DOI: 10.1002/ijc.34899 ISSN: 0020-7136

Health utility values of breast cancer treatments and the impact of varying quality of life assumptions on cost‐effectiveness

Lindy M. Kregting, Noëlle J. M. C. Vrancken Peeters, Marloes E. Clarijs, Linetta B. Koppert, Ida J. Korfage, Nicolien T. van Ravesteyn
  • Cancer Research
  • Oncology

Abstract

In breast cancer research, utility assumptions are outdated and inconsistent which may affect the results of quality adjusted life year (QALY) calculations and thereby cost‐effectiveness analyses (CEAs). Four hundred sixty four female patients with breast cancer treated at Erasmus MC, the Netherlands, completed EQ‐5D‐5L questionnaires from diagnosis throughout their treatment. Average utilities were calculated stratified by age and treatment. These utilities were applied in CEAs analysing 920 breast cancer screening policies differing in eligible ages and screening interval simulated by the MISCAN‐Breast microsimulation model, using a willingness‐to‐pay threshold of €20,000. The CEAs included varying sets on normative, breast cancer treatment and screening and follow‐up utilities. Efficiency frontiers were compared to assess the impact of the utility sets. The calculated average patient utilities were reduced at breast cancer diagnosis and 6 months after surgery and increased toward normative utilities 12 months after surgery. When using normative utility values of 1 in CEAs, QALYs were overestimated compared to using average gender and age‐specific values. Only small differences in QALYs gained were seen when varying treatment utilities in CEAs. The CEAs varying screening and follow‐up utilities showed only small changes in QALYs gained and the efficiency frontier. Throughout all variations in utility sets, the optimal strategy remained robust; biennial for ages 40–76 years and occasionally biennial 40–74 years. In sum, we recommend to use gender and age stratified normative utilities in CEAs, and patient‐based breast cancer utilities stratified by age and treatment or disease stage. Furthermore, despite varying utilities, the optimal screening scenario seems very robust.

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