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EGAPP Finds No Benefit to Marketed Genetic Tests for Cardiovascular Disease Risk

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By Turna Ray

After assessing the available information on gene variants associated with cardiovascular disease risk that are being sold as prognostic tests, an independent working group at the Centers for Disease Control and Prevention found "insufficient evidence" that testing for these markers in the general population will alter CVD risk assessments.

The "magnitude of net health benefit" from use of eight marketed tests analyzing 58 variants and 29 genes is "negligible," the Evaluation of Genomic Applications in Practice and Prevention Working Group wrote in a recommendation statement published Oct. 29 in Genetics in Medicine. "The EWG discourages clinical use unless further evidence supports improved clinical outcomes," the working group recommended.

EGAPP, formed by the Centers for Disease Control and Prevention's Office of Public Health Genomics, previously conducted evidence reviews of tests for Lynch syndrome for use in colorectal cancer cases, the use of tumor gene expression profiles for certain breast cancer patients, and the routine use of UGT1A1 genotyping in patients with metastatic colorectal cancer. After those reviews, the EWG recommended genetic testing for Lynch syndrome for newly diagnosed colorectal cancer patients, but the group did not find enough evidence to issue a favorable recommendation for gene expression testing for breast cancer or UGT1A1 genotyping in metastatic colorectal cancer patients (PGx Reporter 01/21/09).

The working group evaluated the eight genetic tests in terms of their analytic validity, clinical validity, and clinical utility. The EGAPP's recommendations on prognostic tests to gauge risk of CVD, specifically heart disease and stroke, apply to the general population without preexisting heart conditions or a family history of CVD.

EGAPP reviewers defined coronary heart disease as coronary artery disease, ischemic heart disease, and myocardial infarction. Those with stroke could have had intracerebral and subarachnoid hemorrhage, ischemic stroke, and other diseases.

Seven companies marketing the eight tests were identified by EGAPP in February 2008. Some of the tests were marketed directly to consumers and the work group noted that some of these services issued reports to customers detailing "diet and lifestyle recommendations personalized to the individual tested." The other tests reviewed by EGAPP were offered through a physician, and required that a detailed patient medical history and family history be collected.

The EGAPP reviewers looked at CVD prognostic gene tests marketed by Decode Genetics, Genelex, Sciona, Genovations, Genosolutions, Integrative Genomics, and Interleukin Genetics. EGAPP's investigation of these testing services found that Decode makes clinical claims on its test, while the other six firms suggest making lifestyle changes based on genomic test results.

Out of the 58 variants and 29 genes that the reviewers assessed (see table below), they found evidence that variants in two genes — F2 and F5 — have "encouraging" analytical validity and said that 9p21 SNP markers linked to heart disease had the most "credible" clinical validity data. The majority of markers, however, showed limited analytical and clinical validity data, and virtually no clinical utility data.

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EGAPP highlighted the need for large studies that seek to reduce bias and compare the usefulness of genomic markers to traditional risk factors, such as those used in the Framingham Risk Scores.

"The traditional modifiable CVD risk factors, such as those used in the Framingham Risk Scores, have an advantage in clinical screening and risk assessment strategies because they measure the actual targets for therapy (e.g., lipid levels and blood pressure)," the work group points out in its report. "To be useful, genomic testing should provide demonstrable improvement on the predictive value of TRFs."

Questions about the latest EGAPP recommendations to CDC's Office of Public Health Genomics were not answered.

Analytic Validity

EGAPP found reliable analytic validity for two genes, F2 and F5, which are analyzed by Decode Genetics and Interleukin Genetics. According to the reviewers, the in-house data for analytical validity from these two companies were "encouraging but graded as Level 4 evidence." Level 1 evidence is considered the strongest.

Decode's laboratory in Reykjavik, Iceland, is certified under the Centers for Medicare & Medicaid Services' Clinical Laboratory Improvement Amendments and accredited by the College of American Pathologists. The company's representatives were able to provide EGAPP reviewers with details about the test platform, a comparison of test results compared to bidirectional sequencing, and replication data. Decode, whose CVD test is based on Nanogen's Centaurus Assay, also used blinded samples for internal quality checks.

