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 SRS-22r questionnaire onto the EQ-5D-5L utility score in patients with adolescent idiopathic scoliosis
This is a prospect i ve study to establish prediction models that map the refined Scoliosis Research Society 22-item ( SRS-22r ) onto EuroQoL-5 dimension 5-level ( EQ-5D-5L ) utility scores in adolescent idiopathic scoliosis ( AIS ) patients . Comparison of treatment outcomes in AIS can be determined by cost-utility analysis . However , the mainstay spine-specific health-related quality of life outcome measure , the SRS-22r question naire does not provide utility assessment . In this study , AIS patients were prospect ively recruited to complete both the EQ-5D-5L and SRS-22r question naires by trained interviewers . Ordinary least squares regression was undertaken to develop mapping models , which the validity and robustness were assessed by using the 10-fold cross-validation procedure .  EQ-5D-5L utility scores were regressed on demographics , Cobb angle , curve types , treatment modalities , and five domains of the SRS-22r question naire . Three models were developed using stepwise selection method . EQ-5D-5L scores were regressed on 1 ) main effects of SRS-22r subscale scores , 2 ) as per 1 plus squared and interaction terms , and 3 ) as per 2 plus demographic and clinical characteristics . Model goodness-of-fit was assessed using R-square , adjusted R-square , and information criteria ; whereas the predictive performance was evaluated using root mean square error ( RMSE ) , mean absolute error ( MAE ) , and the proportion of absolute error within the threshold of 0.05 and 0.10 . A total of 227 AIS patients with mean age of 15.6 years were recruited . The EQ-5D-5L scores were predicted by four domains of SRS-22r ( main effects of ‘ Function ’ , ‘ Pain ’ , ‘ Appearance ’ and ‘ Mental Health ’ , and squared term of ‘ Function ’ and ‘ Pain ’ ) , and Cobb angle in Model 3 with the best goodness-of-fit ( R-square/adjusted R-square : 62.1%/60.9 % ) . Three models demonstrated an acceptance predictive performance in error analysis applying 10-fold cross-validation to three models where RMSE and MAE were between 0.063–0.065 and between 0.039–0.044 , respectively . Model 3 was therefore recommended out of three mapping models established in this paper . To our knowledge , this is the first study to map a spine-specific health-related quality of life measure onto EQ-5D-5L for AIS patients . With the consideration and incorporation of demographic and clinical characteristics , over 60 % variance explained by mapping model 3 enabled the satisfactory prediction of EQ-5D-5L utility scores from existing SRS-22r data for health economic appraisal of different treatment options
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 .