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 .
Mapping the FACT-G cancer-specific quality of life instrument to the EQ-5D and SF-6D
Objective To help facilitate economic evaluations of oncology treatments , we mapped responses on cancer-specific instrument to generic preference-based measures . Methods Cancer patients ( n = 367 ) completed one cancer-specific instrument , the FACT-G , and two preference-based measures , the  EQ-5D and SF-6D . Responses were r and omly divided to form development ( n = 184 ) and cross-validation ( n = 183 ) sample s. Relationships between the instruments were estimated using ordinary least squares ( OLS ) , generalized linear models ( GLM ) , and censored least absolute deviations ( CLAD ) regression approaches . The performance of each model was assessed in terms of how well the responses to the cancer-specific instrument predicted EQ-5D and SF-6D utilities using mean absolute error ( MAE ) and root mean squared error ( RMSE ) . Results Physical , functional , and emotional well-being domain scores of the FACT-G best explained the EQ-5D and SF-6D . In terms of accuracy of prediction as measured in RMSE , the CLAD model performed best for the EQ-5D ( RMSE = 0.095 ) whereas the GLM model performed best for the SF-6D ( RMSE = 0.061 ) . The GLM predicted SF-6D scores matched the observed values more closely than the CLAD and OLS . Conclusion Our results demonstrate that the estimation of both EQ-5D and SF-6D utility indices using the FACT-G responses can be achieved . The CLAD model for the EQ-5D and the GLM model for the SF-6D are recommended . Thus , it is possible to estimate quality -adjusted life years for economic evaluation from studies where only cancer-specific instrument have been administered
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 .