factors and breast cancer.  The results of these studies support the concept of OncoVue but do not represent direct evidence of its clinical validity or utility.

Do results of OncoVue testing lead to changes in management that result in health outcome improvements?

The medical management implications of this test are unclear.  The Gail Model was originally designed for use in clinical trials, not for individual patient care and management.  Thus using the Gail Model as a baseline for comparison may not be sufficiently informative.  In addition, no evidence of improved outcomes as a result of management changes in OncoVue-identified high-risk patients has been presented or published.  The OncoVue sample report makes no recommendations.  The InterGenetics, Inc. website makes this statement: “A Moderate to High Risk result gives a woman several options: More comprehensive surveillance for breast cancer with mammograms, ultrasound and now Magnetic Resonance Imaging-MRI.  Earlier detection means better long term survival.  Breast cancer prevention drugs like Tamoxifen can actually reduce breast cancer in high risk women.”

Ongoing Clinical Trials

A prospective cohort trial is underway by University of Kansas in collaboration with InterGenetics (NCT00329017).  The purpose of the trial is to examine the potential associations between SNPs and cytomorphology in breast tissue specimens from postmenopausal women.  The trial is no longer recruiting and the results of this study are pending.

Summary

Given the lack of published detail regarding the OncoVue test validation, supportive data, and management implications, there is insufficient evidence to determine if the test provides clinical utility, i.e., whether using breast cancer risk estimates from OncoVue in asymptomatic individuals changes management decisions and improves patient outcomes.  Thus, OncoVue is considered experimental, investigational and unproven.

Coding

Disclaimer for coding information on Medical Policies       

Procedure and diagnosis codes on Medical Policy documents are included only as a general reference tool for each policy.  They may not be all-inclusive.          

The presence or absence of procedure, service, supply, device or diagnosis codes in a Medical Policy document has no relevance for determination of benefit coverage for members or reimbursement for providers. Only the written coverage position in a medical policy should be used for such determinations.           

Benefit coverage determinations based on written Medical Policy coverage positions must include review of the member’s benefit contract or Summary Plan Description (SPD) for defined coverage vs. non-coverage, benefit exclusions, and benefit limitations such as dollar or duration caps. 

ICD-9 Codes

174.0, 174.1, 174.2, 174.3, 174.4, 174.5, 174.6, 174.8, 174.9, 175.0, 175.9, 233.0, 238.3, 239.3, V10.3, V16.3, V82.71, V82.79, V84.01, V84.09

ICD-10 Codes

C50.011, C50.012, C50.019, C50.111, C50.112, C50.119, C50.211, C50.212, C50.219, C50.311, C50.312, C50.319, C50.411, C50.412, C50.419, C50.511, C50.512, C50.519, C50.611, C50.612, C50.619, C50.811, C50.812, C50.819, C50.911, C50.912, C50.919, C50.021, C50.022, C50.029, C50.121, C50.122, C50.129, C50.221, C50.222, C50.229, C50.321, C50.322, C50.329, C50.421, C50.422, C50.429, C50.521, C50.522, C50.529, C50.621, C50.622, C50.629, C50.821, C50.822, C50.829, C50.921, C50.922, C50.929, D05.00, D05.01, D05.02, D05.10, D05.11, D05.12, D05.80, D05.81, D05.82, D05.90, D05.91, D05.92, D48.60, D48.61, D48.62, D49.3, Z12.39, Z13.71, Z13.79, Z13.89, Z15.01, Z80.3, Z85.3

