RESULTS ( 1 ) EQ-5D was valid and responsive for skin conditions and most cancers ; in vision , its performance varied according to aetiology ; and performance was poor for hearing impairments .
The HUI3 performed well for hearing and vision disorders .
It also performed well in cancers although evidence was limited and there was no evidence in skin conditions .
Response mapping using all the domain scores was the best performing model for the EORTC QLQ-C30 .
In an exploratory analysis , a limited dependent variable mixture model performed better than an equivalent linear model .
3 ) The exploratory valuation study found that bolt-on items for vision , hearing and tiredness had a significant impact on values of the health states , but the direction and magnitude of differences depended on the severity of the health state .
The vision bolt-on item had a statistically significant impact on EQ-5D health state values and a full valuation model was estimated .
EQ-5D performs well in studies of cancer and skin conditions .
Mapping techniques provide a solution to predict EQ-5D values where EQ-5D has not been administered .
For conditions where EQ-5D was found to be inappropriate , including some vision disorders and for hearing , bolt-ons provide a promising solution .
BACKGROUND The National Institute for Health and Care Excellence recommends the use of generic preference-based measures ( GPBMs ) of health for its Health Technology Assessment s ( HTAs ) .
However , these data may not be available or appropriate for all health conditions .
OBJECTIVES To determine whether GPBMs are appropriate for some key conditions and to explore alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate .
( 2 ) Potential modelling approaches to ' map ' EQ-5D values from condition-specific and clinical measures of health [ European Organisation for Research and Treatment of Cancer Quality -of-life Question naire Core 30 ( EORTC QLQ-C30 ) and Functional Assessment of Cancer Therapy - General Scale ( FACT-G ) ] are compared for predictive ability and goodness of fit using two separate data sets . (
US Valuation of the EQ-5D Health States: Development and Testing of the D1 Valuation Model
Purpose : The EQ-5D is a brief , multiattribute , preference-based health status measure . This article describes the development of a statistical model for generating US population -based EQ-5D preference weights . Methods : A multistage probability sample was selected from the US adult civilian noninstitutional population . Respondents valued 13 of 243 EQ-5D health states using the time trade-off ( TTO ) method . Data for 12 states were used in econometric modeling . The TTO valuations were linearly transformed to lie on the interval [ −1 , 1 ] . Methods were investigated to account for interaction effects caused by having problems in multiple EQ-5D dimensions . Several alternative model specifications ( eg , pooled least squares , r and om effects ) also were considered . A modified split- sample approach was used to evaluate the predictive accuracy of the models . All statistical analyses took into account the clustering and disproportionate selection probabilities inherent in our sampling design . Results : Our D1 model for the EQ-5D included ordinal terms to capture the effect of departures from perfect health as well as interaction effects . A r and om effects specification of the D1 model yielded a good fit for the observed TTO data , with an overall R2 of 0.38 , a mean absolute error of 0.025 , and 7 prediction errors exceeding 0.05 in absolute magnitude . Conclusions : The D1 model best predicts the values for observed health states . The result ing preference weight estimates represent a significant enhancement of the EQ-5D 's utility for health status assessment and economic analysis in the US
RESULTS ( 1 ) EQ-5D was valid and responsive for skin conditions and most cancers ; in vision , its performance varied according to aetiology ; and performance was poor for hearing impairments .
The HUI3 performed well for hearing and vision disorders .
It also performed well in cancers although evidence was limited and there was no evidence in skin conditions .
Response mapping using all the domain scores was the best performing model for the EORTC QLQ-C30 .
In an exploratory analysis , a limited dependent variable mixture model performed better than an equivalent linear model .
3 ) The exploratory valuation study found that bolt-on items for vision , hearing and tiredness had a significant impact on values of the health states , but the direction and magnitude of differences depended on the severity of the health state .
The vision bolt-on item had a statistically significant impact on EQ-5D health state values and a full valuation model was estimated .
EQ-5D performs well in studies of cancer and skin conditions .
Mapping techniques provide a solution to predict EQ-5D values where EQ-5D has not been administered .
For conditions where EQ-5D was found to be inappropriate , including some vision disorders and for hearing , bolt-ons provide a promising solution .
BACKGROUND The National Institute for Health and Care Excellence recommends the use of generic preference-based measures ( GPBMs ) of health for its Health Technology Assessment s ( HTAs ) .
However , these data may not be available or appropriate for all health conditions .
OBJECTIVES To determine whether GPBMs are appropriate for some key conditions and to explore alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate .
( 2 ) Potential modelling approaches to ' map ' EQ-5D values from condition-specific and clinical measures of health [ European Organisation for Research and Treatment of Cancer Quality -of-life Question naire Core 30 ( EORTC QLQ-C30 ) and Functional Assessment of Cancer Therapy - General Scale ( FACT-G ) ] are compared for predictive ability and goodness of fit using two separate data sets . (