Mapping scores from the Strengths and Difficulties Questionnaire (SDQ) to preference-based utility values Mapping the Paediatric Quality of Life Inventory (PedsQL™) Generic Core Scales onto the Child Health Utility Index–9 Dimension (CHU-9D) Score for Economic Evaluation in Children Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences Mapping of the DLQI scores to EQ-5D utility values using ordinal logistic regression Mapping utility scores from a disease-specific quality-of-life measure in bariatric surgery patients. Mapping from disease-specific measures to health-state utility values in individuals with migraine. Paving the way for the use of the SDQ in economic evaluations of school-based population health interventions: an empirical analysis of the external validity of SDQ mapping algorithms to the CHU9D in an educational setting Assessment of patient preferences among men with prostate cancer. Estimating a preference-based index for a menopause specific health quality of life questionnaire Mapping Between the Sydney Asthma Quality of Life Questionnaire (AQLQ-S) and Five Multi-Attribute Utility Instruments (MAUIs) Mapping SF-36 onto the EQ-5D index: how reliable is the relationship? The Assessment of Quality of Life (AQoL) instrument: a psychometric measure of Health-Related Quality of Life Comparison of methods to estimate health state utilities for ovarian cancer using quality of life data: a Gynecologic Oncology Group study. Modeling a preference-based index for two condition-specific measures (asthma and overactive bladder) using a nonparametric Bayesian method. Developing a utility index for the Aberrant Behavior Checklist (ABC-C) for fragile X syndrome Assessing outcomes for cost-utility analysis in mental health interventions: mapping mental health specific outcome measure GHQ-12 onto EQ-5D-3L Health-Related Quality of Life and Utility in Patients with Advanced Non–Small-Cell Lung Cancer: A Prospective Cross-Sectional Patient Survey in a Real-World Setting Economic evaluation in short bowel syndrome (SBS): an algorithm to estimate utility scores for a patient-reported SBS-specific quality of life scale (SBS-QoL™) Mapping the FACT-G cancer-specific quality of life instrument to the EQ-5D and SF-6D Mapping between the Roland Morris Questionnaire and generic preference-based measures. Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm. Bayesian predictors of very poor health related quality of life and mortality in patients with COPD Testing alternative regression models to predict utilities: mapping the QLQ-C30 onto the EQ-5D-5L and the SF-6D A comparison of physician-rated disease severity and patient reported outcomes in mild to moderately active ulcerative colitis. Multiattribute and Single‐Attribute Utility Functions for the Health Utilities Index Mark 3 System Development of the EXACT-U: a preference-based measure to report COPD exacerbation utilities. Estimating the SF-6D value set for a population-based sample of Brazilians. Cost-effectiveness of pazopanib: an example of improved transparency and accessibility of industry-sponsored economic evaluations through publication in peer-reviewed journals. Scoring the Child Health Utility 9D instrument: estimation of a Chinese child and adolescent-specific tariff Mapping FACT-melanoma quality-of-life scores to EQ-5D health utility weights. Informative value of Patient Reported Outcomes (PRO) in Health Technology Assessment (HTA) Mapping chronic liver disease questionnaire scores onto SF-6D utility values in patients with primary sclerosing cholangitis Reporting quality of life in clinical trials: a CONSORT extension Estimating a Preference-Based Index for an Eight-Dimensional Health State Classification System for Multiple Sclerosis. An empirical comparison of EQ-5D and SF-6D in liver transplant patients. Prospective evaluation of preferences and quality of life in women with hip fractures. Relationship between health-related quality of life, comorbidities and acute health care utilisation, in adults with chronic conditions Rescaling quality of life values from discrete choice experiments for use as QALYs: a cautionary tale Costs and quality of life in community-dwelling patients with Alzheimer's disease in Spain: results from the GERAS II observational study. 3L, 5L, What the L? A NICE Conundrum Mapping the cancer-specific EORTC QLQ-C30 to the preference-based EQ-5D, SF-6D, and 15D instruments. Development of a transformation model to derive general population–based utility: Mapping the pruritus–visual analog scale (VAS) to the EQ‐5D utility Mapping the 25-item National Eye Institute Visual Functioning Questionnaire (NEI VFQ-25) to EQ-5D Utility Scores Evaluating the Quality of Randomized Controlled Trials that Examine the Efficacy of Natural Health Products: A Systematic Review of Critical Appraisal Instruments Estimation of a Preference-Based Index from a Condition-Specific Measure: The King's Health Questionnaire Has the quality of health-related quality of life reporting in cancer clinical trials improved over time? Towards bridging the gap with clinical decision making. Effectiveness of education in evidence-based healthcare: the current state of outcome assessments and a framework for future evaluations. Analysis of health-related quality of life and costs based on a randomised clinical trial of escitalopram for relapse prevention in patients with generalised social anxiety disorder Valuing SF-6D Health States Using a Discrete Choice Experiment The impact of preoperative patient characteristics on the cost-effectiveness of total hip replacement: a cohort study Estimation of patient preference-based utility weights from the functional assessment of cancer therapy - general. Mapping the clinical chronic obstructive pulmonary disease questionnaire onto generic preference-based EQ-5D values. Application of a disease-specific mapping function to estimate utility gains with effective treatment of schizophrenia The effects of strabismus on quality of life in adults. Patient utilities in chronic musculoskeletal pain: how useful is the standard gamble method? Development of an EORTC-8D Utility Algorithm for Sri Lanka Preference-Based Measurement of Health-Related Quality of Life (HRQL) in Children with Chronic Musculoskeletal Disorders (MSKDs)
Abstract Purpose Quality of life mapping methods such as “ Transfer to Utility ” can be used to translate scores on disease-specific measures to utility values , when traditional utility measurement methods ( e.g. st and ard gamble , time trade-off , preference-based multi-attribute instruments ) have not been used . The aim of this study was to generate preliminary ordinary least squares ( OLS ) regression-based algorithms to transform scores from the Strengths and Difficulties Question naires ( SDQ ) , a widely used measure of mental health in children and adolescents , to utility values obtained using the preference-based Child Health Utility ( CHU9D ) instrument . Methods Two hundred caregivers of children receiving community mental health services completed the  SDQ and CHU9D  during a telephone interview . Two OLS regressions were run with the CHU9D utility value as the dependent variable and SDQ subscales as predictors . Result ing algorithms were vali date d by comparing predicted and observed group mean utility values in r and omly selected sub sample s. Results Preliminary validation was obtained for two algorithms , utilising five and three subscales of the SDQ , respectively . Root mean square error values ( .124 ) for both models suggested poor fit at an individual level , but both algorithms performed well in predicting mean group observed utility values . Conclusion This research generated algorithms for translating SDQ scores to utility values and providing research ers with an additional tool for conducting health economic evaluations with child and adolescent mental health data Background The Paediatric Quality of Life Inventory ( PedsQL ™ ) question naire is a widely used , generic instrument design ed for measuring health-related quality of life ( HRQoL ) ; however , it is not preference-based and therefore not suitable for cost – utility analysis . The Child Health Utility Index–9 Dimension ( CHU-9D ) , however , is a preference-based instrument that has been primarily developed to support cost – utility analysis . Objective This paper presents a method for estimating CHU-9D index scores from responses to the PedsQL ™ using data from a r and omised controlled trial of prednisolone therapy for treatment of childhood corticosteroid-sensitive nephrotic syndrome . Methods HRQoL data were collected from children at r and omisation , week 16 , and months 12 , 18 , 24 , 36 and 48 . Observations on children aged 5 years and older were pooled across all data collection timepoints and were then r and omised into an estimation ( n = 279 ) and validation ( n = 284 ) sample . A number of models were developed using the estimation data before internal validation . The best model was chosen using multi-stage selection criteria . Results Most of the models developed accurately predicted the CHU-9D mean index score . The best performing model was a generalised linear model ( mean absolute error = 0.0408 ; mean square error = 0.0035 ) . The proportion of index scores deviating from the observed scores by < 0.03 was 53 % . Conclusions The mapping algorithm provides an empirical tool for estimating CHU-9D index scores and for conducting cost – utility analyses within clinical studies that have only collected PedsQL ™ data . It is valid for children aged 5 years or older . Caution should be exercised when using this with children younger than 5 years , older adolescents ( > 13 years ) or patient groups with particularly poor quality of life . IS RCT N Registry Background Although cancer-specific Health-Related Quality of Life ( HRQOL ) are commonly included in r and omized clinical trials or other prospect i ve non-r and omized clinical studies , it is rare that preference-based instruments are used that allow the calculation of a utility weight suitable for estimating quality -adjusted life-years gained . Objective To develop a mapping algorithm to transform the EORTC QLQ-C30 question naire responses into EQ-5D derived utilities . Study design Retrospective data analysis of a multicentre , multicountry prospect i ve clinical trial in breast cancer patients . Methods Regression analysis of individual pairs of EQ-5D and QLQ-C30 scores . Results A model that explained 80 % of the variance was developed to estimate EQ-5D Utilities from QLQ-C30 scores at individual level . From this reliable group level means and deviations can be derived . Conclusions Mapping from QLQ-C30 scores to EQ-5D-derived utilities when only QLQ-C30 data are available has been shown to be possible with good accuracy . Validation of the proposed algorithm in other external clinical data sets should be encouraged Purpose The Dermatology  Life Quality  Index ( DLQI ) and the European Quality of Life-5 Dimension ( EQ-5D ) are separate measures that may be used to gather health-related quality of life ( HRQoL ) information from patients . The EQ-5D is a generic measure from which health utility estimates can be derived , whereas the DLQI is a specialty-specific measure to assess HRQoL. To reduce the burden of multiple measures being administered and to enable a more disease-specific calculation of health utility estimates , we explored an established mathematical technique known as ordinal logistic regression ( OLR ) to develop an appropriate model to map DLQI data to EQ-5D-based health utility estimates . Methods Retrospective data from 4010 patients were r and omly divided five times into two groups for the derivation and testing of the mapping model . Split-half cross-validation was utilized result ing in a total of ten ordinal logistic regression models for each of the five EQ-5D dimensions against age , sex , and all ten items of the DLQI . Using Monte Carlo simulation , predicted health utility estimates were derived and compared against those observed . This method was repeated for both OLR and a previously tested mapping methodology based on linear regression . Results The model was shown to be highly predictive and its repeated fitting demonstrated a stable model using OLR as well as linear regression . The mean differences between OLR-predicted health utility estimates and observed health utility estimates ranged from 0.0024 to 0.0239 across the ten modeling exercises , with an average overall difference of 0.0120 ( a 1.6 % underestimate , not of clinical importance ) . Conclusions This modeling framework developed in this study will enable research ers to calculate EQ-5D health utility estimates from a specialty-specific study population , reducing patient and economic burden OBJECTIVES To develop algorithms for a conversion of disease-specific quality -of-life into health state values for morbidly obese patients before or after bariatric surgery . METHODS A total of 893 patients were enrolled in a prospect i ve cross-sectional multicenter study . In addition to demographic and clinical data , health-related quality -of-life ( HRQoL ) data were collected using the disease-specific Moorehead-Ardelt II question naire ( MA-II ) and two generic question naires , the EuroQoL-5D ( EQ-5D ) and the Short Form-6D ( SF-6D ) . Multiple regression models were constructed to predict EQ-5D- and SF-6D-based utility values from MA-II scores and additional demographic variables . RESULTS The mean body mass index was 39.4 , and 591 patients ( 66 % ) had already undergone surgery . The average EQ-5D and SF-6D scores were 0.830 and 0.699 . The MA-IIwas correlated to both utility measures ( Spearman 's r = 0.677 and 0.741 ) . Goodness-of-fit was highest ( R(2 ) = 0.55 in the validation sample ) for the following item-based transformation algorithm : utility ( MA-II-based ) = 0.4293 + ( 0.0336 x MA1 ) + ( 0.0071 x MA2 ) + ( 0.0053 x MA3 ) + ( 0.0107 x MA4 ) + ( 0.0001 x MA5 ) . This EQ-5D-based mapping algorithm outperformed a similar SF-6D-based algorithm in terms of mean absolute percentage error ( P = 0.045 ) . CONCLUSIONS Because the mapping algorithm estimated utilities with only minor errors , it appears to be a valid method for calculating health state values in cost-utility analyses . The algorithm will help to define the role of bariatric surgery in morbid obesity OBJECTIVE The objective of this study was to develop empirical algorithms that estimate health-state utility values from disease-specific quality -of-life scores in individuals with migraine . METHODS Data from a cross-sectional , multicountry study were used . Individuals with episodic and chronic migraine were r and omly assigned to training or validation sample s. Spearman 's correlation coefficients between paired EuroQol five-dimensional ( EQ-5D ) question naire utility values and both Headache Impact Test ( HIT-6 ) scores and Migraine-Specific Quality -of-Life Question naire version 2.1 ( MSQ ) domain scores ( role restrictive , role preventive , and emotional function ) were examined . Regression models were constructed to estimate EQ-5D question naire utility values from the HIT-6 score or the MSQ domain scores . Preferred algorithms were confirmed in the validation sample s. RESULTS In episodic migraine , the preferred HIT-6 and MSQ algorithms explained 