title: Mapping of the DLQI scores to EQ-5D utility values using ordinal logistic regression Mapping utility scores from the Barthel index Mapping SF-36 onto the EQ-5D index: how reliable is the relationship? 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 Valuing SF-6D Health States Using a Discrete Choice Experiment Development of a Preference-Weighted Health Status Classification System in France: The Health Utilities Index 3 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 FACT-G cancer-specific quality of life instrument to the EQ-5D and SF-6D Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences Predicting Health-Utility Scores From the Cervical Spine Outcomes Questionnaire in a Multicenter Nationwide Study of Anterior Cervical Spine Surgery Estimation of health-related utility (EQ-5D index) in subjects with seasonal allergic rhinoconjunctivitis to evaluate health gain associated with sublingual grass allergen immunotherapy Mapping MOS Sleep Scale scores to SF‑6D utility index A Portuguese value set for the SF-6D. Mapping Quality of Life (EQ-5D) from DAPsA, Clinical DAPsA and HAQ in Psoriatic Arthritis Health-related quality of life among prostate cancer patients: real-life situation at the beginning of treatment A comparison of physician-rated disease severity and patient reported outcomes in mild to moderately active ulcerative colitis. Mapping of the PDQ-39 to EQ-5D scores in patients with Parkinson’s disease Does disease activity add to functional disability in estimation of utility for rheumatoid arthritis patients on biologic treatment? Assessing outcomes for cost-utility analysis in mental health interventions: mapping mental health specific outcome measure GHQ-12 onto EQ-5D-3L Mapping the 12-item multiple sclerosis walking scale to the EuroQol 5-dimension index measure in North American multiple sclerosis patients Use of health-related quality of life measures to predict health utility in postmenopausal osteoporotic women: results from the Multiple Outcomes of Raloxifene Evaluation study The development of a model for translation of the Neck Disability Index to utility scores for cost-utility analysis in cervical disorders. Cutoff values of the Inflammatory Bowel Disease Questionnaire to predict a normal health related quality of life. Mapping the SRS-22r questionnaire onto the EQ-5D-5L utility score in patients with adolescent idiopathic scoliosis Mapping from disease-specific measures to health-state utility values in individuals with migraine. Using EQ-5D to derive general population-based utilities for the quality of life assessment of growth hormone deficiency in adults (QoL-AGHDA). The potential for a generally applicable mapping model between QLQ-C30 and SF-6D in patients with different cancers: a comparison of regression-based methods Mapping Between the Sydney Asthma Quality of Life Questionnaire (AQLQ-S) and Five Multi-Attribute Utility Instruments (MAUIs) Mapping scores from the Strengths and Difficulties Questionnaire (SDQ) to preference-based utility values Mapping between the Roland Morris Questionnaire and generic preference-based measures. Mapping analyses to estimate health utilities based on responses to the OM8-30 otitis media questionnaire Predicting SF-6D Utility Scores From the Neck Disability Index and Numeric Rating Scales for Neck and Arm Pain Derivation of Utility Values from European Organization for Research and Treatment of Cancer Quality of Life-Core 30 Questionnaire Values in Lung Cancer Generic and disease-specific estimates of quality of life in macular degeneration: mapping the MacDQoL onto the EQ-5D-3L Use of a disease-specific instrument in economic evaluations: mapping WOMAC onto the EQ-5D utility index. Mapping the 25-item National Eye Institute Visual Functioning Questionnaire (NEI VFQ-25) to EQ-5D Utility Scores Estimating a preference-based index from the Japanese SF-36. Mapping the relationship between clinical and quality-of-life outcomes in patients with ankylosing spondylitis The Assessment of Quality of Life (AQoL) instrument: a psychometric measure of Health-Related Quality of Life Mapping the Modified Rankin Scale (mRS) Measurement into the Generic EuroQol (EQ-5D) Health Outcome Mapping chronic liver disease questionnaire scores onto SF-6D utility values in patients with primary sclerosing cholangitis Multiattribute utility function for a comprehensive health status classification system. Health Utilities Index Mark 2. Exploring the impact of changes in neurogenic urinary incontinence frequency and condition-specific quality of life on preference-based outcomes Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm. Mapping