Utility-Based Dose Selection for Stereotactic Body Radiation Therapy in Hepatocellular Carcinoma.

PURPOSE: Stereotactic body radiation therapy (SBRT) planning for hepatocellular carcinoma (HCC) typically prescribes the maximum dose associated with an acceptable risk of toxicity, relying on implicit trade-offs between efficacy and toxicity. To make this trade-off quantitative, we developed a utility-based approach to dose selection for SBRT in HCC and studied the expected effects on clinical outcomes.

METHODS AND MATERIALS: Using a multi-institutional cohort of SBRT-treated patients, we developed predictive models for local progression, competing mortality, and liver toxicity, defined as an increase of 0.5 or more points in albumin-bilirubin score within 6 months. Individualized risks of local progression and toxicity were integrated using a utility framework with a quantitative efficacy/toxicity trade-off. We then performed a simulation comparing predicted clinical outcomes and overall utility between 2 scenarios: if patients in our cohort had been prescribed SBRT according to Radiation Therapy Oncology Group 1112 ("standard dosing"), versus with our proposed utility-based dose selection.

RESULTS

Our cohort included 309 patients (75% Child-Pugh A pretreatment liver function and 24% Child-Pugh B). The median tumor prescription dose in BED10 was 79 Gy10 and the total number of fractions ranged from 2 to 6. The estimated optimal prescription dose under utility-based dose selection varied widely with baseline liver function, with an optimal tumor BED10 of 112 Gy for a patient with Child-Pugh A cirrhosis to 26 Gy for a patient with Child-Pugh C cirrhosis. In the simulation study, the magnitude of utility gains with our approach compared with standard dosing depended on the relative weighting of toxicity and tumor control utilities.

CONCLUSIONS

We describe a novel approach to SBRT radiation treatment planning and dose selection for HCC that combines individualized prediction of efficacy, toxicity, and competing mortality with explicit calculation of the efficacy-toxicity trade-off using an expected utility framework. This approach holds promise to personalize SBRT treatment planning.