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 12-item multiple sclerosis walking scale to the EuroQol 5-dimension index measure in North American multiple sclerosis patients
Objective To map the 12-item Multiple Sclerosis Walking Scale ( MSWS-12 ) onto the EuroQol 5-dimension ( EQ-5D ) health-utility index in multiple sclerosis ( MS ) patients participating in the North American Research Committee on Multiple Sclerosis ( NARCOMS ) registry . Design Cross-sectional MSWS-12 to EQ-5D cross-walking analysis . Setting NARCOMS registry spring 2010 biannual up date and supplemental survey . Participants North American patients completing both the MSWS-12 and the EQ-5D r and omly split into derivation and validation cohorts . Outcome measures Ordinary least squares regression was performed within the derivation cohort , with participants ’ EQ-5D as the dependent variable . Results of the MSWS-12 were input as independent variable(s ) into six regression models . Model goodness-of-fit was subsequently assessed in the validation cohort using the mean absolute error ( MAE ) , root mean square error ( RMSE ) and the adjusted R2 . The best performing model was refined in the entire cohort and utilised for additional analyses . Results A total of 3505 NARCOMS participants were included .  Their mean±SD EQ-5D and MSWS-12 scores were 0.74±0.18 and 50.8±33.5 , respectively , and these assessment s were found to be moderately correlated ( r=–0.553 , p<0.001 ) . The model using all individual MSWS-12 item scores as independent variables was found to have the best fit ( MAE=0.109±0.096 , RMSE=0.145 , adjusted R2=0.329 ) . The percentage of EQ-5D estimates within 0.05 and 0.10 of the actual value were 30 % and 61 % , respectively . This mapping equation was more precise in patients with moderate mobility impairment ( MAE=0.087±0.061 at patient-determined disease step ( PDDS ) of 3–6 ) and less precise in patients with no ( MAE=0.141±0.128 at PDDS of 0–2 ) or severe mobility impairment ( MAE=0.121±0.049 at PDDS ≥7 ) . Conclusions The EQ-5D scores can be predicted using the MSWS-12 item scores with reasonable precision in North American patients with MS . Prediction estimates were more precise in patients with moderate mobility impairment
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 .