(RxWiki News) Some people have a mutation in genes that help the DNA repair itself. This is called Lynch Syndrome, a condition that dramatically increases a person's risk of colon and other types of cancer.
People who have Lynch Syndrome (LS) carry mutations in what's known as the DNA mismatch repair genes (MMR). These are the genes that fix the daily assaults on our DNA. An advanced computer model has been developed that can cost-effectively identify individuals with LS and potentially save lives in the process.
"Easier and cheaper way to identify Lynch Syndrome."
Having LS, an inherited condition, can increase an individual's risk of colon, uterine, pancreatic and urologic cancers by as much as 80 percent.
Marc S. Williams, M.D., director of the Clinical Genetics Institute at LDS Hospital, says it's "profoundly important" to identify those who have this genetic mutation so they - and their families - can have more frequent screenings for colon and other cancers.
And while many different tests can be performed in a variety of combinations to identify LS, the best overall approach remains a mystery, according to lead investigator, James Gudgeon, an analyst with the Clinical Genetics Institute. And full genome sequencing can run $4,000 - $6,000 per person.
With all this in mind, Intermountain Healthcare set out to find a way to use existing tests that could screen for colon cancer LS in a cost-efficient manner. The team gathered data from a variety of sources including patient records and published literature.
The group came up with a plan to rule out Lynch Syndrome using two inexpensive tests.
They have screened 272 colon cancer patients, all but 11 of whom carried no abnormal genes. Those who did have suspect genes underwent full genome sequencing.
This testing model and procedure will save thousands of dollars as it alerts patients to be more vigilant in screening. Some patients may choose to undergo treatment before the cancer appears, i.e., women at risk for ovarian cancer having hysterectomies.
Dr. Williams says he believes these types of models could help other systems make more solid screening and treatment decisions for patients, improving patient outcomes and cost efficiencies at the same time.
This study was published in the American Journal of Managed Care.