UVA shares algorithm to streamline cancer treatment decisions

Charlottesville, Va.-based UVA Health Cancer Center researchers developed an algorithm designed to predict which patients would benefit from kinase inhibitor cancer drugs.

Kinase inhibitors are the most common cancer drugs approved by the FDA and can have profound effects on the right types of cancers, according to an Oct. 27 news release from the health system. However, identifying who would benefit historically has been a long and complicated process.

UVA's algorithm can predict key information based on other available data, creating a "KSTAR score." Physicians can use this score to determine which patients will respond to kinase inhibitors, the release said.

"We are really excited about this algorithm, which performs better than existing approaches with fewer requirements and assumptions — making it more applicable to understanding a cancer state from a single snapshot of the tumor," researcher Kristen Naegle, PhD, of UVA's biomedical engineering department, said in the release. "Combining this approach with existing biomarkers for cancer diagnosis may help us to better tailor therapies, design new combination therapies, anticipate response to treatment and design better clinical trials."

The algorithm can be found here.

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