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 Quality of Life (EQ-5D) from DAPsA, Clinical DAPsA and HAQ in Psoriatic Arthritis
Background Clinical trials and observational studies lacking measures of health-related quality of life ( QoL ) are often inapplicable when conducting cost-effectiveness analyses using quality -adjusted life-years ( QALYs ) . The only solution is to map QoL ex post from additionally collected clinical outcomes and generic QoL instruments . Nonetheless , mapping studies are absent in psoriatic arthritis ( PsA ) . Methods In this 2-year , prospect i ve , multicentre , non-interventional study of PsA patients , EQ-5D and key clinical parameters such as Disease Activity in PsA ( DAPsA ) , clinical DAPsA ( cDAPsA ; DAPsA without C-reactive protein [ CRP ] ) , and Health Assessment Question naire disability index ( HAQ ) were collected . We employed a linear mixed-effect regression model ( ME ) of the longitudinal data set to explore the best predictors of QoL. Results A total of 228 patients were followed over 873 appointments/observations .  DAPsA , cDAPsA and HAQ were stable and highly significant predictors of EQ-5D utilities in both cross-sectional and longitudinal analyses . The best prediction was provided using a linear ME with HAQ and cDAPsA or DAPsA. A HAQ increase of 1 point represented a decrease in EQ-5D by −0.204 or −0.203 ( p < 0.0001 ) ; a one-point increase in cDAPsA or DAPsA dropped EQ-5D equally by −0.005 ( p < 0.0001 ) . The ME revealed steeper and more accurate association compared with cross-sectional regressions or non-linear models/transformations . Conclusions This is the first mapping study conducted in PsA and we hope that our study will encourage further mapping studies in PsA. The results showed that in cases where CRP is absent , cDAPsA provides similar results to DAPsA in predicting
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 .