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 cancer-specific EORTC QLQ-C30 to the preference-based EQ-5D, SF-6D, and 15D instruments.
OBJECTIVES To estimate models , via ordinary least squares regression , for predicting Euro Qol 5D ( EQ-5D ) , Short Form 6D ( SF-6D ) , and 15D utilities from scale scores of the European Organization for Research and Treatment of Cancer Quality of Life Question naire ( EORTC QLQ-C30 ) . METHODS Forty-eight gastric cancer patients , split up into equal subgroups by age , sex , and chemotherapy scheme , were interviewed , and the survey included the QLQ-C30 , SF-36 , EQ-5D , and 15D instruments , along with sociodemographic and clinical data . Model predictive ability and explanatory power were assessed by root mean square error ( RMSE ) and adjusted R(2 ) values , respectively . Pearson 's r between predicted and reported utility indices was compared . Three r and om sub sample s , half in size the initial sample , were created and used for " external " validation of the modeling equations . RESULTS Explanatory power was high , with adjusted R(2 ) reaching 0.909 , 0.833 , and 0.611 for 15D , SF-6D , and EQ-5D , respectively . After normalization of RMSE to the range of possible values , the prediction errors were 12.0 , 5.4 , and 5.6 % for EQ-5D , SF-6D , and 15D , respectively . The estimation equations produced a range of utility scores similar to those achievable by the st and ard scoring algorithms . Predicted and reported indices from the validation sample s were comparable thus confirming the previous results . CONCLUSIONS Evidence on the ability of QLQ-C30 scale scores to validly predict 15D and SF-6D utilities , and to a lesser extent , EQ-5D , has been provided . The modeling equations must be tried in future studies with larger and more diverse sample s to confirm their appropriateness for estimating quality -adjusted life-year in cancer-patient trials including only the 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 .