Data on Utility in Cost-Utility Analyses of Genetic Screen-and-Treat Strategies for Breast and Ovarian Cancer.
Julia Simões Corrêa GalendiVera VennedeyHannah KentenichStephanie StockDirk MüllerPublished in: Cancers (2021)
Genetic screen-and-treat strategies for the risk-reduction of breast cancer (BC) and ovarian cancer (OC) are often evaluated by cost-utility analyses (CUAs). This analysis compares data on health preferences (i.e., utility values) in CUAs of targeted genetic testing for BC and OC. Based on utilities applied in fourteen CUAs, data on utility including related assumptions were extracted for the health states: (i) genetic test, (ii) risk-reducing surgeries, (iii) BC/OC and (iv) post cancer. In addition, information about the sources of utility and the impact on the cost-effectiveness was extracted. Utility for CUAs relied on heterogeneous data and assumptions for all health states. The utility values ranged from 0.68 to 0.97 for risk-reducing surgeries, 0.6 to 0.85 for BC and 0.5 to 0.82 for OC. In two out of nine studies, considering the impact of the test result strongly affected the cost-effectiveness ratio. While in general utilities seem not to affect the cost-utility ratio, in future modeling studies the impact of a positive/negative test on utility should be considered mandatory. Women's health preferences, which may have changed as a result of improved oncologic care and genetic counselling, should be re-evaluated.
Keyphrases
- healthcare
- public health
- mental health
- health information
- electronic health record
- genome wide
- palliative care
- type diabetes
- prostate cancer
- pregnant women
- gene expression
- copy number
- high throughput
- data analysis
- adipose tissue
- skeletal muscle
- risk assessment
- decision making
- cancer therapy
- hepatitis c virus
- hiv infected
- men who have sex with men
- lymph node metastasis
- pain management
- case control
- breast cancer risk
- robot assisted