Depending on the type of cancer a patient has, the rate of genetic testing to determine appropriate treatments today remains low—usually under 50%. And of those tested, only 60% to 75% receive the targeted treatments suggested by their test results.
In a time when molecular diagnostics can provide so much information about an individual patients’ cancer—and with nearly 60% of current drugs in development informed by biomarkers and another 90 targeted cancer therapies already on the market—it’s plain that more needs to be done to encourage both testing and using the test results to tailor cancer care. But these tests have benefit beyond the individual. Aggregating biomarker data and tumor types has broader implications and benefits within the field of oncology ranging from population health and development of prevention and treatment strategies, to opening avenues for communication between patients and physicians for better treatment decisions.
Now, a new opinion piece published in JCO Clinical Oncology penned by Daryl Pritchard, Ph.D., of the Personalized Medicine Coalition (PMC), Clifford Goodman, Ph.D., of the Lewin Group, and Lincoln Nadauld, M.D., Ph.D., of Intermountain Healthcare, advocates for an updated definition of the clinical utility for genetic testing in cancer care to not only increase adoption and utilization of the tests for personalized treatments, but also within the broader context of information that can inform broader research and use of the data for population health.
The call to action is based on a roundtable discussion organized by PMC that counted 18 leaders across different stakeholder groups including researchers, diagnostics developers, clinicians, and patients. As the authors noted in the beginning of their report, “current definitions of clinical utility are inadequate to recognize the wider scope of benefits that accrue from more comprehensive genomic tests, which can develop data sets that inform clinical decision making as well as population health and scientific advancement in novel ways.”
As Pritchard see it, an effort to develop a new definition is meant to build upon those previous definitions but do so in a way that accounts for the current state of technology.
“There have been many efforts to define the clinical utility of genetic testing, but most of these efforts took place largely before the advent of sequencing-based multiplex testing with a focus on one or a few genes,” Pritchard told Inside Precision Medicine. “The most cited definition within published literature was published in 2006. So that definition and many other efforts are outdated since they do not account for advances in genomics, nor the advances in our understanding of driver mutations in cancer made over the past few years.”
The proposed new definition is:
The clinical utility of genomic testing in cancer care is the net benefit to patients with cancer and health systems that are derived from applying information generated by multigene testing to screening, prevention, and treatment strategies that can improve health care outcomes, including through enrollment in clinical trials, facilitate shared decision making, and reduce health care disparities. The utility of genomic profiling depends on its ability to provide information that is used to guide patients more efficiently to safer and more effective prevention and treatment strategies and its ability to improve the practical knowledge base for health system decision making.
Perhaps the most overlooked stakeholder group in the cancer care continuum, though the one most impacted, are the patients themselves. The updated definition and broader testing can be driven by those battling cancer every day.
“Cancer patients with an increased understanding of the utility of personalized medicine will have increasingly open discussions about treatment options and care strategies with their clinicians, thereby driving a patient-centered approach,” said Pritchard. “This patient-centered approach will lead to a greater demand for genetic testing so that patients can participate in clinical decision making based on the best options available. This will lead to improved outcomes in many cases.”
