Health-Related Quality of Life and Health Utilities in Metastatic Castrate-Resistant Prostate Cancer: A Survey Capturing Experiences from a Diverse Sample of UK Patients

Background: The collection of preference-based health outcomes data (or utility values) is required to support cost-effectiveness analyses. Objective: This study aimed to collect health-related quality of life (HRQOL) data in men with metastatic castration-resistant prostate cancer (CRPC) stratified by disease states. Methods: Men with metastatic CRPC were recruited via UK patient associations, patient panels, and specialist recruiters and classified into four subgroups reflecting disease state: asymptomatic/mildly symptomatic before chemotherapy, symptomatic before chemotherapy, receiving chemotherapy, and postchemotherapy. HRQOL data (including five-level EuroQol five-dimensional questionnaire [EQ-5D-5L] European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire [EORTC QLQ-C30], and 25-item prostate cancer-specific questionnaire module designed to supplement the EORTC QLQ-C30) along with background and medical history data were collected via an online survey. The EQ-5D-5L and the EORTC-8D (EORTC-8D is an 8 dimensional utility index scored from QLQ-C30 data) were both used to estimate utilities. Results: Data were collected from a total sample of 163 men with metastatic CRPC. Utility values elicited by the EQ-5D-5L ranged from 0.830 for the asymptomatic/mildly symptomatic before chemotherapy disease state (95% confidence interval [CI] 0.795-0.865) to 0.625 for the symptomatic before chemotherapy disease state (95% CI 0.577-0.673). EORTC-8D utilities ranged from 0.856 (95% CI 0.831-0.882) to 0.697 (95% CI 0.664-0.731) for the same disease/treatment states. Conclusions: This online survey was designed to capture real-world HRQOL data describing men with CRPC. The study estimated utilities using two alternative methods, and the results show good agreement, suggesting that they are robust. This methodology offers a potentially higher quality alternative to vignette-based methods that are commonly used in oncology submissions.