Making the Case for Routine Genetic Testing

Several life-threatening diseases have a major genetic component but gene testing for these conditions remains out of reach for many patients because current clinical guidelines don’t recommend the test. Why not?

By John Halamka, M.D., Diercks President, Mayo Clinic Platform and Paul Cerrato, MA, senior research analyst and communications specialist, Mayo Clinic Platform

1 out of every 200-250 people across the globe has a genetic defect that causes severely elevated serum cholesterol levels, a condition called familial hypercholesterolemia (FH). 1 in 200-500 women has the gene that greatly increases the odds of breast and ovarian cancer, and 1 in 280 people in the United State carries the gene that predisposes them to an inherited form of colon cancer—Lynch syndrome.  Unfortunately, most of these people don’t know they are at risk, and most will probably never be tested for these life-threatening conditions. The traditional argument has been that conducting the genetic testing required to pinpoint any of these diseases is too expensive to justify. In effect, it’s not cost effective. How sound is that argument?

A recent investigation from Mayo Clinic has found that almost 90% of patients with FH would have been missed if clinicians had adhered to standard genetic testing guidelines. They became aware of their genetic predisposition because they had enrolled in a Mayo Clinic population-based study. The study revealed that about one in five had already developed coronary artery disease. In routine medical practice, many patients with FH are overlooked because they don’t have the telltale signs described in the current guidelines used to detect the disorder. They include a personal or family history of premature coronary artery disease, elevated levels of LDL cholesterol, and specific physical traits, including arcus cornealis and tendon xanthomata—unique signs in a patient’s cornea and fatty lumps often appearing on elbows and knuckles.

To determine how common FH is in the United States, Mayo Clinic used data from the Tapestry study, which included patients from three campuses: Rochester, MN, Phoenix, AZ, and Jacksonville, FL. The researchers performed exome sequencing, which measures the DNA in the protein-coding sections of a person’s genome. Among over 84,000 participants, 447 were identified as having the gene for FH, about 0.5% of the population. Critics may question the cost effectiveness of a procedure that only finds the disease in less than 1% of a population. Samadder et al point out, however, that: “Cost-effectiveness analyses have been completed and found that population genomic screening for FH is cost-effective in younger populations as the cost of exome (or targeted gene panel) based sequencing drops below the low hundreds of dollars.”

One cost effectiveness analysis that compared standard clinical guidelines for detecting an elevated risk of inherited breast cancer to population-based genetic testing found that screening all women between 30 and 35 was more cost effective than relying on genetic testing of women who already had a family history of the disease. Guo et al retrospectively reviewed 1 million patient records, and found “ICER of $55,548 per QALY …” for universal gene sequencing. The incremental cost-effectiveness ratio (ICER) is used to determine the difference in health outcomes between the two groups. It’s derived by dividing the difference in costs between the standard protocol—namely only doing genetic testing in women who have family history—and the costs of doing the genetic test on all women. The result is the quality-adjusted life years (QALY); it combines the quantity and quality of life. QALY of $55, 548 means it would cost an additional $55,000+ to implement population-based screening for each extra year of good health that the procedure offered. In the United States, a protocol that comes in at less than $120,000 QALY is considered cost effective.

Similarly, a cost effectiveness study looked at gene sequencing for Lynch syndrome, hereditary breast and ovarian cancer, and FH amongst adults between 20 and 60. The researchers found that screening 100,000 30-year-olds would have led to 101 fewer cancer case and 15 fewer cardiovascular events. Guzauskas et al concluded that there was: “an increase of 495 quality-adjusted life-years (QALYs) … at an incremental cost of $33.9 million. The incremental cost-effectiveness ratio was $68,600 per QALY gained."

In light of this evidence, why isn’t gene sequencing being routinely done in age groups that see the most benefit? Third party payers have raised several issues about the cost effectiveness of such testing. They question the strength of modeling studies and early real-world data that support population-based genetic testing and want larger-scale, long-term studies that confirm these benefits in diverse populations. They are also concerned about downstream costs, including the possibility of unnecessary follow-up procedures or overdiagnosis. In addition, managers change insurance companies every four years because of job turnover. That means that an insurance company that funds a genetic test may not appreciate the benefit from the cost avoidance of future treatment. It's a unique misalignment of incentives in the US healthcare system.

There is also a phenomenon that health economists call discounting of future care, which they apply when doing cost effectiveness analyses. It is based on the belief that society prefers benefits and costs to occur sooner than later. Several healthcare organizations recommend a 3% annual discount rate for future costs and health effects.

Finally, one of the most important issues is the cost of an individual genetic test, which can vary widely depending on the setting. In the US, population-wide FH genomic screening in 20-year-olds has been shown to be cost effective when the test costs $100-$200. Similarly, international models suggest that population genomic screening for FH in young adults is cost-effective if per-test costs are ≤ Australian $250 (about US $170).

The research to date is reason to be hopeful.  The cost of genomic testing has been steadily decreasing over the years and will likely continue to drop with advances in lab technology. The faster these numbers decline, the sooner at-risk patients will reap the benefits.