the clinical chronic obstructive pulmonary disease questionnaire onto generic preference-based EQ-5D values. Multiattribute and Single‐Attribute Utility Functions for the Health Utilities Index Mark 3 System Estimating the SF-6D value set for a population-based sample of Brazilians. Mapping health assessment questionnaire disability index (HAQ-DI) score, pain visual analog scale (VAS), and disease activity score in 28 joints (DAS28) onto the EuroQol-5D (EQ-5D) utility score with the KORean Observational study Network for Arthritis (KORONA) registry data Predicting health-related quality of life (EQ-5D-5 L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP Mapping FACT-melanoma quality-of-life scores to EQ-5D health utility weights. Generating EQ-5D-3L Utility Scores from the Dermatology Life Quality Index: A Mapping Study in Patients with Psoriasis. Testing alternative regression models to predict utilities: mapping the QLQ-C30 onto the EQ-5D-5L and the SF-6D Does Selecting Covariates Using Factor Analysis in Mapping Algorithms Improve Predictive Accuracy? A Case of Predicting EQ-5D-5L and SF-6D Utilities from the Women's Health Questionnaire. Scoring the Child Health Utility 9D instrument: estimation of a Chinese child and adolescent-specific tariff Mapping utility scores from a disease-specific quality-of-life measure in bariatric surgery patients. Mapping the cancer-specific EORTC QLQ-C30 to the preference-based EQ-5D, SF-6D, and 15D instruments. Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39)
abstract: 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 Purpose It is not always possible to collect utility-based outcome data , like EQ-5D , needed for conducting economic evaluations in population s of older people . Sometimes , information on other non-utility outcome measures may have been collected . This paper examines the possibility of mapping the EQ-5D from a non-utility-based outcome , the Barthel index . Methods Data for 1,189 UK intermediate care patients were used .  Ordinary least squares ( OLS ) , censored least absolute deviations ( CLAD ) estimator and multinomial logistic ( ML ) models were used . The mean absolute error ( MAE ) and root-mean-squared error ( RMSE ) were used to estimate the predictive accuracy of eight regression models . Validation of primary models was carried out on r and om sample s of data collected at admission and discharge . Results Models where the EQ-5D was entered as a continuous dependent variable and Barthel dimensions used as explanatory variables performed better . CLAD performed best on MAE and OLS on the RMSE , while the ML performed the worst on both measures . The CLAD predicted EQ-5D scores that matched the observed values more closely than the OLS . Conclusions It is possible to reasonably predict that the EQ-5D from the Barthel using regression methods and the CLAD model ( 4 ) is recommended 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 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 . 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 The Health Utilities Index is a generic multiattribute preference-based system for assessing health-related quality of life , devised by Torrance et al. It is being used in cost-effectiveness evaluations in North America and in international multicentre studies but was not available in France . Following adaptation of the HUI3 classification in France , the purpose of the reported investigation was to derive French preference weights . This article provides a reminder of the theoretical foundations used to model the multiattribute utility function . Within this framework , a multiattribute multiplicative aggregate utility function was constructed in accordance with the explicitly decomposed approach . The study took place in June 1999 over a sample of 365 persons from the French general population , aged between 20 and 65 , and not suffering from any chronic or incapacitating illness . The recruitment procedure was based upon a r and om selection of individuals , using the phone book . Interviews took place in the homes of the interviewees . The methods of revelation ( VAS and SG ) were applied by setting the value of the best possible state of the HUI3 a priori at 1 , and leaving a choice between two states ( worst possible state , death ) for 0 . The aggregated individuals ( person-mean and median ) were calculated and the multiplicative utility functions constructed . A comparison of the calculated utilities with the observed ones provides a primary indicator of the validity of the person-mean or median functions constructed . The slight absolute differences obtained between