22 % and 25 % of the variance ( R(2 ) ) in the training sample s , respectively , and had similar prediction errors ( root mean square errors of 0.30 ) . In chronic migraine , the preferred HIT-6 and MSQ algorithms explained 36 % and 45 % of the variance in the training sample s , respectively , and had similar prediction errors ( root mean square errors 0.31 and 0.29 ) . In episodic and chronic migraine , no statistically significant differences were observed between the mean observed and the mean estimated EQ-5D question naire utility values for the preferred HIT-6 and MSQ algorithms in the validation sample s. CONCLUSIONS The relationship between the EQ-5D question naire and the HIT-6 or the MSQ is adequate to use regression equations to estimate EQ-5D question naire utility values . The preferred HIT-6 and MSQ algorithms will be useful in estimating health-state utilities in migraine trials in which no preference-based measure is present Abstract Purpose The Strengths and Difficulties Question naire ( SDQ ) is a behavioural screening tool for children . The SDQ is increasingly used as the primary outcome measure in population health interventions involving children , but it is not preference based ; therefore , its role in allocative economic evaluation is limited . The Child Health Utility 9D ( CHU9D ) is a generic preference-based health-related quality of-life measure . This study investigates the applicability of the SDQ outcome measure for use in economic evaluations and examines its relationship with the CHU9D by testing previously published mapping algorithms . The aim of the paper is to explore the feasibility of using the SDQ within economic evaluations of school-based population health interventions . Methods Data were available from children participating in a cluster r and omised controlled trial of the school-based roots of empathy programme in Northern Irel and . Utility was calculated using the original and alternative CHU9D tariffs along with two SDQ mapping algorithms . t tests were performed for pairwise differences in utility values from the preference-based tariffs and mapping algorithms . Results Mean ( st and ard deviation ) SDQ total difficulties and prosocial scores were 12 ( 3.2 ) and 8.3 ( 2.1 ) . Utility values obtained from the original tariff , alternative tariff , and mapping algorithms using five and three SDQ subscales were 0.84 ( 0.11 ) , 0.80 ( 0.13 ) , 0.84 ( 0.05 ) , and 0.83 ( 0.04 ) , respectively . Each method for calculating utility produced statistically significantly different values except the original tariff and five SDQ subscale algorithm . Conclusion Initial evidence suggests the SDQ and CHU9D are related in some of their measurement properties . The mapping algorithm using five SDQ subscales was found to be optimal in predicting mean child health utility . Future research valuing changes in the SDQ scores would contribute to this research PURPOSE We developed a self-administered paper based instrument to assess patient preferences quantified as utilities for common outcomes associated with the management of prostate cancer . MATERIAL S AND METHODS A total of 50 patients was invited to test a self-administered paper based instrument design ed to assess preferences for health outcomes associated with the management of localized prostate cancer . The 50 patients were selected from a group of 625 r and omly identified men with prostate cancer who responded to a survey instrument design ed to assess health related quality of life . The 50 patients selected for this pilot project were chosen because of the wide range of responses to the  quality of life survey . Patient utilities were assessed for the 5 health states of overall quality of life , problems related to prostate cancer , and problems related to urinary , bowel and sexual dysfunction . RESULTS Patients were able to complete the assigned tasks . The self-administered instrument had high test-retest reliability . In addition results obtained from this instrument showed a correlation with results obtained from assessment s using other instruments , including an analog scale , a computer based system known as U-Titer , a quality of life survey and the Health Utility Index:3 . CONCLUSIONS A self-administered paper based instrument can be used to assess patient utilities for health states associated with prostate cancer management . Results from the instrument tested appear to be reliable and valid , and are comparable to those obtained from other assessment techniques . A self-administered paper based instrument has distinct advantages when conducting large survey studies because it can be incorporated at relatively low cost Background The aim of the study was to develop a menopause-specific , preference-based health-related quality -of-life ( HRQoL ) index reflecting both menopausal symptoms and potential side-effects of Hormone Replacement Therapy ( HRT ) . Methods The study had three phases : the development of a health state classification , a prospect i ve valuation survey and the estimation of a model to interpolate HRQoL indices for all remaining health states as defined by the classification . A menopausal health state classification was developed with seven dimensions : hot flushes , aching joints/muscles , anxious/frightened feelings , breast tenderness , bleeding , vaginal dryness and undesirable and rogenic signs . Each dimension contains between three and five levels and defines a total of 6,075 health states . A sample of 96 health states was selected for the valuation survey . These states were valued by a sample of 229 women aged 45 to 60 , r and omly selected from 6 general practice lists in Sheffield , UK . Respondents were asked to complete a time trade-off ( TTO ) task for nine health states , result ing in an average of 16.5 values for each health state . Results Mean health states valued range from 0.48 to 0.98 ( where 1.0 is full health and zero is for states regarded as equivalent to death ) . Symptoms , as described by the classification system , can be rank-ordered in terms of their impact ( from high to low ) on menopausal HRQoL as follows : aching joints and muscles , bleeding , breast tenderness , anxious or frightened feelings , vaginal dryness , and rogenic signs . Hot flushes did not significantly contribute to model fit . The preferred model produced a mean absolute error of 0.053 , but suffered from bias at both ends of the scale . Conclusion This article presents an attempt to directly value a condition specific health state classification . The overall fit was disappointing , but the results demonstrate that menopausal symptoms are perceived by patients to have a significant impact on utility . The overall effect is modest compared to the more generic health state descriptions such as the EQ-5D . The result ant algorithm generates a preference-based index that can be used economic evaluation and that reflects the impact of this condition Purpose Economic evaluation of health services commonly requires information regarding health-state utilities . Sometimes this information is not available but non-utility measures of quality of life may have been collected from which the required utilities can be estimated . This paper examines the possibility of mapping a non-utility-based outcome , the Sydney Asthma Quality of Life Question naire ( AQLQ-S ) , onto five multi-attribute utility instruments :  Assessment of Quality of Life 8 Dimensions ( AQoL-8D ) ,  EuroQoL 5 Dimensions 5-Level ( EQ-5D-5L ) , Health Utilities Index Mark 3 ( HUI3 ) , 15 Dimensions ( 15D ) , and the Short-Form 6 Dimensions ( SF-6D ) . Methods Data for 856 individuals with asthma were obtained from a large Multi-Instrument Comparison ( MIC ) survey . Four statistical techniques were employed to estimate utilities from the AQLQ-S. The predictive accuracy of 180 regression models was assessed using six criteria : mean absolute error ( MAE ) , root mean squared error ( RMSE ) , correlation , distribution of predicted utilities , distribution of residuals , and proportion of predictions with absolute errors < 0.0.5 . Validation of initial ‘ primary ’ models was carried out on a r and om sample of the MIC data . Results Best results were obtained with non-linear models that included a quadratic term for the AQLQ-S score along with demographic variables . The four statistical techniques predicted models that performed differently when assessed by the six criteria ; however , the best results , for both the estimation and validation sample s , were obtained using a generalised linear model ( GLM estimator ) . Conclusions It is possible to predict valid utilities from the AQLQ-S using regression methods . We recommend GLM models for this exercise Background Mapping from health status measures onto generic preference-based measures is becoming a common solution when health state utility values are not directly available for economic evaluation . However the accuracy and reliability of the models employed is largely untested , and there is little evidence of their suitability in patient data sets . This paper examines whether mapping approaches are reliable and accurate in terms of their predictions for a large and varied UK patient data set . Methods SF-36 dimension scores are mapped onto the EQ-5D index using a number of different model specifications . The predicted EQ-5D scores for subsets of the sample are compared across inpatient and outpatient setting s and medical conditions . This paper compares the results to those obtained from existing mapping functions . Results The model including SF-36 dimensions , squared and interaction terms estimated using r and om effects GLS has the most accurate predictions of all models estimated here and existing mapping functions as indicated by MAE ( 0.127 ) and MSE ( 0.030 ) . Mean absolute error in predictions by EQ-5D utility range increases with severity for our models ( 0.085 to 0.34 ) and for existing mapping functions ( 0.123 to 0.272 ) . Conclusion Our results suggest that models mapping the SF-36 onto the EQ-5D have similar predictions across inpatient and outpatient setting and medical conditions . However , the models overpredict for more severe EQ-5D states ; this problem is also present in the existing mapping functions This paper describes constructing the Assessment of Quality of Life ( AQoL ) instrument ; design ed to measure health-related quality of life ( HRQoL )  , and to be the descriptive system for a multi-attribute utility instrument . Unlike previous utility instruments ' descriptive systems , the AQoL 's has been developed using state-of-the-art psychometric procedures . The result is a descriptive system which emphasizes five different facets of HRQoL and which can cl aim to have construct validity . Based on the WHO 's definition of health a model of HRQoL was developed . Items were written by focus groups of doctors and the research ers . These were administered to a construction sample , comprising hospital patients , and community members chosen at r and om . Final construction was through an iterative process of factor and reliability analyses . The AQoL measures 5 dimensions : illness , independent living , social relationships , physical senses and psychological wellbeing . Each has three items . Exploratory factor analysis showed the dimensions were orthogonal , and each was unidimensional . Internal consistency was α = 0.81 . Structural equation modeling explored its internal structure ; the comparative fit index was 0.90 . These preliminary results indicate the AQoL has the prerequisite qualities for a psychometric HRQoL instrument for evaluation ; replication with a larger sample is needed to verify these findings . Scaling it for economic evaluation using utilities is being undertaken . Respondents have indicated the AQoL is easy to underst and and is quickly completed . Its initial properties suggest it may be widely applicable BACKGROUND Cost-effectiveness/cost-utility analyses are increasingly needed to inform decisions about care . Algorithms have been developed using the Functional Assessment of Cancer Therapy ( FACT ) quality of life instrument to estimate utility weights for cost analyses . This study was design ed to compare these algorithms in the setting of ovarian cancer . METHODS GOG-0152 was a 550-patient r and omized phase III trial of interval cytoreduction , and GOG-0172 was a 415-patient r and omized phase III trial comparing intravenous versus intraperitoneal therapy among women with advanced ovarian cancer .  QOL data were collected via the FACT at four time points in each study . Two published mapping algorithms ( Cheung and Dobrez ) and a linear transformation method were applied to these data . The agreement between measures was assessed by the concordance correlation coefficient ( r(CCC ) ) , and paired t-tests were used to compare means . RESULTS While agreement between the estimation algorithms was good ( ranged from 0.72 to 0.81 ) , there were statistically significant ( p<0.001 ) and clinical ly meaningful differences between the scores : mean scores were higher with Dobrez than with Cheung or the linear transformation method . Scores were also statistically significantly different ( p<0.001 ) between studies . CONCLUSIONS In the absence of prospect ively collected utility data , the use of mapping algorithms is feasible , however , the optimal algorithm is not clear . There were significant differences between studies , which highlight the need for validation of these algorithms in specific setting s. If cost analyses incorporate mapping algorithms to obtain utility estimates , investigators should take the variability into account BACKGROUND Conventionally , parametric models were used for health state valuation data . Recently , research ers started to explore the use of nonparametric Bayesian methods in this area . OBJECTIVES We present a nonparametric Bayesian model to estimate a preference-based index for two condition-specific five-dimensional health state classifications , one for asthma ( five-dimensional Asthma Quality of Life Utility Index ) and the other for overactive bladder ( five-dimensional Overactive Bladder Quality of Life-Utility Index ) . METHODS Sample s of 307 and 311 members of the UK general population valued 99 health states selected from a total of 3125 health states defined by each of the measures using the time trade-off technique . The article presents the results of the nonparametric model and compares it with the original model estimated using a conventional parametric r and om-effects model . The different methods are compared theoretically and in terms of empirical performance across the two data sets . It also reports the effect of respondent characteristics on health state valuations . RESULTS The nonparametric models were found to be better at predicting health state values within the estimation sample than without in terms of root mean square error and the patterns of st and ardized residuals . Some respondent characteristics were found to explain variation in health state values , but these did not have a significant effect on the health states values when estimates were adjusted for sample differences with the general population . CONCLUSIONS The nonparametric Bayesian models are theoretically more appropriate than previously used parametric models