While risk prediction and personalized therapies are advancing in some areas, there's much work to be done to make such efforts effective, according to an article in BMC Medicine.
Daniel F. Hayes of the University of Michigan Comprehensive Cancer Center advocates for better industry oversight for tumor biomarker tests and the need to know whether a particular biomarker is significant clinically--whether to give or withhold a particular treatment. Few tests have demonstrated both analytical and clinical utility, he says.
Next-generation sequencing--comparing a tumor to a patient's normal DNA--is the next step, though that's still in its infancy.
Electronic medical records will provide the capability to review millions of patients' outcomes and apply lessons from them, he says.
"I hope that such approaches will remain complementary to clinical trials, so that we can generate prospective data from clinical trials but also do much better comparative effectiveness research by having access to huge databases," he writes.
Using genetics in predicting stroke risk is even more in its infancy, according to Hugh S. Markus, professor of stroke medicine at the University of Cambridge. The identified genes contribute only a small amount of risk, so it's difficult to determine how much each contributes to overall risk.
Diabetes management has long been "one-size-fits-all," focused on preventing complications. With an increased number of available drugs, however, a more patient-tailored approach is possible, according to David Leslie, professor of diabetes and autoimmunity at the Blizard Institute, University of London. It will require practitioners, however, to understand more about the condition, the available drugs and the person they're treating.
Eric J. Topol, cardiologist, chief academic officer of Scripps Health and professor of genomics at The Scripps Research Institute, reiterates in the article his belief that mobile devices-- smartphones in particular--can revolutionize healthcare. Despite concerns about the accuracy of mobile apps and data security, he sees mobile devices empowering patients with their own health data.
Though genomic sequencing increasingly can be done faster and less expensively, there's much still to be learned, Topol told FierceHealthIT. Millions will need to have whole genome sequencing done before enough data is available to understand various medical conditions.
Information from these genomes, plus patient and family histories adds to our knowledge about inherited disorders, says Elizabeth McNally, Ph.D., leader of a University of Chicago-based team that recently used a supercomputer to analyze 240 full genomes in two days.
"In this setting, each patient is a big-data problem," she said.
To learn more:
- find the article in BMC Medicine