observed and calculated utilities and the low RMSE scores lead us towards a favourable conclusion 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 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 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 Study Design . Cross-sectional analysis of the Cervical Spine Research Society Outcomes Study , a longitudinal multicenter cohort study . Objective . To provide a statistical model for estimating health utility from the Cervical Spine Outcomes Question naire ( CSOQ ) domain scores . Summary of Background Data . There is consensus among health-policy research ers that the results of economic evaluations of health can be reported in quality -adjusted life-years ( QALY ) . The CSOQ is a condition-specific instrument that assesses individuals across several domains , including neck and arm/shoulder pain and psychological distress . Methods . The  CSOQ and 36-Item Short Form Health Survey ( SF-36 )  were prospect ively administered before surgery ( within 4 weeks ) and after surgery ( at 3 , 6 , and 24 months ) to individuals undergoing anterior cervical decompression and fusion for degenerative disc disease of the cervical spine . Using methods reported by Brazier et al , health utility ( SF-6D ) was estimated using the SF-36 . Regression analyses were used on a training data set ( n = 164 ) to compute the SF-6D from the domain scores of the CSOQ . A validation data set ( n = 328 ) was used to estimate the SF-6D for comparison to the calculated health utility from the SF-36 . Results . Domain scores were moderately correlated with health utility ( SF-6D ) ( P < 0.001 ) with correlation coefficients ranging from 0.48 to 0.70 . The regression equation to predict SF-6D on the basis of CSOQ domain scores and patient age using the training data set accounted for 65 % of the variation in health utility . In the validation data set , predicted SF-6D was positively correlated with observed SF-6D ( r = 0.680 , P < 0.001 ) . Conclusion . Our findings show that the CSOQ 's domain scores can be used to estimate health-utility scores among those undergoing elective anterior cervical decompression and fusion for cervical degenerative disc disease . The ability to assess health utility , coupled with the psychometric properties of the CSOQ , should increase the clinical utility of this patient-reported outcomes instrument Background Grass allergen immunotherapy ( AIT ) reduces symptom severity in seasonal allergic rhinoconjunctivitis ( ARC ) but its impact on general health-related utility has not been characterised for the purpose s of economic evaluation . The aim of this study was to model the preferred measure of utility , EQ-5D index , from symptom severity and estimate incremental quality adjusted life years ( QALYs ) associated with SQ-st and ardised grass immunotherapy tablet ( GRAZAX ® , 75,000 SQ-T/2,800 BAU , ALK , Denmark ) . Methods Data were analysed from five consecutive pollen seasons in a r and omised placebo controlled trial of GRAZAX ® . Binomial and Gaussian mixed effects modelling related weekly EQ-5D index score to daily symptom and medication scores ( DSS & DMS respectively ) . In turn , daily EQ-5D index was estimated from ARC symptoms and medication use . Results DSS and DMS were the principal predictors of ‘ perfect ’ health ( EQ-5D = 1.000 ; binomial ) and ‘ imperfect ’ health ( EQ-5D < 1.000 ; Gaussian ) . Each unit increase in DSS and DMS reduced the odds of ‘ perfect ’ health ( EQ-5D = 1.000 ) by 27 % and 16 % respectively , and reduced ‘ imperfect ’ health by 0.17 and 0.13 , respectively . Gender remained the only other significant main fixed effect ( Male odds ratio [ OR ] = 1.82 ) . Incremental estimated EQ-5D index utility  for GRAZAX ® was observed from day -30 to day + 70 of the pooled pollen season ; mean daily utility for GRAZAX ® = 0.938 units ( 95%CI 0.932 - 0.943 ) vs. 0.914 ( 0.907 - 0.921 ) for placebo , an incremental difference of 0.0238 ( p < 0.001 ) . This translates into an incremental 0.0324 Quality Adjusted Life Years over the five year study period . Conclusions ARC symptoms and medication use are the main predictors of EQ-5D index . The incremental QALYs observed for GRAZAX ® may not fully describe the health benefits of this treatment , suggesting that economic modelling may be conservative ABSTRACT Objective : Deriving preference scores for the  Medical Outcomes Study  ( MOS ) Sleep Scale would enable its use in cost – utility analyses . The objective of this study was to map scores of the MOS Sleep Scale to a preference-based health-state utility index ( SF‑6D ) scored from the SF‑36 Health Survey ( SF‑36 ) . Research design and methods : Three data sets were used : ( 1 ) the MOS study , a 4-year observational study of chronically ill patients , ( 2 ) a 7-week open-label , non-comparative clinical trial of an osmotic controlled-release oral delivery system ( OROS ) hydromorphone in the treatment of chronic low back pain ( CLBP ) , and ( 3 ) a 6-week open-label r and omized controlled trial of OROS hydromorphone in the treatment of pain associated with chronic osteoarthritis ( OA ) . Various models were tested , where SF‑6D was regressed onto the Sleep Problem Index‑II ( SLP9 ) in 1000 r and om half ( developmental ) sample s of the MOS ( n = 1413 ) . The best fitting model was applied to the other 1000 r and om half ( cross-validation ) sample s of the MOS ( n = 1412 ) , and to the two trial sample s ( n = 199 in the CLBP trial ; n = 124 in the OA trial ) . Results : The best fitting model in the MOS sample s included a quadratic term for the SLP9 which explained 34 % of the variance in SF‑6D in the developmental sample s. Errors in prediction were greatest at higher SLP9 scores . Addition of demographic and clinical variables to the model explained minimal incremental amounts of variance ( < 5 % ) in SF‑6D scores . These results were replicated in the cross-validation MOS sample s. In both developmental and cross-validation MOS sample s , mean predicted and observed SF‑6D scores were nearly identical . When the mapping algorithm developed in the MOS was applied to the CLBP sample , mean predicted SF‑6D scores were 0.09 points higher than observed SF‑6D scores at both baseline and final visits , while changes in predicted and observed SF‑6D scores were identical . Conclusion : Results indicate that it is possible to map MOS SLP9 to SF‑6D yielding useable preference-based scores essential for cost – utility analyses . A limitation concerns the interpretation of SF‑6D scores estimated from SLP9 scores above 60 , where the prediction errors increased considerably OBJECTIVES The SF-6D is a preference-based measure of health derived from the SF-36 that can be used for cost-effectiveness analysis using cost-per- quality adjusted life-year analysis . This study seeks to estimate a system weight for the SF-6D for Portugal and to compare the results with the UK system weights . METHODS A sample of 55 health states defined by the SF-6D has been valued by a representative r and om sample of the Portuguese population , stratified by sex and age ( n = 140 ) , using the St and ard Gamble ( SG ) . Several models are estimated at both the individual and aggregate levels for predicting health-state valuations . Models with main effects , with interaction effects and with the constant forced to unity are presented . R and om effects ( RE ) models are estimated using generalized least squares ( GLS ) regressions . Generalized estimation equations ( GEE ) are used to estimate RE models with the constant forced to unity . Estimations at the individual level were performed using 630 health-state valuations . Alternative functional forms are considered to account for the skewed distribution of health-state valuations . RESULTS The models are analyzed in terms of their coefficients , overall fit , and the ability for predicting the SG-values . The RE models estimated using GLS and through GEE produce significant coefficients , which are robust across model specification . However , there are concerns regarding some inconsistent estimates , and so parsimonious consistent models were estimated . There is evidence of under prediction in some states assigned to poor health . The results are consistent with the UK results . CONCLUSION The models estimated provide preference-based quality of life weights for the Portuguese population when health status data have been collected using the SF-36 . Although the sample was r and omly drowned findings should be treated with caution , given the small sample size , even knowing that they have been estimated at the individual level Background Clinical trials and observational studies lacking measures of health-related quality of life ( QoL ) are often inapplicable when conducting cost-effectiveness analyses using quality -adjusted life-years ( QALYs ) . The only solution is to map QoL ex post from additionally collected clinical outcomes and generic QoL instruments . Nonetheless , mapping studies are absent in psoriatic arthritis ( PsA ) . Methods In this 2-year , prospect i ve , multicentre , non-interventional study of PsA patients , EQ-5D and key clinical parameters such as Disease Activity in PsA ( DAPsA ) , clinical DAPsA ( cDAPsA ; DAPsA without C-reactive protein [ CRP ] ) , and Health Assessment Question naire disability index ( HAQ ) were collected . We employed a linear mixed-effect regression model ( ME ) of the longitudinal data set to explore the best predictors of QoL. Results A total of 228 patients were followed over 873 appointments/observations .  