Non-BRCA Breast Cancer Risk Assessment (OncoVue)
|Subsection||Last Review Status/Date
Reviewed with Literature search/8:2012
|Original Policy Date
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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.
The OncoVue® Breast Cancer Risk Test (InterGenetics, Inc.) is a proprietary test that evaluates multiple, low-risk single nucleotide polymorphisms (SNPs) associated with breast cancer. The results are incorporated along with personal history measures to determine breast cancer risk at different times during adulthood. The test does not detect known high risk genetic factors such as BRCA mutations (associated with hereditary breast and ovarian cancer, see Policy 2.04.02). 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 members 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 2010, 32 Breast Care Centers, located in 20 states, were listed on the company website.
The OncoVue® Breast Cancer Risk Test is considered investigational as a method of estimating individual patient risk for developing breast cancer.
OncoVue is not offered over the internet or directly to consumers. Patients may self-refer by finding the location of a participating member of the Breast Cancer Risk Testing Network, available on the InterGenetics Web site, and making an appointment.
BRCA genetic testing should be used in those from high-risk families; see policy 2.04.02 for details.
There is no specific code for the OncoVue test. InterGenetics suggests use of the following CPT codes:
83891 Molecular diagnostics; isolation or extraction of highly purified nucleic acid, each nucleic acid type
83894 separation by gel electrophoresis, each nucleic acid preparation
83892x2 enzymatic digestion, each enzyme treatment
83900 amplification, target, multiplex, first 2 nucleic acid sequences
83901x20 amplification, target, multiplex, each additional nucleic acid sequence beyond 2
83909 x 2 separation and identification by high resolution technique, each nucleic acid preparation
83912 interpretation and report
83914x22 Mutation identification by enzymatic ligation or primer extension, single segment…
99090 Analysis of clinical data stored in computers
BlueCard/National Account Issues
The OncoVue® test was developed by evaluating samples from a large case-control study for 117 common, functional polymorphisms, mostly single nucleotide polymorphisms (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. (1) In the same study, the model was validated on an independent sample set with similarly significant results. To date, 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. (2)
Using the same case-control validation data, OncoVue was also compared to risk estimation determined by 7 SNPs reported in other genome-wide association studies (GWAS) (3); 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 ER-positive breast cancer and 1.05 for ER-negative breast cancer. (4)
An additional analysis of the same case-control data was reported at the 2010 San Antonio Breast Cancer Symposium. (5) The OncoVue risk score was calculated in the same discovery (4,768 Caucasian women,1,592 cases and 3,176 controls) and independent validation sets (1,137 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 measures?
The performance of OncoVue was studied in women from the Marin County, CA, 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. (6) OncoVue was also more effective at stratifying risk in the high-risk Marin County population than 7 SNPs reported in other GWAS. (7) 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. (8) This study stratified breast cancer cases and normal controls into 3 age groups, then determined breast cancer risk for SNP homozygotes and heterozygotes for each of 18 candidate SNPs within each age group. Of these, 5 SNP variants had statistically significant odds ratios for at least 1 age group. In a separate validation sample, only 1 had a statistically significant odds ratio but not in a pattern similar to that of the discovery set. The other 4 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 10-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 (9-12) evaluated 7-17 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. (10) 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. (12) concluded that combining 7 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. (11) found that 8 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. (9) 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. (13) 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 regarding patient management. The InterGenetics, Inc. website makes this statement regarding test results: “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, online at: http://www.clinicaltrials.gov/ct2/show/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.
No new information was found related to OncoVue from general or specific author searches in PubMed, from a search of online ClinicalTrials.gov, or from a search of the FDA website. No new abstracts or publications, and no new information on clinical trial NCT00329017 were posted on the InterGenetics website.
