Researchers at the University of Michigan Health System in Ann Arbor have created a risk prediction model designed to identify which hepatitis C patients are most in need of new drug therapies.
The risk prediction model uses routine lab values and machine-learning methods to determine the outlook of a patient's health after being diagnosed with HCV.
"Offering immediate treatment to patients identified as high risk for poor health outcomes would allow these patients to benefit from highly effective treatments as other patients continue to be monitored and their risk assessment updated at each clinic visit," says lead study author Monica Konerman, MD, MSc, a fellow in gastroenterology at the University of Michigan Health System.
The model was published in the June issue of the journal Hepatology.