and provide better utility estimates from the two condition-specific measures . Furthermore , the model is more flexible in estimating the effect of covariates Purpose This study aim ed to develop a utility index ( the ABC-UI ) from the Aberrant Behavior Checklist-Community ( ABC-C ) , for use in quantifying the benefit of emerging treatments for fragile X syndrome ( FXS ) . Methods The ABC-C is a proxy-completed assessment of behaviour and is a widely used measure in FXS . A subset of ABC-C items across seven dimensions was identified to include in health state descriptions . This item reduction process was based on item performance , factor analysis and Rasch analysis performed on an observational study data set , and consultation with five clinical experts and a method ological expert . Dimensions were combined into health states using an orthogonal design and valued using time trade-off ( TTO ) , with lead-time TTO methods used where TTO indicated a state valued as worse than dead . Preference weights were estimated using mean , individual level , ordinary least squares and r and om-effects maximum likelihood estimation [ RE ( MLE ) ] regression models . Results A representative sample of the UK general public ( n = 349 ; mean age 35.8 years , 58.2 % female ) each valued 12 health states . Mean observed values ranged from 0.92 to 0.16 for best to worst health states . The RE ( MLE ) model performed best based on number of significant coefficients and mean absolute error of 0.018 . Mean utilities predicted by the model covered a similar range to that observed . Conclusions The ABC-UI estimates a wide range of utilities from patient-level FXS ABC-C data , allowing estimation of FXS health-related quality of life impact for economic evaluation from an established FXS clinical trial instrument Background Many intervention-based studies aim ing to improve mental health do not include a multi-attribute utility instrument ( MAUI ) that produces quality -adjusted life-years ( QALYs ) and it limits the applicability of the health economic analyses . This study aims to develop ‘ crosswalk ’ transformation algorithm between a measure for psychological distress General Health Question naire ( GHQ-12 ) and MAUI EuroQoL ( EQ-5D-3L ) . Methods The study is based on a survey question  naire sent to a r and om sample in four counties in Sweden in 2012 . The survey included  GHQ-12 and EQ-5D instruments  , as well as a question about self-rated health . The EQ-5D index was calculated using the UK and the Swedish tariff values . Two OLS models were used to estimate the EQ-5D health state values using the GHQ-12 as exposure , based on the respondents ( n = 17 , 101 ) of two counties . The algorithms were applied to the data from two other counties , ( n = 15 , 447 ) to check the predictive capacity of the models . Results The final models included gender , age , self-rated health and GHQ-12 scores as a quantitative variable . The regression equations explained 40 % ( UK tariff ) and 46 % ( Swedish tariff ) of the variances . The model showed a satisfying predictive capacity between the observed and the predicted EQ-5D index score , with Pearson correlation = 0.65 and 0.69 for the UK and Swedish models , respectively . Conclusion The algorithms developed in this study can be used to determine cost-effectiveness of services or interventions that use GHQ-12 as a primary outcome where the utility measures are not collected Background : Non – small-cell lung cancer ( NSCLC ) has a significant impact on patients ’ health-related quality of life ( HRQOL ) . This study aim ed to measure health state utility values representing the individual ’s preferences for specific health-related outcomes in advanced NSCLC patients and to assess predictive parameters . Methods : We conducted a prospect i ve  quality -of-life survey on advanced NSCLC patients in 25 hospitals in Europe , Canada , Australia , and Turkey .  HRQOL was assessed using the  EuroQol ( EQ-5D ) question naire and  EQ-5D utility  and  EQ-visual analog ( EQ-VAS ) scores were estimated . Results : Three hundred nineteen patients were recruited of which 263 had evaluable data .  Mean utility for progression-free ( PF ) patients on first- , second- , and third-/fourth-line treatment was 0.71 ( SD = 0.24 ) , 0.74 ( SD = 0.18 ) , and 0.62 ( SD = 0.29 ) , respectively . Mean utility for patients with progressive disease ( PD ) while on first- , second- and third-/fourth-line treatment was 0.67 ( SD = 0.2 ) , 0.59 ( SD = 0.34 ) , and 0.46 ( SD = 0.38 ) , respectively . Overall , patients with PD had lower mean utility scores than PF patients ( 0.58 versus 0.70 ) . The results of the EQ-VAS showed that the score decreased with later treatment lines . Patients with PD had a 10-point decrease in VAS scores compared with PF patients ( 53.7 versus 66.6 ) . The regression analysis revealed that stage IV disease , higher lines of treatment , and health state were significant predictors of utility at the 10 % level . Conclusion : The results presented indicate a substantial impact of lung cancer on patients ’ HRQOL , with stage IV disease , line of treatment , and PD , result ing in considerable deterioration of utility . The values obtained here will inform evaluations of cost-utility for NSCLC therapies Purpose Condition-specific preference-based measures can offer utility data where they would not otherwise be available or where generic measures may lack sensitivity , although they lack comparability across conditions . This study aim ed to develop an algorithm for estimating utilities from the short bowel syndrome health-related quality of life scale ( SBS-QoL ™ ) . Methods SBS-QoL ™ items were selected based on factor and item performance analysis of a European SBS-QoL ™ data set and consultation with 3 SBS clinical experts . Six-dimension health states were developed using 8 SBS-QoL ™ items ( 2 dimensions combined 2 SBS-QoL ™ items ) . SBS health states were valued by a UK general population sample ( N = 250 ) using the lead-time time trade-off method . Preference weights or ‘ utility decrements ’ for each severity level of each dimension were estimated by regression models and used to develop the scoring algorithm . Results Mean utilities for the SBS health states ranged from −0.46 ( worst health state , very much affected on all dimensions ) to 0.92 ( best health state , not at all affected on all dimensions ) . The r and om effects model with maximum likelihood estimation regression had the best predictive ability and lowest root mean squared error and mean absolute error , and was used to develop the scoring algorithm . Conclusions The preference-weighted scoring algorithm for the SBS-QoL ™ developed is able to estimate a wide range of utility values from patient-level SBS-QoL ™ data . This allows estimation of SBS HRQL impact for the purpose of economic evaluation of SBS treatment benefits Objective To help facilitate economic evaluations of oncology treatments , we mapped responses on cancer-specific instrument to generic preference-based measures . Methods Cancer patients ( n = 367 ) completed one cancer-specific instrument , the FACT-G , and two preference-based measures , the  EQ-5D and SF-6D . Responses were r and omly divided to form development ( n = 184 ) and cross-validation ( n = 183 ) sample s. Relationships between the instruments were estimated using ordinary least squares ( OLS ) , generalized linear models ( GLM ) , and censored least absolute deviations ( CLAD ) regression approaches . The performance of each model was assessed in terms of how well the responses to the cancer-specific instrument predicted EQ-5D and SF-6D utilities using mean absolute error ( MAE ) and root mean squared error ( RMSE ) . Results Physical , functional , and emotional well-being domain scores of the FACT-G best explained the EQ-5D and SF-6D . In terms of accuracy of prediction as measured in RMSE , the CLAD model performed best for the EQ-5D ( RMSE = 0.095 ) whereas the GLM model performed best for the SF-6D ( RMSE = 0.061 ) . The GLM predicted SF-6D scores matched the observed values more closely than the CLAD and OLS . Conclusion Our results demonstrate that the estimation of both EQ-5D and SF-6D utility indices using the FACT-G responses can be achieved . The CLAD model for the EQ-5D and the GLM model for the SF-6D are recommended . Thus , it is possible to estimate quality -adjusted life years for economic evaluation from studies where only cancer-specific instrument have been administered OBJECTIVES The Rol and Morris Question naire ( RMQ ) is a widely used health status measure for low back pain ( LBP ) . It is not preference-based , and there are currently no established algorithms for mapping between the RMQ and preference-based health-related quality -of-life measures . Using data from r and omized controlled trials of treatment for LBP , we sought to develop algorithms for mapping between RMQ scores and health utilities derived using either the EuroQol five-dimensional question naire ( EQ-5D ) or the six-dimensional health state short form ( derived from Medical Outcomes Study 36-Item Short-Form Health Survey ) ( SF-6D ) . METHODS This study is based on data from the Back Skills Training Trial in which data were collected from 701 patients at baseline and subsequently at 3 , 6 , and 12 months postr and omization using a range of outcome measures , including the  RMQ , the EQ-5D , and the Short Form 12 item Health Survey ( SF-12 ) ( from which SF-6D utilities can be derived ) . We used baseline trial data to estimate models using both direct and response mapping approaches to predict EQ-5D and SF-6D health utilities and dimension responses . A multistage model selection process was used to assess the predictive accuracy of the models . We then explored different techniques and mapping models that made use of repeated follow-up observations in the data . The estimated mapping algorithms were vali date d using external data from the UK Back Pain Exercise and Manipulation trial . RESULTS A number of models were developed that accurately predict health utilities in this context . The best performing model for RMQ to EQ-5D mapping was a beta regression with Bayesian quasi-likelihood estimation that included 24 dummy variables for RMQ responses , age , and sex as covariates ( mean squared error 0.0380 ) based on repeated data . The model selected for RMQ to SF-6D mapping was a finite mixture model that included the overall RMQ score , age , sex , RMQ score squared , age squared , and an interaction term for age and RMQ score as covariates ( mean squared error 0.0114 ) based on repeated data . CONCLUSIONS It is possible to reasonably predict EQ-5D and SF-6D health utilities from RMQ scores and responses using regression methods . Our regression equations provide an empirical basis for estimating health utilities when EQ-5D or SF-6D data are not available . They can be used to inform future economic evaluations of interventions targeting LBP In contrast to the recent proliferation of studies incorporating ordinal methods to generate health state values from adults , to date relatively few studies have utilised ordinal methods to generate health state values from adolescents . This paper reports upon a study to apply profile case best worst scaling methods to derive a new adolescent specific scoring algorithm  for the Child Health Utility 9D ( CHU9D ) , a generic preference based instrument that has been specifically design ed for the estimation of quality adjusted life years for the economic evaluation of health care treatment and preventive programs targeted at young people . A survey was developed for administration in an on-line format in which consenting community based Australian adolescents aged 11 - 17 years ( N = 1982 ) indicated the best and worst features of a series of 10 health states derived from the CHU9D descriptive system . The data were analyzed using latent class conditional logit models to estimate values ( part worth utilities ) for each level of the nine attributes relating to the CHU9D . A marginal utility matrix was then estimated to generate an adolescent-specific scoring algorithm  on the full health = 1 and dead = 0 scale required for the calculation of QALYs . It was evident that different decision processes were being used in the best and worst choices . Whilst respondents appeared readily able to choose ' best ' attribute levels for the CHU9D health states , a large amount of r and om variability and indeed different decision rules were evident for the choice of ' worst ' attribute levels , to the extent that the best and worst data should not be pooled from the statistical perspective . The optimal  adolescent-specific scoring algorithm  was therefore derived using data obtained from the best choices only . The study provides important insights into the use of profile case best worst scaling methods to generate health state values with adolescent population Background Chronic obstructive pulmonary disease ( COPD ) is associated with increased mortality and poor health-related quality of life ( HRQoL ) compared with the general population . The objective of this study was to identify clinical characteristics which predict mortality and very poor HRQoL among the COPD population and to develop a Bayesian prediction model . Methods The data consisted of 738 patients with COPD who had visited the Pulmonary Clinic of the Helsinki and Turku University Hospitals during 1995–2006 . The data set contained 49 potential predictor variables and two outcome variables : survival ( dead/alive ) and HRQoL measured with a 15D instrument  ( very poor HRQoL < 0.70 vs. typical HRQoL ≥ 0.70).In the first phase of model validation we r and omly divided the material into a training set ( n = 538 ) , and a test set ( n = 200 ) . This procedure was repeated ten times in r and om fashion to obtain independently created training sets and corresponding test sets . Modeling was performed by using the training set , and each model was tested by using the corresponding test set , repeated in each training set . In the second phase the final model was created by using the total material and eighteen most predictive variables . The performance of six logistic regressions approaches were shown for comparison purpose s. Results In the final model , the following variables were associated with mortality or very poor HRQoL : age at onset , cerebrovascular disease , diabetes , alcohol abuse , cancer , psychiatric disease , body mass index , Forced Expiratory Volume ( FEV1 ) % of predicted , atrial fibrillation , and prolonged QT time in ECG . The prediction accuracy of the model was 77 % , sensitivity 0.30 , specificity 0.95 , positive predictive value 0.68 , negative predictive value 0.78 , and area under the ROC curve 0.69 . While the sensitivity of the model reminded limited , good specificity , moderate accuracy , comparable or better performance in classification and better performance in variable selection and data usage in comparison to the logistic regression approaches , and positive and negative predictive values indicate that the model has potential in predicting mortality and very poor HRQoL in COPD patients . Conclusion We developed a Bayesian prediction model which is potentially useful in predicting mortality and very poor HRQoL in patients with COPD Purpose The purpose of the study was to compare alternative statistical techniques to find the best approach for converting QLQ-C30 scores onto EQ-5D-5L and SF-6D utilities , and to estimate the mapping algorithms that best predict these health state utilities . Methods 772 cancer patients described their health along the  cancer-specific instrument ( QLQ-C30 )  and two generic preference-based instruments ( EQ-5D-5L and SF-6D ) . Seven alternative regression models were applied : ordinary least squares , generalized linear model , extended estimating equations ( EEE ) , fractional regression model , beta binomial ( BB ) regression , logistic quantile regression and censored least absolute deviation .  Normalized mean absolute error ( NMAE ) , normalized root mean square error ( NRMSE ) , r-squared ( r2 ) and concordance correlation coefficient ( CCC ) were used as model performance criteria . Cross-validation was conducted by r and omly splitting internal data set into two equally sized groups to test the generalizability of each model . Results In predicting EQ-5D-5L utilities , the BB regression performed best . It gave better predictive accuracy in terms of all criteria in the full sample , as well as in the validation sample . In predicting SF-6D , the EEE performed best . It outperformed in all criteria : NRMSE = 0.1004 , NMAE = 0.0798 , CCC = 0.842 and r2 = 72.7 % in the full sample , and NRMSE = 0.1037 , NMAE = 0.0821 , CCC = 0.8345 and r2 = 71.4 % in cross-validation . Conclusions When only QLQ-C30 data are available , mapping provides an alternative approach to obtain health state utility data for use in cost-effectiveness analyses . Among seven alternative regression models , the BB and the EEE gave the most accurate predictions for EQ-5D-5L and SF-6D , respectively BACKGROUND AND AIMS The aim was to derive health state utility scores in ulcerative colitis ( UC ) by establishing the relationship between the physician-rated ulcerative colitis disease activity index ( UCDAI ) and a patient reported EQ-5D by statistically mapping the two instruments . METHODS In a r and omised controlled trial comparing oral plus enema mesalazine treatment with oral mesalazine treatment alone ( PINCE ) , UCDAI and EQ-5D scores were collected in parallel from patients with active UC . From these data , multinomial logistic regression was used to estimate response probabilities to each of the five domains of the EQ-5D index from assessment of UC disease severity using original and abbreviated ( no endoscopy ) versions of the UCDAI . Predicted EQ-5D responses were converted by Monte Carlo simulation to the EQ-5D index for predicting health-related quality of life ( HRQoL ) . The reliability of the algorithm was tested using UCDAI scores from a second mesalazine RCT ( PODIUM ) . RESULTS The abbreviated-UCDAI showed comparable explanatory performance to the full UCDAI . For patients in remission , mean utility was 0.939 , 0.944 , and 0.940U for PINCE(estimated ) , PINCE(observed ) , and PODIUM , respectively . Mild/moderate and relapsing cases showed mean utilities of 0.801 , 0.811 , and 0.775 , respectively ; whilst for those in severe relapse , the mean utilities were 0.630 , 0.700 and 0.660 units , respectively . The mean squared error between actual and predicted utilities from observations in PINCE was 0.019 . CONCLUSION Response mapping of UC activity to EQ-5D domains produced reliable estimates of patient-rated health state utility consistent with UCDAI rated severity . Comparing abbreviated-UCDAI and full UCDAI suggests that inclusion of endoscopy scores has limited predictive value in estimating patient Background . The Health Utilities Index Mark 3 ( HUI3 ) is a generic multiattribute preference‐based measure of health status and health‐related quality of life that is widely used as an outcome measure in clinical studies , in population health surveys , in the estimation of quality ‐adjusted life years , and in economic evaluations . HUI3 consists of eight attributes ( or dimensions ) of health status : vision , hearing , speech , ambulation , dexterity , emotion , cognition , and pain with 5 or 6 levels per attribute , varying from highly impaired to normal . Objectives . The objectives are to present a multiattribute utility function and eight single‐attribute utility functions for the HUI3 system based on community preferences . Study Design . Two preference surveys were conducted . One , the modeling survey , collected preference scores for the estimation of the utility functions . The other , the direct survey , provided independent scores to assess the predictive validity of the utility functions . Measures . Preference measures included value scores obtained on the Feeling Thermometer and st and ard gamble utility scores obtained using the Chance Board . Respondents . A r and om sample of the general population ( ≥16 years of age ) in Hamilton , Ontario , Canada . Results . Estimates were obtained for eight single‐attribute utility functions and an overall multiattribute utility function . The intraclass correlation coefficient between directly measured utility scores and scores generated by the multiattribute function for 73 health states was 0.88 . Conclusions . The HUI3 scoring function has strong theoretical and empirical foundations . It performs well in predicting directly measured scores . The HUI3 system provides a practical way to obtain utility scores based on community preferences BACKGROUND The exacerbations of chronic obstructive pulmonary disease tool ( EXACT ) is a condition-specific daily diary recently developed to evaluate the frequency , severity , and duration of chronic obstructive pulmonary disease ( COPD ) exacerbations . A preference-based algorithm for the EXACT would allow utilities to be reported from patients during an exacerbation when EQ-5D data are not available . OBJECTIVE To develop the exacerbations of chronic obstructive pulmonary disease tool-utility ( EXACT-U ) , a condition-specific preference-based measure to report utilities from the EXACT for use in cost-effectiveness studies . METHODS Five items with three to five levels comprise the EXACT-U. Two groups of health states and respondents were constructed to allow for model development ( Development group ) and predictive validity testing ( Validation group ) using independent sample s. Members of the UK general public each valued 11 r and omized health states using time trade-offs ( TTOs ) scaled from full health/dead with 10-year duration s. Regression models estimated from the Development group using individual data , mean data , and panel design s. Models assessed by number of inconsistent coefficients estimated and R(2 ) and tested against observed utilities from the Validation group using mean absolute error ( MAE ) and root mean squared error ( RMSE ) . RESULTS A total of 55 health states , including the best and worst states , were valued in TTO interviews conducted with 400 respondents . Ten models were developed . The final preferred model contained no logical inconsistencies and found MAE = 0.04 and RMSE = 0.05 with a predicted utility range from 0.09 to 0.95 . CONCLUSIONS The EXACT-U is a condition-specific preference-based measure with strong predictive validity to report daily utilities during an exacerbation OBJECTIVES SF-6D is a preference-based measure of health developed to estimate utility values from the SF-36 . The aim of this study was to estimate a weighting system for the SF-6D health states representing the preferences of a sample of the Southern Brazilian general population . METHODS A sample of 248 health states defined by the SF-6D was valued by a sample of the southern Brazilian population using the st and ard gamble . Mean and individual level multivariate regression models were fitted to the st and ard gamble valuation data to estimate preference weights for all SF-6D health states . The models were compared with those estimated in the UK study . RESULTS Five hundred twenty-eight participants were interviewed , but 58 ( 11 % ) were excluded for failing to value the worst state . Data from 469 subjects producing 2696 health states valuations were used in the regression analysis . In contrast to the best performing model for the UK data , the best performing model for the Brazilian data was a r and om effects model using only the main effects variables , highlighting the importance of adopting a country-specific algorithm to derive SF-6D health states values . Inconsistent coefficients were merged to produce the final recommended model , which has all significant coefficients and a mean absolute difference between observed and predicted st and ard gamble values of 0.07 . CONCLUSIONS The results provide the first population -based value set for Brazil for SF-6D health states , making it possible to generate quality -adjusted life years for cost-utility studies using regional data . Besides , utility weights derived using the preferences of a sample from a southern Brazilian population can be derived from existing SF-36 data sets We congratulate Amdahl et al.1 on publishing their paper about the cost-effectiveness of pazopanib compared with sunitinib in metastatic renal cell carcinoma ( mrcc ) in Canada . The article reports an analysis similar to the one su bmi tted to the pan-Canadian Oncology Drug Review to support the funding request for pazopanib in mrcc , up date d with final overall survival ( os ) data from the pivotal trial2 . Economic evaluations in oncology are increasingly important to guide both policy and practice . We commend the efforts of these authors to put their su bmi tted analyses into the public domain for transparency and to support and inform future research . The base-case analysis ( using the list prices of pazopanib and sunitinib ) by Amdahl et al.1 found that , compared with sunitinib , which is the st and ard of care for first-line therapy in mrcc , first-line pazopanib is likely cost-saving . The base case analysis also suggested that pazopanib might be slightly more effective than sunitinib numerically , with an incremental gain of 0.057 life-years and 0.059 quality -adjusted life-years . Before concluding that pazopanib is dominant ( that is , it provides more benefit for a lower cost ) with respect to sunitinib , it is important to review the clinical data comparing pazopanib and sunitinib in mrcc to assess the comparative efficacy and preference-based measures of health-related quality of life ( hrqol ) associated with those agents — that is , their health utilities — to examine the face validity of the economic model in its base case . The efficacy differences between the pazopanib and sunitinib in the comparz study 3 were not statistically significant , median progression-free survival for pazopanib and sunitinib being 8.4 months [ 95 % confidence interval ( ci ) : 8.3 to 10.9 months ] and 9.5 months ( 95 % ci : 8.3 to 11.1 months ) respectively , with a hazard ratio of 1.05 ( 95 % ci : 0.90 to 1.22 ) . The study met its primary endpoint of non-inferiority in progression-free survival . No os difference was observed in the comparz study , in which median os was 28.4 months for pazopanib ( 95 % ci : 26.2 to 35.6 months ) and 29.3 months for sunitinib ( 95 % ci : 25.3 to 32.5 months ) , with a hazard ratio of 0.91 ( 95 % ci : 0.76 to 1.08 ) . At the up date d analysis , os was similar in the two groups ( hazard ratio for pazopanib vs. sunitinib : 0.92 ; 95 % ci : 0.79 to 1.06 ; p = 0.24)2 . With similar survival results for pazopanib and sunitinib based on the comparz study , one might ask , “ How did the model project an incremental gain of 0.057 life-years in favour of pazopanib ? ” The model actually projected a shorter life expectancy while patients were taking pazopanib than while their counterparts were taking sunitinib ( 0.013 life-years lost in the progression-free state ) . However , the model also projected that , after patients progressed and stopped taking pazopanib , their life expectancy was longer than it was for patients who received sunitinib ( 0.070 life-years gained in the post-progression state ) . Together , the loss and the gain result ed in a net gain in life expectancy for pazopanib , implying that the survival benefit of pazopanib acted only after progression , when patients were no longer taking pazopanib . There is no biologic basis for that phenomenon , and it likely simply reflects small numerical differences between the pazopanib and sunitinib progression-free survival and os curves , without accounting for uncertainty . Interestingly , the model also predicted that pazopanib would be more effective in at least 80 % ( or possibly all ) of the simulations despite the nonsignificant result . Although the comparz study 3 collected some hrqol measures , it did not collect preference-based measures of hrqol to allow for the calculation of quality -adjusted life-years for the purpose of economic evaluation . The pisces study 4—a r and omized , double-blind trial with a crossover design ( that is , pazopanib→sunitinib vs. sunitinib→pazopanib)—had , as its primary endpoint , an examination of patient preference for either pazopanib or sunitinib , which suggested that patients preferred pazopanib over sunitinib . However , the study had a few limitations 5 , including a relatively high proportion of the r and omly assigned patients ( 33 % ) not being evaluable for the primary endpoint , and the analysis of the pazopanib preference being based on a “ modified ” intention-to-treat population . The EQ-5D ( EuroQoL Group , Rotterdam , Netherl and s ) was also collected as the preference-based measure of hrqol in the pisces study 4 , but the EQ-5D results would have been subject to similar limitations . The data from the pisces study were used in the su bmi ssion to the pan-Canadian Oncology Drug Review . In the up date d analysis 1 , the authors conducted a regression based on patients in a trial comparing pazopanib with placebo6  , assuming that the effect of adverse events ( aes ) were driving the differences in hrqol , regardless of actual treatment received . For the analysis , the aes were grouped by severity and whether the aes were more commonly occurring in the sunitinib or the pazopanib group of the comparz trial . Using that approach , the regression model found that the health utility decrement was larger for the group of aes more commonly occurring in patients who used sunitinib than for the remaining aes more frequently occurring in patients who used pazopanib in the comparz trial . The results of the regression model were combined with the incidence and duration of aes in each treatment arm to derive the mean utility values used in the model , producing mean utility values of 0.7089 ( st and ard error : 0.0193 ) for pazopanib and 0.6832 ( st and ard error : 0.0236 ) for sunitinib , an incremental difference of 0.0257 in the progression-free period1 . Given that the comparz trial demonstrated similar efficacy and a more favourable toxicity profile for pazopanib , it is not unreasonable that the point estimate of the utility score could slightly favour the pazopanib group . However , these mean utility values were not directly derived and might be neither statistically nor clinical ly different , especially because the difference was smaller than the reported estimates of minimal important differences for health utilities ( which are in the range of 0.05–0.08 for the EQ-5D)7,8 . Thus , it is somewhat difficult to conclude from those data that pazopanib is associated with better utility than sunitinib . It might be reasonable to conservatively expect that the utilities of pazopanib and sunitinib are fairly similar given the size of the st and ard errors of the two utilities , subject to a reasonable amount of uncertainty9,10 . Given that clinical trials did not demonstrate a statistically significant survival benefit or EQ-5D health utility benefit for pazopanib over sunitinib , we feel that an appropriate interpretation could be that the study findings suggest similar efficacy and health utility for the two drugs . Reasonably , the pan-Canadian Oncology Drug Review ’s Expert Review Committee also concluded that it is reasonable to assume similar efficacy and to focus on the cost comparison between pazopanib and sunitinib in this setting 11 . We appreciate that the sensitivity analyses by Amdahl et al.1 address all the considerations discussed here , including the importance of the relative price of the two drugs . The authors demonstrate as part of their additional analyses that — assuming similar efficacy , health utility , and daily price of the two therapies — only minor cost differences remain . Thus , interpreting the analyses in light of the evidence , it appears that these two options for first-line therapy in mrcc might be largely similar and , taking into account the relative prices of the two drugs , the hope would be that , after confidential negotiations , they will also be similar in cost . In that case , having both drugs available would give patients the option to choose based on individual preference and side effect profile , especially in the case of intolerance to one of the drugs , and would ensure that health care re sources are being efficiently used . The generalizability of the study findings remains to be seen in practice . Verification from experience is needed to know whether the comparative outcomes as laid out will be realized . In Canada , jurisdictions have an important opportunity and challenge to evaluate the real-world effectiveness and cost-effectiveness of therapies in clinical practice after drugs are funded . Moreover , post-market research can provide valuable insights into practice patterns when two alternatives are funded and can possibly inform continued uncertainties such as sequencing and long-term adverse effects . We applaud the approach of the authors to share their analyses with the broader clinical and research communities , and we encourage more authors of economic evaluations created and su bmi tted to review bodies ( for example , the Canadian Agency for Drugs and Technologies in Health , the pan-Canadian Oncology Drug Review ) to follow suit . We expect that this activity will build on the principle of transparency being increasingly championed by the review organizations and will improve the rigour of the economic evidence used to inform policy . Finally , we call on the community to continue to pursue both academic merit and clinical and policy relevance by supporting the availability of peer- review ed publications of economic evaluations to inform the reimbursement review process . Ideally , it would be helpful if economic evaluations were to be published before decision-making so as to engage more stakeholders in the discussion 12 . In doing so , the clinical and economic evidence bases supporting the health technology assessment processes in Canada might be brought into better alignment , improving the robustness of decision-making and ultimately helping health care systems in Canada to provide effective and appropriate care to patients Purpose To derive children and adolescents ’ preferences for health states defined by the Chinese version of Child Health Utility 9D ( CHU9D-CHN ) instrument in China that can be used to estimate quality -adjusted life years ( QALYs ) for economic evaluation . Methods A profile case best – worst scaling ( BWS ) and a time trade-off ( TTO ) method were combined to derive a Chinese-specific tariff for the CHU9D-CHN . The BWS survey  recruited students from primary and high schools using a multi-stage r and om sampling method and was administered in a classroom setting , whilst the TTO survey adopted an interviewer-administrated conventional TTO task and was administered to a convenience sample of undergraduate students . A latent class modelling framework was adopted for analysing the BWS data . Results Two independent surveys were conducted in Nanjing , China , including a valid sample of 902 students ( mean age 13 years ) from the BWS survey and a valid sample of 38 students ( mean age 18 years ) from the TTO survey . The poolability of the best and the worst responses was rejected and the optimal result based on the best responses only . The optimal model suggests the existence of two latent classes . The BWS estimates were further re-anchored onto the QALY scale using the TTO generated health state values via a mapping approach . Conclusion This study provides further insights into the use of the BWS method to generate health state values with young people and highlights the potential different decision rules that young people may employ for determining best vs. worst choices in this context OBJECTIVES We sought to develop a mapping function from functional assessment of cancer therapy-melanoma ( FACT-M ) quality of life scores to the EuroQol-5D ( EQ-5D ) utility scores . METHODS FACT-M and EQ-5D scores were collected during a prospect i ve study of melanoma-related quality of life at a tertiary cancer care center in the United States . The study sample was divided into development and validation data sets with equal distributions by cancer stage and treatment status . Censored Least Absolute Deviation ( CLAD ) and Ordinary Least Squares ( OLS ) regression analyses were performed using the developmental data set to derive mapping functions , and model performance was examined through comparisons of residuals and measures of fit in the validation data set . Exploratory analyses examined the predictive ability of clinical factors and individual subscales . RESULTS Of 273 patients , 75 were undergoing treatment with 198 in follow-up surveillance . Relatively even distributions were observed by melanoma stage : I/II ( n = 102 ) , III ( n = 100 ) , and IV ( n = 71 ) . OLS regression result ed in a mapping function of EQ-5D = 0.0037*FACT-M+0.2238 with an R(2 ) 0.499 . CLAD regression result ed in a mapping function of EQ-5D = 0.0042*FACT-M+0.1648 with pseudo R(2 ) 0.328 . When applied to the validation data set , correlations between observed and predicted values result ed in identical coefficients ( r = 0.824 , P < 0.001 ) . Though the mapping functions were similar , residuals were smaller at the 20th , 40th , and 60th percentiles using the OLS model . The CLAD derived mapping function result ed in smaller residuals only for patients whose EQ-5D = 1 . CONCLUSIONS The OLS mapping function demonstrated better predictive ability and will facilitate the derivation of utilities when direct population preference measures are not available Background “ Patient-Reported Outcome ” ( PRO ) is used as an umbrella term for different concepts for measuring subjectively perceived health status e. g. as treatment effects . Their common characteristic is , that the appraisal of the health status is reported by the patient himself . In order to describe the informative value of PRO in Health Technology Assessment ( HTA ) first an overview of concepts , classifications and methods of measurement is given . The overview is complemented by an empirical analysis of clinical trials and HTA-reports on rheumatoid arthritis and breast cancer in order to report on type , frequency and consequences of PRO used in these documents . Methods For both issues systematic review s of the literature have been performed . The search for method ological literature covers the publication period from 1990 to 2009 , the search for clinical trials of rheumatoid arthritis and breast cancer covers the period 2005 to 2009 . Both search es were performed in the medical data bases of the German Institute of Medical Documentation and Information ( DIMDI ) . The search for HTA-reports and method ological papers of HTA-agencies was performed in the CRD- Data bases ( CRD = Centre for Review s and Dissemination ) and by h and search ing the websites of INAHTA member agencies ( INAHTA = International Network of Agencies for Health Technology Assessment ) . For all issues specific inclusion and exclusion criteria were defined . The method ological quality of r and omized controlled trials ( RCT ) was assessed by a modified version of the Cochrane Risk of Bias Tool . For the method ological part information extraction from the literature is structured by the report ’s chapters , for the empirical part data extraction sheets were constructed . All information is summarized in a qualitative manner . Results Concerning the method ological issues the literature search retrieved 158 documents ( 87 documents related to definition or classification , 125 documents related to operationalisation of PRO ) . For the empirical analyses 225 RCT ( rheumatoid arthritis : 77 ; breast cancer : 148 ) and 40 HTA-reports and method papers were found . The analysis of the method ological literature confirms the role of PRO as an umbrella term for a variety of different concepts . The newest classification system facilitates the description of PRO measures by construct , target population and the method of measurement . Steps of operationalisation involve defining a conceptual framework , instrument development , exploration of measurement properties or , possibly , the modification of existing instruments . Seven out of 59 RCT analysing the effects of antibody therapy for rheumatoid arthritis define PRO as the primary endpoint , 38 trials utilize composite measures ( ACR , DAS ) and ten trials report clinical or radiological parameters as the primary endpoint . Six out of 123 chemotherapy trials for breast cancer define PRO as the primary endpoint , while 98 trials report clinical endpoints ( survival , tumour response , progression ) in their primary analyses . Discrepancies in the number of trials result from inaccurate specifications of endpoints in the publications . This distribution is reflected in the HTA-reports : while almost all reports on rheumatoid arthritis refer to PRO , this is only the case in about half of the reports on breast cancer . Conclusions As definition and classification of PRO are concerned , coherent concepts are found in the literature . Their operationalisation and implementation must be guided by scientific principles . The type and frequency of PRO used in clinical trials largely depend on the disease analysed . The HTA-community seems to pursue the utilization of PRO proactively – in case of missing data the need for further research is stated Purpose The chronic liver disease question naire ( CLDQ ) is a frequently used liver-specific quality of life instrument , but it does not provide information on preference-adjusted health status , which is essential for cost-utility analysis . We aim ed to develop a mapping function deriving utilities from the CLDQ in primary sclerosing cholangitis ( PSC ) . Methods  Short form-6D ( SF-6D ) utilities  were calculated from SF-36 data collected in a recent prospect i ve study in which unselected patients with PSC also completed the CLDQ . Ordinary least squares ( OLS ) , generalized linear , median , and kernel regression analyses were employed to devise a mapping function predicting utilities . This was vali date d in three r and om sub sample s of the cohort and in a separate sample of PSC patients following liver transplantation .  Adjusted R2 and root-mean-square error ( RMSE ) as well as Pearson ’s r coefficients and mean absolute errors between predicted and observed values were used to determine model performance . Results Decompensated liver disease and fatigue , systemic symptoms , and emotional distress , assessed with the CLDQ , were related to worse SF-6D utilities . The final OLS prediction model explained 66.3 % of the variance in the derivation sample . Predicted and observed utilities were strongly correlated ( r = 0.807 , p < 0.001 ) , but the mean absolute error ( 0.0604 ) and adjusted RMSE ( 10.6 % ) were of intermediate size . Similar model characteristics were observed after employment of generalized linear and median regression models and at validation . Conclusions A model has been constructed , showing good validity predicting SF-6D utilities from CLDQ scores at the group level in PSC . Further testing is required to externally vali date the model Results for health-related quality of life ( HRQoL ) from clinical trials are increasingly used for clinical decision making as well as comparative eff ectiveness , health policy , and reimbursement decisions . Research suggests that HRQoL information can be used to establish treatment preferences because patients value HRQoL data and can interpret HRQoL fi ndings accurately . Trials that incorporate HRQoL as an outcome should therefore be design ed , analysed , and reported well . We did a systematic review of the literature and identifi ed 18 publications with guidelines or st and ards for reporting of HRQoL in r and omised controlled trials , which draw attention to the need for good quality in both trial design and reporting . With regard to trial design , examples of key quality criteria include : the need to use reliable and valid HRQoL measures that are appropriate for the population of interest and that include core outcomes agreed by clinicians , research ers , and patients ; timing of HRQoL assessment that is relevant to clinical interpretation of results ; minimisation of missing data ( since data are often not missing r and omly , but instead could be linked to other clinical outcomes of interest , with those most unwell not providing data ) ; and use of prespecifi ed statistical analyses to avoid multiple statistical testing and selective reporting of results . Given these and other requirements for quality st and ards in clinical trial design , many authors have recommended st and ards for HRQoL reporting so that readers of trial reports can ascertain whether quality st and ards have been reached . Such st and ard criteria have included , for example , the provision of a clear rationale for the domains of HRQoL assessment ( eg , specifi c symptoms such as pain , or functions such as activity levels ) and the corresponding choice of HRQoL instrument , with cited evidence of the instrument ’s validity and a statement about the timing of HRQoL assessment s used in the trial . Trials should report baseline compliance and the extent of subsequent missing data , since reports that omit details about the amount of missing data , or report substantial missing data , should be interpreted with caution . Type 1 statistical errors , result ing from multiple statistical testing , can be addressed by the requirement that trial protocol s prespecify the principal HRQoL postulated outcomes , and their respective timepoints for analysis and reporting in the fi nal trial publication . Finally , reporting of HRQoL data in a comprehensible , clinical ly applicable format , and in the context of other trial outcomes might better promote the use of HRQoL data in practice . Despite these existing recommendations , a systematic review of 794 r and omised trials undertaken between 2002 and 2008 that reported HRQoL outcomes across a range of medical conditions showed that only 56 % of trials provided a rationale for the selected outcome measure , 50 % provided an HRQoL hypothesis , 28 % provided information about missing data , and 36 % did not discuss the HRQoL fi ndings in the context of the other trial outcomes . The review noted that when HRQoL data 8 Ezzati M , Kammen DM . Indoor air pollution from biomass combustion and acute respiratory infections in Kenya : an exposure-response study . Lancet 2001 ; 358 : 619–24 . 9 Naeher LP , Smith KR , Leaderer BP , Mage D , Grajeda R. Indoor and outdoor PM2.5 and CO in high and low-density Guatemalan villages . J Expo Anal Environ Epidemiol 2000 ; 10 : 544–51 . 10 Barraza-Villarreal A , Sunyer J , Hern and ez-Cadena L , et al. Air pollution , airway infl ammation , and lung function in a cohort study of Mexico City schoolchildren . Environ Health Perspect 2008 ; 116 : 832–38 . 11 Moshammer H , Hoek G , Luttmann-Gibson H , et al.  Parental smoking and lung function in children : an international study . Am J Respir Crit Care Med 2006 ; 173 : 1255–63 . 12 Miller RL , Daswani M , Lendor C. Prenatal exposure to air pollution and respiratory outcomes in children . In : Jeorgenson NA , ed . Passive smoking and health research . New York : Nova Science Publishers , 2007 : 283–96 BACKGROUND Condition-specific measures are frequently used to assess the health-related quality of life of people with multiple sclerosis ( MS ) . Such measures are unsuitable for use in economic evaluations that require estimates of cost per quality -adjusted life-year because they are not based on preferences . OBJECTIVES To report the estimation of a preference-based single index for an eight-dimensional instrument for MS , the Multiple Sclerosis Impact Scale - Eight Dimensions ( MSIS-8D ) , derived from an MS-specific measure of health-related quality of life , the 29-item Multiple Sclerosis Impact Scale ( MSIS-29 ) . METHODS We elicited preferences for a sample of MSIS-8D states ( n = 169 ) from a sample ( n = 1702 ) of the UK general population . Preferences were elicited using the time trade-off technique via an Internet-based survey . We fitted regression models to these data to estimate values for all health states described by the MSIS-8D . Estimated values were assessed against MSIS-29 scores and values derived from generic preference-based measures in a large , representative sample of people with MS . RESULTS Participants reported that the time trade-off questions were easy to underst and . Observed health state values ranged from 0.08 to 0.89 . The best-performing model was a main effects , r and om effects model ( mean absolute error = 0.04 ) . Validation analyses support the performance of the MSIS-8D index : it correlated more strongly than did generic measures with MSIS-29 scores , and it discriminated effectively between subgroups of people with MS . CONCLUSIONS The MSIS-8D enables health state values to be estimated from the MSIS-29 , adding to the methods available to assess health outcomes and to estimate quality -adjusted life-years for MS for use in health technology assessment and decision-making context There remains disagreement about the preferred utility-based measure of health-related quality of life for use in constructing quality -adjusted life years ( QALYs ) . The recent development of a new measure , the SF-6D , has highlighted this issue . The SF-6D and EuroQol EQ-5D measure health-related utilities on a scale where 0 represents death and 1 represents full health , and both have utility scores generated from r and om sample s of the general UK population . This study explored whether , in a large sample of liver transplant patients , the two instruments provide similar results . The empirical data highlight important variation in the results generated from the use of the two instruments . The data are consistent with a view that the SF-6D does not describe health states at the lower end of the utility scale but is more sensitive than EQ-5D in detecting small changes towards the top of the scale OBJECTIVE Hip fractures are a major cause of morbidity for older women , which result in impaired health related quality of life ( HRQOL ) . Few studies have prospect ively evaluated the effect of hip fractures in women on HRQOL with different health state preference measures . We compared how 4 different preference measures change in women post-hip fracture and evaluated the responsiveness of the preference measures . We also compared HRQOL in women with recent hip fractures to a control sample at baseline and to normative Canadian data at followup . METHODS Health status measures [ the Medical Outcomes Study Short Form-36 ( SF-36 ) ] and preferences ( direct and indirect ) of women over age 50 years with hip fractures were measured at baseline and at 3 and 9 months . Baseline preferences [ Health Utilities Index ( HUI ) , Feeling Thermometer , St and ard Gamble , and SF-36 ] were obtained from women without hip fractures for comparison . Independent sample t tests were used to compare baseline scores of fracture and nonfracture controls . Correlations between preference and health status measures were assessed and repeated measures ANOVA was used to assess change in health status and preferences over time . RESULTS Health status and preference measures were lower in women with hip fractures in comparison to nonfracture controls . After 9 months , the SF-36 , HUI , Feeling Thermometer , and SF-6D scores improved significantly . Values for the SF-36 remained lower than an age-matched normative sample . The HUI and SF-6D were sensitive to change over time , but the St and ard Gamble was not . CONCLUSION HRQOL and preference measures improve over time in women with recent hip fractures , with the majority of the change occurring in the initial 3 months . Our results suggest that the HUI and SF-6D are valid measures to assess change over time post-hip fracture Background There is increased interest in developing multidisciplinary ambulatory care models of service delivery to manage patients with complex chronic diseases . These programs are expensive and given limited re sources it is important that care is targeted effectively . One potential screening strategy is to identify individuals who report the greatest decrement in health related quality of life ( HRQoL )  and thus greater need . The aim of this study was to explore the relationship between HRQoL , comorbid conditions and acute health care utilisation . Methods A prospect i ve , longitudinal cohort design was used to evaluate the impact of  HRQoL  on acute care utilisation rates over three-years of follow-up . Participants were enrolled in chronic disease management programs run by a metropolitan health service in Australia . Baseline data was collected from 2007–2009 and follow-up data until 2012 . Administrative data was used to classify patients ’ primary reasons for enrolment , number of comorbidities ( Charlson Score ) and presentations to acute care . At enrolment ,  HRQoL  was measured using  the Assessment of Quality of Life ( AQoL ) instrument  , for analysis AQoL scores were dichotomised at two st and ard deviations below the population norm . Results There were 1999 participants ( 54 % male ) with a mean age of 63 years ( range 18–101 ) , enrolled in the study . Participants ’ primary health conditions at enrolment were : diabetes 915 ( 46 % ) , chronic respiratory disease 463 ( 23 % ) , cardiac disease 260 ( 13 % ) , peripheral vascular disease , and 181 ( 9 % ) and aged care 180 ( 9 % ) . At 1-year multivariate logistic regression models demonstrated that AQOL utility score was not predictive of acute care presentations after adjusting for comorbidities . Over 3-years an AQoL utility score in the lowest quartile was predictive of both ED presentation ( OR 1.58 , 95 % CI , 1.16–2.13 , p = 0.003 ) and admissions ( OR 1.67 , 95 % CI.1.21 to 2.30 , p = 0.002 ) after adjusting for differences in age and comorbidities . Conclusion This study found that both HRQoL and comorbidities were predictive of subsequent acute care attendance over 3-years of follow-up . At 1-year , comorbidities was a better predictor of acute care representation than HRQoL. To maximise benefits , programs should initially focus on medical disease management , but subsequently switch to strategies that enhance health independence and raise Background Research ers are increasingly investigating the potential for ordinal tasks such as ranking and discrete choice experiments to estimate QALY health state values . However , the assumptions of r and om utility theory , which underpin the statistical models used to provide these estimates , have received insufficient attention . In particular , the assumptions made about the decisions between living states and the death state are not satisfied , at least for some people . Estimated values are likely to be incorrectly anchored with respect to death ( zero ) in such circumstances . Methods Data from the Investigating Choice Experiments for the preferences of older people CAPability instrument ( ICECAP ) valuation exercise were analysed . The values ( previously anchored to the worst possible state ) were rescaled using an ordinal model proposed previously to estimate QALY-like values . Bootstrapping was conducted to vary artificially the proportion of people who conformed to the conventional r and om utility model underpinning the analyses . Results Only 26 % of respondents conformed unequivocally to the assumptions of conventional r and om utility theory . At least 14 % of respondents unequivocally violated the assumptions . Varying the relative proportions of conforming respondents in sensitivity analyses led to large changes in the estimated QALY values , particularly for lower-valued states . As a result these values could be either positive ( considered to be better than death ) or negative ( considered to be worse than death ) . Conclusion Use of a statistical model such as conditional ( multinomial ) regression to anchor quality of life values from ordinal data to death is inappropriate in the presence of respondents who do not conform to the assumptions of conventional r and om utility theory . This is clearest when estimating values for that group of respondents observed in valuation sample s who refuse to consider any living state to be worse than death : in such circumstances the model can not be estimated . Only a valuation task requiring respondents to make choices in which both length and quality of life vary can produce estimates that properly reflect the preferences of all respondents BACKGROUND Country-specific data on re source use and costs associated with Alzheimer 's disease ( AD ) help inform governments about the increasing need for medical and financial support as the disease increases in prevalence . METHODS GERAS II , a prospect i ve observational study , assessed re source use , costs , and health-related quality of life ( HRQoL ) among patients with AD and their caregivers in Spain . Community-dwelling patients aged ≥55 years with probable AD , and their primary caregivers , were recruited by study investigators during routine clinical practice and assessed as having mild , moderate , or moderately severe/severe ( MS/S ) AD dementia based on patient Mini-Mental State Examination scores .  Costs of AD were calculated by applying costs to re source -use data obtained in caregiver interviews using the Re source Utilization in Dementia instrument . Total societal costs included patients ' health and social care costs and caregiver informal care costs . Baseline results are presented . RESULTS Total mean monthly societal costs/patient ( 2013 values ) were € 1514 for mild ( n = 116 ) , € 2082 for moderate ( n = 118 ) , and € 2818 for MS/S AD dementia ( n = 146 ) ( p value < 0.001 between groups ) . Caregiver informal care costs comprised most of the total societal costs and differed significantly between groups ( € 1050 , € 1239 , € 1580 , respectively ; p value = 0.013 ) , whereas patient healthcare costs did not . Across AD dementia severity groups , patient HRQoL ( measured by proxy ) decreased significantly ( p value < 0.001 ) , caregiver subjective burden significantly increased ( p value < 0.001 ) and caregiver HRQoL was similar . CONCLUSIONS Societal costs associated with AD in Spain were largely attributable to caregiver informal care costs and increased with increasing AD dementia severity For many years , the National Institute for Health and Care Excellence ( NICE ) has recommended use of the EQ-5D-3L ( 3L ) [ 1 ] and its value set for the UK [ 2 ] . Since 2011 , an exp and ed-level instrument , the EQ-5D-5L ( 5L ) , has been available [ 3 ] and value sets now exist to support its use , including a value set for Engl and [ 4 , 5 ] . This poses a challenge for NICE . Should it recommend the 5L rather than the 3L ? This is neither a trivial nor merely academic matter : the choice of whether to use the 5L ( and English value set ) or the 3L ( and UK value set ) is likely to impact estimates of quality -adjusted life-years ( QALYs ) and incremental cost-effectiveness ratios ( ICERs ) . The size and direction of that impact will depend on the disease and the nature of the health problems . In general , where technologies improve self-reported health , estimates of QALY gains will often be smaller with the 5L [ 6 ] . In contrast , where technologies extend the length of life , estimates of QALY gains will be higher ( to varying degrees ) : each year of additional life is assigned a higher utility . The ultimate impact on health technology assessment ( HTA ) will depend on whether the differences between the 3L and 5L push ICERs from one side of the cost-effectiveness threshold to the other . Given the implication s for NICE ’s technology appraisal process , and other decisions informed by EQ-5D data , the Department of Health for Engl and has called for an independent validation of the 5L value set , given its relevance to policy [ 7 ] . In 2017 , NICE released a ‘ position statement ’ [ 8 ] stating that : The 3L value set continues to be used for reference-case analyses . Where 5L data have been collected , reference-case analyses should calculate utilities by mapping the 5L descriptive system data onto the 3L value set , using the van Hout et al. [ 9 ] mapping function . NICE supports sponsors of prospect i ve clinical studies continuing to use the 5L to collect data on quality of life . A further position statement is planned for August 2018 , to be informed by evidence from various studies underway . These include studies commissioned by the English Department of Health to investigate the implication s for past NICE technology appraisal s had the 5L been used , and to collect 3L and 5L data in parallel to further improve functions for mapping from one to the other . Other studies , funded by the EuroQol Group , are also underway , investigating various aspects of the relationship between the 3L and 5L across disease areas . The 3L and its UK value set has occupied a special place