DAPsA , cDAPsA and HAQ were stable and highly significant predictors of EQ-5D utilities in both cross-sectional and longitudinal analyses . The best prediction was provided using a linear ME with HAQ and cDAPsA or DAPsA. A HAQ increase of 1 point represented a decrease in EQ-5D by −0.204 or −0.203 ( p < 0.0001 ) ; a one-point increase in cDAPsA or DAPsA dropped EQ-5D equally by −0.005 ( p < 0.0001 ) . The ME revealed steeper and more accurate association compared with cross-sectional regressions or non-linear models/transformations . Conclusions This is the first mapping study conducted in PsA and we hope that our study will encourage further mapping studies in PsA. The results showed that in cases where CRP is absent , cDAPsA provides similar results to DAPsA in predicting Abstract Objective : The aims of this study were to measure the real-life health-related quality of life ( HRQoL ) of newly diagnosed prostate cancer ( PCa ) patients , to compare it with that of the general male population and to explore factors affecting HRQoL. Methods : All newly diagnosed PCa patients in the Helsinki University Hospital were asked to fill in 15D and EORTC QLQ-C30 question naires . Clinical background information was collected retrospectively from patient charts . Patients were categorized into three mutually exclusive groups based on the disease stage : Local , Locally advanced and Metastatic groups . Multivariate linear regression analysis was conducted to explore which factors explained variance in 15D scores . A regression model was built to map the EORTC QLQ-C30 to 15D in a r and om sample of 50 % of patients and the model was tested in the other half of the patients . Results : In total , 1050 men with a mean age of 67 years responded to the question naires . The mean ± SD 15D score of patients was slightly lower than that of the age-st and ardized general male population : 0.905 ± 0.089 vs 0.915 ± 0.082 ( p = .057 ) . The mean ± SD 15D utility scores were 0.912 ± 0.084 , 0.897 ± 0.102 and 0.855 ± 0.109 for Local , Locally advanced and Metastatic groups , respectively . The mapping model of EORTC QLQ-C30 to 15D was robust and fitted well ( root mean square error = 0.042 , adjusted R² = .79 ) . Conclusions : The HRQoL of PCa patients entering treatment was similar to that of the general population . HRQoL was most impaired among patients with metastatic disease , whereas the difference between patients with localized PCa and the general population was minor . Mapping indicated that the 15D score aggregates quite accurately the information from the EORTC QLQ-C30 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 Purpose The EuroQoL ( EQ-5D ) is ideal to compare quality of life across conditions . However , the Parkinson ’s Disease Question naire ( PDQ-39 ) is often the only quality -of-life instrument used in Parkinson ’s disease research . We aim ed to identify associations between PDQ-39 domains and EQ-5D domains , and compare different methods of developing a function to map the PDQ-39 to EQ-5D scores . Methods Adults with Parkinson ’s disease self-completed both instruments . Ordinal regression identified associations between PDQ-39 domain scores and each EQ-5D domain . Modeling ( n = 80 ) and validation sets ( n = 16 ) were r and omly generated . Overall performance of four methods of mapping the PDQ-39 to EQ-5D scores ( using PDQ-39 domains and total score in ordinal and linear regression ) was assessed with the validation set , followed by assessing the equivalence of observed and predicted EQ-5D scores on the full data set controlling for sociodemographic factors . Results Different sets of PDQ-39 domains were associated with each EQ-5D domain . For example , PDQ-39 “ Activities of Daily Living ” and “ Social Support ” were associated with EQ-5D “ Personal Care , ” while PDQ-39 “ Emotional Well-being ” was associated with EQ-5D “ Anxiety/Depression . ” Over one-third ( 37.5 % ) of predictions from ordinal regressions had an error < 0.01 % ( compared to 6.3 % for linear regressions ) . The EQ-5D scores predicted with ordinal regression using PDQ-39 domains were similar in distribution and association with sociodemographic factors to the observed EQ-5D scores . Conclusions Of the four methods tested , using PDQ-39 domains in ordinal regression was superior for mapping EQ-5D scores . The function reported here