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William J. Gradishar, MD, FACP, FASCO


Cost-Effectiveness of Breast Cancer Therapy: Learning From New Utility Values

By: Amanda E. Ruffino, BA
Posted: Tuesday, June 18, 2024

In breast cancer research, the accuracy of cost-effectiveness analyses relies on quality-adjusted life year (QALY) calculations, which in turn depend on assumptions about utility values. Given that existing utility assumptions tend to be inconsistent, Nicolien T. van Ravesteyn, PhD, of Erasmus MC, University Medical Center, Rotterdam, the Netherlands, and colleagues aimed to provide new data-based utility values for these patients. By analyzing the EQ-5D-5L questionnaires of 464 female patients with breast cancer, from diagnosis to treatment completion, the investigators calculated average utilities based on age and treatment type, revealing a decrease in utilities at diagnosis and 6 months after surgery, followed by a gradual increase toward normative levels by 12 months after surgery.

“[Our study] showed that the use of gender- and age-stratified normative utilities and patient-based breast cancer quality-of-life parameters stratified by age and treatment or disease stage are recommended,” the study authors noted.

By using these patient-derived utility values, the investigators conducted cost-effectiveness analyses of 920 breast cancer screening policies, varying in eligible ages and screening intervals, through the MISCAN-Breast microsimulation model. Cost-effectiveness analyses employed a willingness-to-pay threshold of €20,000 ($21,580) and considered different utility sets, including normative, breast cancer treatment, and screening/follow-up utilities. Results indicated that using normative utility values of 1 in cost-effectiveness analyses led to overestimation of QALYs compared with age- and gender-specific averages. However, variations in treatment utilities had minimal impact on QALYs gained.

Furthermore, cost-effectiveness analyses incorporating different screening and follow-up utility sets showed only marginal changes in QALYs gained and the efficiency frontier. Despite these variations, the optimal screening strategy consistently emerged as biennial for ages 40 to 76. The investigators recommended using gender- and age-stratified normative utilities in cost-effectiveness analyses, along with patient-specific breast cancer utilities stratified by age and treatment/disease stage.

By using patient-specific utility values alongside normative benchmarks, cost-effectiveness analyses may better capture the nuanced impacts of breast cancer treatments and screening policies, ultimately informing more accurate and tailored health-care decision-making, the authors proposed.

Disclosure: For full disclosures of the study authors, visit

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