A Systematic Literature Review of Health Utility Values in Breast Cancer
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Background Health utility values (HUVs) are important inputs to the cost-utility analysis of breast cancer interventions. Purpose Provide a catalog of breast cancer–related published HUVs across different stages of breast cancer and treatment interventions. Data Sources Systematic searches of MEDLINE, MEDLINE In-Process, EMBASE, Web of Science, CINAHL, PsycINFO, EconLit, and Cochrane databases (2005–2017). Study Selection Studies published in English that reported mean or median HUVs using direct or indirect methods of utility elicitation for breast cancer. Data Extraction Independent reviewers extracted data on a preestablished and piloted form; disagreements were resolved through discussion. Data Analysis Mixed-effects meta-regression using restricted maximum likelihood modeling was conducted for intervention type, stage of breast cancer, and typical clinical and treatment trajectory of breast cancer patients to assess the effect of study characteristics (i.e., sample size, utility elicitation method, and respondent type) on HUVs. Data Synthesis Seventy-nine studies were included in the review. Most articles ( n = 52, 66%) derived HUVs using the EQ-5D. Patients with advanced-stage breast cancer (range, 0.08 to 0.82) reported lower HUVs as compared with patients with early-stage breast cancer (range, 0.58 to 0.99). The meta-regression analysis found that undergoing chemotherapy and surgery and radiation, being diagnosed with an advanced stage of breast cancer, and recurrent cancer were associated with lower HUVs. The members of the general public reported lower HUVs as compared with patients. Limitations There was considerable heterogeneity in the study population, health states assessed, and utility elicitation methods. Conclusion This review provides a catalog of published HUVs related to breast cancer. The substantial heterogeneity in the health utility studies makes it challenging for researchers to choose which HUVs to use in cost-utility analyses for breast cancer interventions.
