Jeffrey S. Buguliskis Ph.D. Technical Editor Genetic Engineering & Biotechnology News

Evaluating the Risk-to-Benefit Ratio of Genomic Health Advances

The utilization of genomic information for patients as a part of their overall clinical care, either from a diagnostic or therapeutic decision-making perspective, is the hallmark of genomic medicine. However, one recently added dimension to this field is the effect genomic information can have on policy implementation and health outcomes with respect to the data’s clinical usage. Policy makers often are asked to weigh the benefits and risks of tests and procedures to determine their clinical utility before they are widely adopted for routine medical practice.

Guidelines on the use of genomic medicine—most specifically genetic testing—within clinical practices were framed almost 20 years ago by the U.S. Task Force on Genetic Testing, which established the criteria for assessment of the usefulness of various molecular screens, diagnostic assays, or devices. As technology has advanced, we have seen the broadening of the definition for what encompasses clinical utility in areas such as gene expression, epigenetics, and genomic and proteomic data. Information from these sources could help stratify patients into various risk groups, ultimately affecting therapeutic outcomes.

Of all the application areas genomics has affected in precision medicine, clinical diagnostics particularly stands out as having achieved extraordinary progress. More specifically, genetic tests and biomarkers, which are often used in some prognostic manner or for shaping the therapeutic regimen, have been the most scrutinized for their validity and utility to overall patient care.

“Every product needs to prove clinical utility,” declares Harry Glorikian, senior executive, board director, and consultant in the life sciences/healthcare industry. “Does the product/device/test change the clinical management of the patient? A ‘Yes’ is  needed to have a product adopted.”


How to Assess Usefulness

A conundrum that many researchers, manufacturers, and policymakers are increasingly facing is precisely how to determine if a particular genomic technology or test is clinically valid and useful. For example, a biomarker or molecular diagnostic test alone does not have direct influence on health outcomes based on the speed with which it is adopted into the clinical community. Rather, the clinical utility should depend on rapid access to efficacious, therapeutic interventions. However, trying to obtain conditional agreement on the topic from all parties involved is a bit of a juggling act.       

“The big problem is that there is little consensus on how to assess clinical utility,” notes Glorikian. “Basically, the intended use and the intended population will direct risk, use for screening, differential diagnostics, and prognosis—all of which are used to calculate clinical utility.

“Study design is also a crucial part of determining clinical utility,” Glorikian adds “If your study isn’t set up properly, with the right outcomes, patient populations, and controls, it won’t be very helpful.”

This past February the American College of Medical Genetics and Genomics (ACMG), which represents the medical genetics professional community, published a position statement on the clinical utility of genetic and genomic services. In the paper, the ACMG board of directors addressed how they think the clinical community should tackle the determination of usefulness for genetic tests, stating that “we believe that clinical utility must take into account the value a diagnosis can bring to the individual, the family, and society in general.”

The statement went on to say that “ACMG believes that the interests and lives of family members should be an important clinical consideration in the care of patients. The challenge is in balancing the physician’s responsibilities to the patient with the important medical interests of the family.”   

The ACMG’s guidelines take into consideration the greater social implications of genetic clinical usefulness and begin to establish a framework that places less emphasis on personal utility and more on the greater value to the overall medical community—a philosophy that propels the notion that understanding the underlying causes of disease will drive research forward, enhancing society as a whole. In many ways this is revolutionary thinking in an era when personalized medicine has captured the attention of the population. It is not, however, counterintuitive reasoning; the medical community has always sought to serve the needs of the many over the needs of the few.


Evaluating Future Utility

At the speed with which it is now possible to sequence an entire genome, combined with the exponentially reduced cost in comparison to the original human genome project, it is conceivable that in the near future a significant number of patients entering the clinical realm will have had their genome sequenced. Thus, the focus of genetic testing and genomic medicine will shift toward the interpretation of the patient’s genomic data and what consequences that will have for treatment.

Understanding these comprehensive datasets will require developments in bioinformatics, large-scale databases, and computing power that can sift through the terabytes of data generated from even the smallest of sequencing endeavors. Big data solutions will become a primary factor in the clinical utility of genomic screens because the lack of efficient computational power would essentially render the screening process moot. Interestingly, there are a few scientists who believe that if many data analysis issues can be overcome, it’s conceivable that we would reach a point where geneticists could predict and observe every possible genetic variation within the human genome—and possibly far beyond in numerous other species’ genomes.

The current primary focus of genomic medicine is applying the vast number of genetic tests to the appropriate patients. Once properly validated, these techniques could affect short-term critical care by assigning the proper pharmacotherapeutic compounds. Furthermore, genetic tests can have a significant effect on long-term patient care by tracking disease progression and allowing physicians to adjust treatment strategies to appropriately balance patient tolerance with suitable treatment options.   

“If these tests are found to be clinically useful, they have the potential to dramatically change medication prescription, patient management, and patient outcome,” says Glorikian. “In addition to improved patient care, there is potential for genomic medicine to positively impact the cost of healthcare.”

The bond between genomic and personalized health has been forged through the fastidious work and productive collaborations among translational researchers who are actively introducing technology that are shortening the bench-to-bedside transition. While questions still remain about the best way to navigate the murky waters of applying clinical utility to new diagnostic tests, the pace within the field of precision medicine shows few signs of slowing down. The logjam to meet the needs of the affirmed population may soon rest on the shoulders of regulatory officials and policymakers.








































 

This article was originally published in the February 2016 issue of Clinical OMICs. For more content like this and details on how to get a free subscription to this digital publication, go to www.clinicalomics.com.