Novel Oncology Therapies Require Innovative Methods in Oncology Modeling

Innovative methods in oncology modeling are needed to demonstrate the value of many new cancer treatments, including immuno-oncologic therapies.

Health technology assessment (HTA) agencies have long required evidence of long-term survival and lifetime estimates of quality of life before they will approve new treatments. Health economics and outcomes research analysts have relied on standard parametric models to extrapolate overall survival rates from clinical trial data to estimate quality of life.

This traditional approach identifies the statistical models that best fit the available data and then uses these models to predict outcomes over the lifetime. It worked well for traditional cancer treatments, including chemotherapy. However, many new oncology drugs have a different mechanism of action—including the possibility of delayed and prolonged response to treatment and, potentially, cure—which may not be accurately represented by these traditional models.