Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .
Health-related quality of life among prostate cancer patients: real-life situation at the beginning of treatment
Abstract Objective : The aims of this study were to measure the real-life health-related quality of life ( HRQoL ) of newly diagnosed prostate cancer ( PCa ) patients , to compare it with that of the general male population and to explore factors affecting HRQoL. Methods : All newly diagnosed PCa patients in the Helsinki University Hospital were asked to fill in 15D and EORTC QLQ-C30 question naires . Clinical background information was collected retrospectively from patient charts . Patients were categorized into three mutually exclusive groups based on the disease stage : Local , Locally advanced and Metastatic groups . Multivariate linear regression analysis was conducted to explore which factors explained variance in 15D scores . A regression model was built to map the EORTC QLQ-C30 to 15D in a r and om sample of 50 % of patients and the model was tested in the other half of the patients . Results : In total , 1050 men with a mean age of 67 years responded to the question naires . The mean ± SD 15D score of patients was slightly lower than that of the age-st and ardized general male population : 0.905 ± 0.089 vs 0.915 ± 0.082 ( p = .057 ) . The mean ± SD 15D utility scores were 0.912 ± 0.084 , 0.897 ± 0.102 and 0.855 ± 0.109 for Local , Locally advanced and Metastatic groups , respectively . The mapping model of EORTC QLQ-C30 to 15D was robust and fitted well ( root mean square error = 0.042 , adjusted R² = .79 ) . Conclusions : The HRQoL of PCa patients entering treatment was similar to that of the general population . HRQoL was most impaired among patients with metastatic disease , whereas the difference between patients with localized PCa and the general population was minor . Mapping indicated that the 15D score aggregates quite accurately the information from the EORTC QLQ-C30
Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .