Photo courtesy of
University Hospital Ulm
Research published in Nature Genetics suggests a knowledge bank
can reveal the optimal treatment for patients with acute
myeloid leukemia (AML), although more research is needed before such
banks can be used in the clinic.
Researchers built a knowledge
bank using data from 1540 AML patients enrolled in clinical
trials in Germany and Austria.
The bank includes information on genetic features, treatment, and outcomes for each patient.
The researchers used this information to develop models that could predict a patient’s likelihood of remission, relapse, and mortality.
The team then validated those results using data from patients in The Cancer Genome Atlas.
The researchers estimate that up to 1 in 3 AML patients would be prescribed a different treatment regimen if physicians used the knowledge bank approach rather than current practice.
“The knowledge bank approach makes far more detailed and accurate predictions about the likely future course of a patient with AML than what we can make in the clinic at the moment,” said study author Peter Campbell, PhD, of the Wellcome Trust Sanger Institute in Hinxton, UK.
“Current guides use a simple set of rules based on only a few genetic findings. For any given patient, using the new tool, we can compare the likely future outcomes under a transplant route versus a standard chemotherapy route. This means that we can make a treatment choice that is personally tailored to the unique features of that particular patient.”
However, the researchers said the knowledge bank approach requires further testing before it can be used to prescribe treatment in AML clinics.
“Our analysis reveals that knowledge banks of up to 10,000 patients would be needed to obtain the precision needed for routine clinical application,” said study author Moritz Gerstung, PhD, of the European Bioinformatics Institute in Hinxton, UK.
“Building knowledge banks is not easy,” added author Hartmut Döhner, MD, of the University of Ulm in Germany. “To get accurate treatment predictions, you need data from thousands of patients and all tumor types.”
“Furthermore, such knowledge banks will need continuous updating as new therapies become approved and available. As genetic testing enters routine clinical practice, there is an opportunity to learn from patients undergoing care in our health systems. Our paper gives the first real evidence that the approach is worthwhile, how it could be used, and what the scale needs to be.”