Interleukin Genetics' laboratory is CLIA-certified in four states, according to EGAPP's evaluation. The company's representatives provided EGAPP reviewers information about the platform, test methodology, test results compared to commercial cell lines, short-term replications, and failure rates. Interleukin's Inherent Health Heart Health test operates on a tagged fluorescent assay based on single-base extension technology; the test uses Beckman Coulter's GenomeLab SNPStream genotyping system to identify SNPs of interest.

Meanwhile, the five other companies did not respond to EGAPP's efforts to gather information about their tests. As such, the reviewers found "insufficient evidence" on basic data about the other six tests, such as the specific variant being tested for in the gene and published literature on the testing platforms. Furthermore, EGAPP reviewers reported that external proficiency testing was not available for any of the genes other than F5 and F2.

These spotty findings led EGAPP to conclude that "there is inadequate evidence that the genomic profiling tests identified in this report have analytic validity, but platforms exist that could allow at least satisfactory sensitivity and specificity."

Clinical Validity

In investigating the clinical validity of the various CVD risk tests, EGAPP considered the odds ratios to evaluate how accurately the gene variants predict the likelihood of heart disease and stroke. Additionally, EGAPP created a "best-case scenario" model for the combination of markers with the strongest evidence for both of these disease settings.

Although the clinical validity data varied "widely" among the 58 gene variants, the evaluation revealed the "most credible" clinical validity evidence on 9p21 SNP markers for heart disease. "This association is highly reproducible, unlikely to be influenced by major biases, and has the largest effect size documented for any variant with at least moderate credibility (OR = 1.56)," the work group wrote in its published recommendations.

Meanwhile, the other combined associations for heart disease have "some credible evidence," but were weighed down by evidence gaps. For example, according to EGAPP, several variants are based on small studies that could be hampered by biases and "weak credibility."

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EGAPP explained that a perfect diagnostic would have an area under the curve (AUC), of 100 percent, while a value of 50 percent AUC would describe a test that provides "no useful information." Based on these parameters, the reviewers calculated an AUC of 64.7 percent and a disease detection rate of 24 percent for 24 genes and/or variants associated with heart disease.

"This combination of genomic markers would not be considered a useful standalone test for heart disease risk stratification," EWG concluded.

For stroke, the "data … are less convincing," the EWG wrote. Modeling the cumulative odds ratio for 13 gene variants linked to stroke, the reviewers calculated an AUC of 55.2 percent and a disease detection rate of 14 percent.

Additionally, reviewers did not find sufficient evidence on whether combining genomic data with traditional risk factors improves prediction of heart disease. In their investigations, EGAPP only found literature discussing the ability of 9p21 SNPs to improve outcomes over traditional risk factors.

Using the net reclassification index, reviewers measured how much heart disease risk prediction was improved with the use of 9p21 over traditional risk assessment methods. After this calculation, EGAPP reported that testing for 9p21 markers achieved scores ranging from "a nonsignificant decrease in prediction" to "a clinically unimportant but statistically significant improvement in risk prediction."

The totality of the data gathered on the clinical validity of the gene variants of interest led EGAPP to conclude that there is "convincing evidence" that 9p21 variants are associated with heart disease but "that the improvement in prediction when added to traditional risk factors is negligible."

Twenty-four other gene variants had "adequate" clinical validity information, while 34 had "inadequate information," the work group found.

"Modeling showed that combining the 24 most credible markers for heart disease would not provide a clinically useful standalone test," the work group concluded. "Modeling the 13 most credible markers for stroke is even less predictive."

Clinical Utility

The evidence supporting the 58 variants' clinical utility — defined as the benefits and harms associated with using genomic tests to gauge people's CVD risk — were less than satisfactory, according to EGAPP.

The group found no published studies evaluating the clinical utility of the markers. There was "preliminary evidence" suggesting that heart disease risk scores "may translate into modest benefits (e.g., increased drug treatment and short-term blood pressure reduction), without clinical harms," the group noted, adding that higher-quality data on long-term outcomes and replication of findings in different cohorts is necessary.

The reviewers found some studies looking at the clinical utility of genomic testing conducted in different disease states, such as lung cancer and diabetes. In these settings, the data suggested that genomic testing could impact behavior in the short term.

Based on the lack of data available, the reviewers concluded ultimately that "there is inadequate evidence of clinical utility for genomic profiles."

EGAPP did not review the cost-effectiveness of prognostic genetic testing for CVD.

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