in NICE ’s technology appraisal process since its inception , therefore any transition will inevitably pose challenges ; for example , reconciling potential inconsistencies between past and future decisions . Given that evidence will continue to be su bmi tted using both the 3L and 5L for years to come , if both value sets are able to be used , there is a risk of inconsistency between decisions being made in the future . HTA in other countries may also face similar issues . Given the difficulties with any transition away from the 3L , is there a case for NICE to adopt the 5L as its preferred instrument ? Papers in this issue of Pharmacoeconomics , which are cited in this commentary , address that question by investigating comparative performance of the 3L and 5L 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 RATIONALE , AIMS , AND OBJECTIVES Although nonpreference-based disease-specific measures are widely used in clinical studies , they can not generate utilities for economic evaluation . A solution to this problem is to estimate utilities from disease-specific instruments using the mapping function . This study aim ed to develop a transformation model for mapping the pruritus-visual analog scale ( VAS ) to the EuroQol 5-Dimension 3-Level ( EQ-5D-3L ) utility index in pruritus . METHODS A cross-sectional survey was conducted with a sample ( n = 268 ) drawn from the general population of South Korea . Data were r and omly divided into 2 groups , one for estimating and the other for validating mapping models . To select the best model , we developed and compared 3 separate models using demographic information and the pruritus-VAS as independent variables . The predictive performance was assessed using the mean absolute deviation and root mean square error in a separate data set . RESULTS Among the 3 models , model 2 using age , age squared , sex , and the pruritus-VAS as independent variables had the best performance based on the goodness of fit and model simplicity , with a log likelihood of 187.13 . The 3 models had similar precision errors based on mean absolute deviation and root mean square error in the validation data set . No statistically significant difference was observed between the mean observed and predicted values in all models . CONCLUSIONS In conclusion , model 2 was chosen as the preferred mapping model . Outcomes measured as the pruritus-VAS can be transformed into the EQ-5D-3L utility index using this mapping model , which makes an economic evaluation possible when only pruritus-VAS data are available Abstract Purpose : To develop a mapping algorithm for the estimation of EQ-5D-based utility scores from observed 25-item National Eye Institute Visual Functioning Question naire ( NEI VFQ-25 ) scores , a disease-specific , patient-reported outcome measure used in several retinal disorders to evaluate vision-specific functioning . Methods : The data set comprised 951 paired EQ-5D/NEI VFQ-25 observations from 344 patients in RESTORE , a 12-month , r and omized , double-blind trial in individuals with visual impairment due to diabetic macular edema .  EQ-5D index scores ( utilities ) were calculated based on the UK tariff . We evaluated 11 models using predictor sets based on the NEI VFQ-25 subscales to estimate utility as a function of NEI VFQ-25 score , based on four modeling techniques . Model performance was assessed by 10-fold cross-validation comparing root mean squared error ( RMSE ) , mean absolute error ( MAE ) and correlation with EQ-5D score ( Pearson and Spearman correlation coefficients ) . Results : Mapping results were similar across all techniques and predictor sets . The reverse two-part generalized estimating equation model used fewest predictors and had the best predictive performance ( RMSE 0.200 , MAE 0.140 ) . Predicted and original EQ-5D values were not strongly correlated ( squared Spearman correlation coefficient , 0.34 ) . Conclusions : Although mapping disease-specific instruments to EQ-5D utilities is a preferred method by some reimbursement bodies , finding an appropriate mapping equation is not straightforward . In this study , mapping NEI VFQ-25 scores to EQ-5D utilities provided low predictive power , independent of the modeling methodology applied , suggesting an inability of the EQ-5D to discriminate vision-related activities , and highlighting that mapping exercises may lead to inaccurate utility values that do not represent patients ’ preferences The purpose of this project was to conduct a systematic review to identify instruments design ed to evaluate the quality of r and omized controlled trials ( RCTs ) of natural health products ( NHPs ) . Instruments were examined for inclusion of items assessing methods , identity and content of the NHP , generalizability of results and instructions for use . Online data bases , websites , textbooks and reference lists were search ed to identify instruments . Relevance assessment and data extraction of articles were completed by two investigators and disagreements were settled by the third investigator . Data were analyzed using descriptive statistics . Of the 4442 citations identified , 29 were potentially relevant with 16 meeting the criteria for inclusion . None of the instruments stated they were vali date d ; content in the four areas of interest varied considerably . The most common items included r and omization sequence generation ( 100 % ) , blinding ( 100 % ) , allocation concealment ( 75 % ) and participant flow ( 75 % ) . Only nine of the NHP instruments included at least one item to appraise the specific content of the NHP . The CONSORT Statement for Herbal Interventions most closely addressed the four areas of interest ; however , this instrument was specific for herbs . There is a need for the development of a vali date d instrument for assessment of the quality of RCTs that would be useful for herbs as well as other NHPs Background . Generic preference-based measures of health may not adequately cover the impact of some conditions . There is therefore increasing interest in developing condition-specific preference-based measures . Objectives . The purpose of this study was to estimate a preference-based measure from a condition-specific measure of health for urinary incontinence , the 21-item King 's Health Question naire , for use in economic evaluation . Methods . The King 's Health Question naire ( KHQ ) was revised into a 5-dimensional health state classification amenable to valuation using items selected using psychometric evidence . Forty-nine states were valued using st and ard gamble by a representative sample of patients with urinary incontinence attending UK hospital outpatient clinics . Each respondent was asked to value 9 health states . Models have been estimated for predicting health state valuations for all 1024 states defined by the KHQ classification . The modeling had to cope with the clustering of data by respondent and its skewed distribution . Results . In total , 110 usable interviews were obtained from 169 patients approached to participate in the study . These responders generated 959 health state valuations . Mean health state values ranged from 0.77 to 0.98 . Models were estimated using mean health state values and r and om effects models of individual-level health state values . These models generated robust estimates of the ` main effects , ` and in general , the results support the ordinality of the KHQ health state classification . There were problems modeling interaction effects , and a number of alternatives were explored . Conclusion . The recommended model for estimating a preference-based measure from the condition-specific KHQ is presented BACKGROUND Previous work highlighted a number of method ological constraints when reporting health-related quality of life ( HRQOL ) outcomes from r and omized controlled trials ( RCTs ) . Given this , the objective of this study was to investigate whether the quality of such HRQOL reports has improved over time . MATERIAL S AND METHODS On the basis of a predefined set of criteria , 159 RCTs with a HRQOL end point , published between 1990 and 2004 were identified and analyzed . Each study was evaluated by a number of issues ( e.g. sample size and industry sponsorship ) and by the " minimum st and ard checklist for evaluating HRQOL outcomes in cancer clinical trials " . RESULTS The quality of HRQOL reports , as measured by the overall checklist score , was independently related to more recently published studies ( P < 0.0001 ) . This relationship was independent of industry funded , HRQOL end point ( primary versus secondary ) , cancer disease site , size of the study and HRQOL difference between treatment arms . While only 39.3 % of studies published between 1990 and 2000 ( 89/159 RCTs ) were identified as being probably robust , thus likely to support clinical decision making , this percentage was 64.3 % for studies published after 2000 ( 70/159 RCTs ) . CONCLUSION Since we found a significant learning curve in HRQOL trial reporting since 1990 , it can be expected that HRQOL data will increasingly impact on clinical decision making and treatment policies in the near future Background A discipline which critically looks at the evidence for practice should itself be critically examined . Credible evidence for the effectiveness of training in evidence -based healthcare ( EBHC ) is essential . We attempted to summarise the current knowledge on evaluating the effectiveness of training in EBHC while identifying the gaps . Methods A working group of EBHC teachers developed a conceptual framework of key areas of EBHC teaching and practice in need of evidence mapped to appropriate methods and outcomes . A literature search was conducted to review the current state of research in these key areas . Studies of training interventions that evaluated effectiveness by considering learner , patient or health system outcomes in terms of knowledge , skills , attitude , judgement , competence , decision-making , patient satisfaction , quality of life , clinical indicators or cost were included . There was no language restriction . Results Of 55 articles review ed , 15 met the inclusion criteria : six systematic review s , three r and omised controlled trials and six before-after studies . We found weak indications that undergraduate training in EBHC improves knowledge but not skills , and that clinical ly integrated postgraduate teaching improves both knowledge and skills . Two r and omised controlled trials reported no impact on attitudes or behaviour . One before-after study found a positive impact on decision-making , while another suggested change in learners ' behaviour and improved patient outcome . We found no studies assessing the impact of EBHC training on patient satisfaction , health-related quality of life , cost or population -level indicators of health . Conclusions Literature evaluating the effectiveness of training in EBHC has focused on short-term acquisition of knowledge and skills . Evaluation design s were method ologically weak , controlled trials appeared inadequately powered and systematic review s could not provide conclusive evidence owing to weakness of study design Background : Social anxiety disorder ( SAD ) is associated with substantial reduction in health-related quality of life ( HRQoL ) .  Escitalopram has proven efficacy in the short-term treatment of SAD and prevention of relapse . Objectives : To determine whether the clinical effects of treatment translated into HRQoL benefits and to investigate costs of SAD treatment . Methods : Data on HRQoL and re source utilisation were collected in a previously published clinical trial of escitalopram in relapse prevention . Among 517 patients , 371 responded to 12 weeks of open-label treatment with escitalopram  and were r and omised to escitalopram or placebo for 24 weeks .  HRQoL was assessed using the short form (SF)-36 instrument and SF-6D utilities ( preference-based index scores for overall HRQoL ) were calculated . Costs were calculated for responders over the acute phase and for non-relapsed patients over the continuation phase , applying UK unit costs . Results : Health-related quality of life was significantly improved after the acute phase when compared with baseline . The SF-6D utility increased by 0.047 in responders ( p < 0.0001 ) and 0.021 in non-responders ( p = 0.0005 ) . Healthcare costs were non-significantly lower in acute phase than during pre study phase ( p = 0.0587 from NHS perspective ) , as were productivity costs ( p = 0.1440 ) . HRQoL at last visit was lower in relapsed than non-relapsed patients . The difference in utility was −0.026 ( p = 0.0007 ) . Healthcare and productivity costs were non-significantly lower in the escitalopram group than in the placebo group . Conclusions : Both effective acute treatment of SAD and prevention of relapse with escitalopram are associated with significant HRQoL benefits . Despite some limitations , the cost analysis suggests that savings in physician-visits and inpatient care may offset drug acquisition costs Background . SF-6D utility weights are conventionally produced using a st and ard gamble ( SG ) . SG-derived weights consistently demonstrate a floor effect not observed with other elicitation techniques . Recent advances in discrete choice methods have allowed estimation of utility weights . The objective was to produce Australian utility weights for the SF-6D and to explore the application of discrete choice experiment ( DCE ) methods in this context . We hypothesized that weights derived using this method would reflect the largely monotonic construction of the SF-6D . Methods . We design ed an online DCE and administered it to an Australia-representative online panel ( n = 1017 ) . A range of specifications investigating nonlinear preferences with respect to additional life expectancy were estimated using a r and om-effects probit model . The preferred model was then used to estimate a preference index such that full health and death were valued at 1 and 0 , respectively , to provide an algorithm for Australian cost-utility analyses . Results . Physical functioning , pain , mental health , and vitality were the largest drivers of utility weights . Combining levels to remove illogical orderings did not lead to a poorer model fit . Relative to international SG-derived weights , the range of utility weights was larger with 5 % of health states valued below zero . Conclusion s. DCEs can be used to investigate preferences for health profiles and to estimate utility weights for multi-attribute utility instruments . Australian cost-utility analyses can now use domestic SF-6D weights . The comparability of DCE results to those using other elicitation methods for estimating utility weights for quality -adjusted life-year calculations should be further investigated Background To facilitate the discussion on the increasing number of total hip replacements ( THR ) and their effectiveness , we apply a joint evaluation of hospital case costs and health outcomes at the patient level to enable comparative effectiveness research ( CER ) based on the preoperative health state . Methods In 2012 , 292 patients from a German orthopedic hospital participated in health state evaluation before and 6 months after THR , where health-related quality of life ( HRQoL ) and disease specific pain and dysfunction