There is a lack of published detail regarding the OncoVue® test validation, supportive data, and management implications. The available data suggests that OncoVue may add predictive accuracy to the Gail Model. However, the degree of improved risk prediction may be modest, and the clinical implications are unclear. There is insufficient evidence to determine whether using breast cancer risk estimates from OncoVue in asymptomatic individuals changes management decisions and improves patient outcomes. Therefore, OncoVue testing for breast cancer risk assessment is considered investigational.
Medicare National Coverage
No national coverage determination.
- Jupe ER, Ralph DA, Manjeshwar S et al. The OncoVue model for predicting breast cancer risk. 2007 San Antonio Breast Cancer Symposium, Abstract 4038.
- Cummings SR, Tice JA, Bauer S et al. Prevention of breast cancer in postmenopausal women: approaches to estimating and reducing risk. J Natl Cancer Inst 2009; 101(6):384-98.
- Jupe ER, Pugh TW, Knowlton NS et al. Breast cancer risk estimation using the OncoVue® model compared to combined GWAS single nucleotide polymorphisms. 2009 San Antonio Breast Cancer Symposium, Abstract 3177.
- Reeves GK, Travis RC, Green J et al. Incidence of breast cancer and its subtypes in relation to individual and multiple low-penetrance genetic susceptibility loci. JAMA 2010; 304(4):426-34.
- Jupe E, Pugh T, Knowlton N et al. Accurate Identification of Women at High Risk of Breast Cancer Using OncoVue. 2010 San Antonio Breast Cancer Symposium; Poster P6-09-04.
- Dalessandri KM, Miike R, Wrensch MR. Validation of OncoVue, a new individualized breast cancer risk estimator in the Marin County, California adolescent risk study. 2008 San Antonio Breast Cancer Symposium; Abstract 502.
- Dalessandri KM, Miike R, Wrensch MR. Breast cancer risk assessment in the high risk Marin County population using OncoVue compared to SNPs from genome wide association studies. 2009 San Antonio Breast Cancer Symposium; Abstract 3057.
- Ralph DA, Zhao LP, Aston CE et al. Age-specific association of steroid hormone pathway gene polymorphisms with breast cancer risk. Cancer 2007; 109(10):1940-8.
- Campa D, Kaaks R, Le Marchand L et al. Interactions between genetic variants and breast cancer risk factors in the Breast and Prostate Cancer Cohort Consortium. J Natl Cancer Inst 2011 [E-pub ahead of print].
- Aston CE, Ralph DA, Lalo DP et al. Oligogenic combinations associated with breast cancer risk in women under 53 years of age. Hum Genet 2005; 116(3):208-21.
- Zheng W, Wen W, Gao YT et al. Genetic and clinical predictors for breast cancer risk assessment and stratification among Chinese women. J Natl Cancer Inst 2010; 102(13):972-81.
- Mealiffe ME, Stokowski RP, Rhees BK et al. Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information. J Natl Cancer Inst 2010; 102(21):1618-27.
- Evans DG, Howell A. Breast cancer risk-assessment models. Breast Cancer Res 2007; 9(5):213.
|CPT||No specific code available(See Policy Guidelines)|
|ICD-9 Diagnosis||Investigational for all applicable codes|
|ICD-10-CM (effective 10/1/13)||Investigational for all applicable diagnoses|
|Z12.39||Encounter for other screening for malignant neoplasm of breast|
|Z13.71||Encounter for nonprocreative screening for genetic disease carrier status|
|Z13.79||Encounter for other screening for genetic and chromosomal anomalies|
|ICD-10-PCS (effective 10/1/13)||Not applicable. No ICD procedure codes for laboratory tests.|
|08/13/09||New policy; add to Medicine section||Policy created with literature search
through July 2009; considered investigational
|09/16/10||Replace policy||Policy reviewed with literature search; references 2–4 and 6 added. No change to policy statement|
|9/01/11||Replace policy||Policy reviewed with literature search; references 5,9,11-13 added. No change to policy statement.|
|08/09/12||Replace policy||Policy reviewed with literature search; no new references added. No change to policy statement.|