Procedural Codes: [Deleted 1/2013: 83891, 83892, 83894, 83898, 83900, 83901, 83909, 83912, 83914]
References
  1. Aston, C.E., Ralph, D.A., et al.  Oliogogenic combinations associated with breast cancer risk in women under 53 years of age.  Human Genetics (2005) 116:208-21.
  2. Brown, P.  Risk assessment: controversies and management of moderate- to high-risk individuals.  Breast Journal (2005 March-April) 11 Supplement 1:S11-9.
  3. Onay, V.U., Briollais, L., et al.  SNP-SNP interactions in breast cancer susceptibility.  BMC Cancer (2006) 6:114.
  4. Evans, D.G., and A. Howell.  Breast cancer risk-assessment models.  Breast Cancer Research (2007) 9(5) :213.
  5. Ralph, D.A., Zhoa, L.P., et al.  Age-specific association of steroid hormone pathway gene polymorphisms with breast cancer risk.  Cancer (2007 May 15) 109(10):1940-8.
  6. SABCS – 30th Annual San Antonio Breast Cancer Symposium: Jupe, E.R., Ralph, D.A., et al.  The OncoVue model for predicting breast cancer risk, Abstract Number 4038 (2007 December 13-16).  Available at http://www.intergenetics.com (accessed on 2011 March 8).
  7. Driver, K.E., Song, H., et al.  Association of single-nucleotide polymorphisms in the cell cycle genes with breast cancer in the British population.  Carcinogenesis (2008 February) 29(2):333-41.
  8. OncoVue Breast Cancer Risk Assessment Test Product Specifications – Product Information.  Oklahoma City, Oklahoma: InterGenetics (2008 March).
  9. SABCS – 31st Annual San Antonio Breast Cancer Symposium: Dalessandri, K.M., Miike, R., et al.  Validation of OncoVue, a new individualized breast cancer risk estimator in the Marin County, California adolescent risk study, Abstract Number 502 (2008 December 12).  Available at http://www.intergenetics.com (accessed on 2011 March 8).
  10. Mavaddat, N., Dunning, A.M., et al.  Common genetic variation in candidate genes and susceptibility to subtypes of breast cancer.  Cancer Epidemiology, Biomarkers and Prevention (2009 January) 18(1):255-9.
  11. Cummings, S.R., Tice, J.A., et al.  Prevention of breast cancer in postmenopausal women: approaches to estimating and reducing risk.  Journal of the National Cancer Institute (2009 March 18) 101(6):384-98.
  12. Mealiffe, M.E., Stokowski, R.P., et al.  Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information.  (2010 November 3) 102 (21):1618-27.
  13. SABCS – 32nd Annual San Antonio Breast Cancer Symposium: Dalessandri, K.M., Miike, R., et al.  Breast cancer risk assessment in the high risk Marin County population using OncoVue compared to SNPs from Genome Wide Association Studies, Abstract Number 3057 (2009 December 11).  Available at http://www.intergenetics.com (accessed on 2011 March 8).
  14. SABCS – 32nd Annual San Antonio Breast Cancer Symposium: Jupe, E.R., Pugh, T.W., et al.  Breast cancer risk estimation using the OncoVue model compared to combined GWAS single nucleotide polymorphisms, Abstract Number 3177 (2009 December 11).  Available at http://www.intergenetics.com (accessed on 2011 March 8).
  15. ClinicalTrials.gov – Protocol for Postmenopausal Women at Increased Risk of Developing Breast Cancer (NCT00329017).  (2010 March 22).  Available at www.clinicaltrials.gov (accessed on 2011 September 2).
  16. Zheng, W., Wen, W., et al.  Genetic and clinical predictors for breast cancer risk assessment and stratification among Chinese women.  Journal of the National Cancer Institute (2010 July 7) 102(13):972-81.
  17. Reeves, G.K., Travis, R.C., et al.  Incidence of breast cancer and its subtypes in relation to individual and multiple low-penetrance genetic susceptibility loci.  Journal of the American Medical Association (2010 July 28) 304(4):426-34.
  18. SABCS – 33th Annual San Antonio Breast Cancer Symposium: Jupe, E.R., Pugh, T.W., et al.  Accurate identification of women at high risk breast cancer using OncoVue.  Poster P6-09-04 (2010 December 12).  Available at http://www.posters2view.com (accessed on 2011 September 1).
  19. Campa, D., Kaaks, R., et al.  Interactions between genetic variants and breast cancer risk factors in the breast and prostate cancer cohort consortium.  Journal of the National Cancer Institute (2011 August 17) 103(16):1252-63.
  20. Non-BRCA Breast Cancer Risk Assessment (OncoVue).  Chicago, Illinois: Blue Cross Blue Shield Association Medical Policy Reference Manual (2011 September) Medicine 2.04.57.
History
December 2011  Policy reviewed with literature search; references 5,9,11-13 added. No change to policy statement. 
October 2012 Policy reviewed with literature search; no new references added. No change to policy statement.
October 2013 Policy formatting and language revised.  Policy statement unchanged.  Title changed from "Genetic Testing: Non-BRCA Breast Cancer Risk Assessment (OncoVue)" to "Non-BRCA (Breast Cancer) Risk Assessment".
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Non-BRCA (Breast Cancer) Risk Assessment