were analyzed using EQ-5D and WOMAC scores . Costs were measured with a patient-based DRG costing scheme in a prospect i ve observation of a cohort . Costs per quality -adjusted life year ( QALY ) were calculated based on the preoperative WOMAC score , as preoperative health states were found to be the best predictors of QALY gains in multivariate linear regressions . Results Mean inpatient costs of THR were 6,310 Euros for primary replacement and 7,730 Euros for inpatient lifetime costs including revisions . QALYs gained using the U.K. population preference-weighted index were 5.95 . Lifetime costs per QALY were 1,300 Euros . Conclusions The WOMAC score and the EQ-5D score before operation were the most important predictors of QALY gains . The poorer the WOMAC score or the EQ-5D score before operation , the higher the patient benefit . Costs per QALY were far below common thresholds in all preoperative utility score groups and with all underlying calculation method ologies OBJECTIVE The goal of this study was to estimate an algorithm to convert responses to the Functional Assessment of Cancer Therapy - General ( FACT-G ) to time trade-off ( TTO ) utilities based on utilities for current health elicited from cancer patients . METHODS Data for 1433 cancer patients were r and omly separated into construction and validation sample s. Four FACT-G questions were selected for inclusion based on correlation with Eastern Clinical Oncology Group - Performance Status ( ECOG-PS ) scores and TTO utilities . Item response theory was used to collapse response categories . Ordinary least squares regression with the constant constrained to one was used to estimate the algorithm . RESULTS The algorithm estimated mean utility for the full validation sample within three points of observed mean utility ( 0.805 vs. 0.832 , P < 0.01 ) . Mean utilities were well predicted ( mean absolute difference < 0.03 , P > 0.05 ) for most subgroups defined by ECOG-PS and Short Form-36 physical functioning scores , and responses to the FACT-G overall quality of life item . Nevertheless , the algorithm systematic ally overpredicted utilities for poorer health states . CONCLUSIONS A FACT-G-based algorithm of cancer patient utilities was developed that estimates group mean utility scores with accuracy comparable to other indirect preference-based measures of health-related quality of life . Patient-based preferences for health outcomes of cancer treatment may be useful in multiple situations , such as managing re sources within cancer centers and in underst and ing health states preferences among cancer experienced patients before and after treatment OBJECTIVES To develop a model to predict  EuroQol five-dimensional question naire ( EQ-5D ) values from clinical chronic obstructive pulmonary disease ( COPD ) question naire ( CCQ ) scores . METHODS We used data from three clinical trials ( the R and omized Clinical Trial on Effectiveness of Integrated COPD Management in Primary Care [ RECODE ] , the Assessment Of Going Home Under Early Assisted Discharge [ GO-AHEAD ] , and the Health Status Guided COPD Care [ MARCH ] ) . Data were r and omly split into an estimation sample and a validation sample . The conceptual similarity between patient-reported CCQ and preference-based EQ-5D scores was assessed using correlation and principal-component analysis . Different types of models were estimated with increasing complexity . We selected the final models on the basis of mean absolute error and root mean square error when comparing predicted and observed values from the same population ( internal validity ) and from different trial population s ( external validity ) . We also developed models for different country-specific EQ-5D value sets . RESULTS The principal-component analysis showed that the CCQ domains functional state and mental state are associated with four dimensions of the EQ-5D . The EQ-5D dimension pain/discomfort formed a separate construct on which no CCQ item loaded . The mean observed EQ-5D values were not significantly different from the mean predicted EQ-5D values in internal validation sample s but did significantly differ in external validation sample s. The models underestimated EQ-5D values in milder health states and overestimated them in more severe health states . The predictive ability of the models was similar across different EQ-5D value sets . CONCLUSIONS The models can predict mean EQ-5D values that are similar to observed mean values in a similar population . The overestimating/underestimating of the low/high EQ-5D values , however , limits its use in Markov models . Therefore , mapping should be used cautiously Background Most tools for estimating utilities use clinical trial data from general health status models , such as the 36-Item Short-Form Health Survey ( SF-36 ) . A disease-specific model may be more appropriate . The objective of this study was to apply a disease-specific utility mapping function for schizophrenia to data from a large , 1-year , open-label study of long-acting risperidone and to compare its performance with an SF-36-based utility mapping function . Methods Patients with schizophrenia or schizoaffective disorder by DSM-IV criteria received 25 , 50 , or 75 mg long-acting risperidone every 2 weeks for 12 months . The Positive and Negative Syndrome Scale ( PANSS ) and SF-36 were used to assess efficacy and health-related quality of life . Movement disorder severity was measured using the Extrapyramidal Symptom Rating Scale ( ESRS ) ; data concerning other common adverse effects ( orthostatic hypotension , weight gain ) were collected . Transforms were applied to estimate utilities . Results A total of 474 patients completed the study . Long-acting risperidone treatment was associated with a utility gain of 0.051 using the disease-specific function . The estimated gain using an SF-36-based mapping function was smaller : 0.0285 . Estimates of gains were only weakly correlated ( r = 0.2 ) . Because of differences in scaling and variance , the requisite sample size for a r and omized trial to confirm observed effects is much smaller for the disease-specific mapping function ( 156 versus 672 total subjects ) . Conclusion Application of a disease-specific mapping function was feasible . Differences in scaling and precision suggest the clinical ly based mapping function has greater power than the SF-36-based measure to detect differences in utility PURPOSE As a first step in the development of a health-related quality of life ( HRQOL ) instrument , we conducted in-depth interviews to identify the specific concerns of adults with strabismus . DESIGN Prospect i ve cross-sectional study . METHODS Thirty adults with strabismus , 17 with diplopia , and 13 without were recruited .  Individual interviews , using 11 open-ended questions , were audiotaped , transcribed , and transcripts review ed independently by three investigators . Phrases regarding how strabismus affected everyday life were grouped into topic areas and the frequency of each topic analyzed for subjects with and without diplopia . RESULTS A total of 1,508 phrases were extracted : 207 ( 14 % ) of 1,508 were excluded because they did not pertain to HRQOL . From the remaining 1,301 phrases , 48 topic areas were apparent . For patients with diplopia , the most frequently occurring topics were : nonspecific negative feeling ( 15/17 ; 88 % ) ( " really hard " ) ; general disability ( 15/17 ; 88 % ) ( " affects everything " ) ; and driving ( 14/17 ; 82 % ) . In those without diplopia , the most frequently mentioned topics were appearance to others ( 12/13 ; 92 % ) ( " people notice my eyes " ) followed by problems with eye contact ( 10/13 ; 77 % ) and interpersonal relationships ( 10/13 ; 77 % ) . Of the topics that were common to both groups ( n = 42 ) , two of the most frequent were driving and nonspecific negative feeling . CONCLUSIONS Multiple individual interviews revealed many topics that negatively affect quality of life in patients with strabismus . The frequency and type of concerns confirm the importance of HRQOL assessment as an important aspect of strabismus management The main goal of current pain management approaches is to increase the patients ' quality of life by improving pain coping skills and by reducing the levels of disability in daily life , often despite persistent pain . Direct measurement of quality of life is of crucial importance in economic evaluation research , in which not only is the estimation of financial costs and benefits included , but so is the evaluation of costs and benefits in terms of changes in health states . The purpose of this study is to compare the psychometric qualities of two instruments for assessing patients ' utilities , the  rating scale ( RS )  and the st and ard gamble ( SG ) . Such instruments are design ed for their application in economic evaluation research , but have seldomly been used in chronic pain trials . Both methods provide a single measure between 0 and 1 . The relationship between these utility measures and descriptive and domain-specific quality of life measures was examined in 133 fibromyalgia patients and 148 patients with chronic non-specific low back pain .  Mean utility score at baseline was 0.43 with the RS and 0.78 for the SG . The correlation between both methods was found to be poor ( r = 0.21 ) . Both measures appeared to be fairly stable in a 2-week test-retest period ( intra class correlation coefficient ( ICC ) = 0.74 and 0.77 ) . Scores on the description of patient 's own health on six domains , global assessment of change and domain specific measures correlated moderately with the RS scores and low with the SG . Multiple regression analyses demonstrated that 32 % of the variance in RS values and only 13 % of the variance in SG utilities could be explained by domain-specific measures . These results suggest an acceptable construct validity for the RS but insufficient construct validity for the SG . Valuations of ones own health appear only partially to be related to the assessment of the pain-specific measures and measures of distress . It can be concluded that the RS and domain-specific measures assess partly different , but nevertheless complementary aspects of health-related quality of life . It is therefore recommended to include in economic evaluation studies both domain-specific measures and valuation measures . Finally , in chronic musculoskeletal pain patients , RS scores were found to be more responsive in detecting significant changes in preferences than SG scores . For use in patients with chronic musculoskeletal pain , the RS is preferred to the SG for establishing accurate decisions about the impact of new interventions on their health outcomes Background . Currently there are no reported cancer-specific health state valuations in low- and middle-income countries using a vali date d preference-based measure . The EORTC-8D , a cancer-specific preference-based measure , has 81,920 health states and is useful for economic evaluations in cancer care . The aim of this study was to develop a utility algorithm to value EORTC-8D health states using preferences derived from a representative population sample in Sri Lanka . Methods . The time-tradeoff method was used to elicit preferences from a general population sample of 780 in Sri Lanka . A block design of 85 health states , with a time horizon of 10 years , was used for the direct valuation . Data were analyzed using generalized least squares with r and om effects . All respondents with at least one logical inconsistency were excluded from the analysis . Results . After logical inconsistencies were excluded , 4520 observations were available from 717 respondents for the analysis . The preferred model specified main effects with an interaction term for any level 4 or worse descriptor within a health state . Worsening of physical functioning had a substantially greater utility decrement than any other dimension in this population . Limitations are that the data collection could not include the whole country and that females formed a large part of the sample . Conclusions . Preference weights for EORTC-8D health states for Sri Lanka have been derived : These will be very useful in economic evaluations of cancer-related interventions in a range of low- and middle-income countries Background . Health-related quality of life can be measured by patients ' health preferences ( utilities or values ) . No method for measuring health state preferences has been st and ardized for children with arthritis or other musculoskeletal disorders ( MSKDs ) . Such a method is needed for economic evaluations of current and new pediatric treatments . Objectives . 1 ) To assess the feasibility of utility measurements in children with MSKDs , 2 ) to test the validity of the Health Utility Index ( HUI ) for these children , 3 ) to assess whether rating scale values can be mathematically converted into meaningful st and ard gamble ( SG ) utilities , and 4 ) to study whether parents can act as proxies for their children with respect to health state preferences . Methods . Eighty parents of children with MSKDs were consecutively sample d. Their children , if 8 years of age or older ( n = 55 ) , were studied concurrently . Utilities of current health states were obtained by using the SG and the HUI in r and om order . In addition , health state preferences were assessed using categorical and analog rating scales . Traditional nonutility measures of health status ( the Childhood Health Assessment Question naire [ CHAQ ] and the Activities Scale for Kids [ ASK ] ) were also completed . Intraclass correlation coefficients ( ICCs ) were calculated to assess concordance between the different utility measures and also between the ratings of the parents and their children . Results . Children 8 years of age or older were able to express the strength of their health state preferences using the HUI and rating scales . Children older than 10 years of age were able to use the SG method . The health state utilities of the parents were higher than those of their children . The utilities varied widely depending on the elicitation method . The expected high agreement between the SG and the HUI was not found ( ICC = 0.028 for parents , ICC = 0.016 for patients ) . Unlike the SG , the global utilities derived from the HUI agreed better with preferences derived from rating scales ( ICC = 0.23 - 0.25 ) and correlated with traditional health status measures ( with CHAQ , r = -0.56 ; with ASK , r = 0.46 ) both for parents and children . It was not possible to mathematically convert rating scale preferences into SG utilities . The SG utilities were unrelated to results from the rating scales , the CHAQ , and the ASK . Especially for parents , the SG utilities were very high , even when ratings of the other measures indicated poor health . Conclusions . Although it is possible to measure health utilities for children with MSKDs , the results are highly method dependent . The properties of the HUI in this population are more like those of the traditional health status measures rather than those of the SG . Preferences derived from rating scales , although easily performed , can not readily be converted into SG utilities . Parents ' ratings for their children are impaired by risk aversion
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 .