may prove particularly useful for cost-utility analyses comparing Parkinson ’s disease with other conditions OBJECTIVE Treatment in general is mostly directly aim ed at disease activity , and measures such as the DAS28 might therefore present important additional information . Our aim was to develop and vali date a model that uses a combination of disease activity ( DAS28 ) and HAQs to estimate EuroQoL 5-dimension scale ( EQ5D ) utilities . METHODS Longitudinal data from a cohort study in RA patients from the Utrecht Rheumatoid Arthritis Cohort study Group ( Stichting Reumaonderzoek Utrecht ) who started treatment with a biologic drug  were used for mapping and validation . All 702 observations , including DAS28 , HAQ and EQ5D assessed at the same time points , were used . The observations were r and omly divided into a subset for development of the model ( n = 428 observations ) and a subset for validation ( n = 274 ) . A stepwise multivariable regression analysis was used to test the association of DAS28 ( components ) and HAQ ( domains ) with EQ5D . Model performance was assessed using the explained variance ( R(2 ) ) and root mean square errors . Observed and predicted utility scores were compared to check for under- or overestimation of the scores . Finally , the performance of the model was compared with published mapping models . RESULTS Lower DAS28 score and HAQ items dressing and grooming , arising , eating , walking and activities were associated with higher EQ5D scores . The final model had an explained variance of 0.35 and a lower root mean square error as compared with other models tested . The agreement between predicted and observed scores was fair . CONCLUSION HAQ components estimate EQ5D better than total HAQ . Adding DAS28 to HAQ components does not result in better utility estimations 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 Objective To map the 12-item Multiple Sclerosis Walking Scale ( MSWS-12 ) onto the EuroQol 5-dimension ( EQ-5D ) health-utility index in multiple sclerosis ( MS ) patients participating in the North American Research Committee on Multiple Sclerosis ( NARCOMS ) registry . Design Cross-sectional MSWS-12 to EQ-5D cross-walking analysis . Setting NARCOMS registry spring 2010 biannual up date and supplemental survey . Participants North American patients completing both the MSWS-12 and the EQ-5D r and omly split into derivation and validation cohorts . Outcome measures Ordinary least squares regression was performed within the derivation cohort , with participants ’ EQ-5D as the dependent variable . Results of the MSWS-12 were input as independent variable(s ) into six regression models . Model goodness-of-fit was subsequently assessed in the validation cohort using the mean absolute error ( MAE ) , root mean square error ( RMSE ) and the adjusted R2 . The best performing model was refined in the entire cohort and utilised for additional analyses . Results A total of 3505 NARCOMS participants were included .  Their mean±SD EQ-5D and MSWS-12 scores were 0.74±0.18 and 50.8±33.5 , respectively , and these assessment s were found to be moderately correlated ( r=–0.553 , p<0.001 ) . The model using all individual MSWS-12 item scores as independent variables was found to have the best fit ( MAE=0.109±0.096 , RMSE=0.145 , adjusted R2=0.329 ) . The percentage of EQ-5D estimates within 0.05 and 0.10 of the actual value were 30 % and 61 % , respectively . This mapping equation was more precise in patients with moderate mobility impairment ( MAE=0.087±0.061 at patient-determined disease step ( PDDS ) of 3–6 ) and less precise in patients with no ( MAE=0.141±0.128 at PDDS of 0–2 ) or severe mobility impairment ( MAE=0.121±0.049 at PDDS ≥7 ) . Conclusions The EQ-5D scores can be predicted using the MSWS-12 item scores with reasonable precision in North American patients with MS . Prediction estimates were more precise in patients with moderate mobility impairment Background The aim of this study is to examine the associations between health utility ( HU ) , health-related quality of life ( HRQoL ) , and patient characteristics in postmenopausal osteoporotic ( PMO ) women . Methods Baseline data from a sub sample of 1,245 participants of the Multiple Outcomes of Raloxifene Evaluation study , a r and omized , placebo-controlled , multinational clinical trial to evaluate the safety and efficacy of raloxifene  , were analyzed . The study cohort included 694 participants from non-European Union ( non-EU ) countries and 551 participants from EU countries . All participants with complete baseline HU and HRQoL assessment s were included in the following analyses : 1 ) HU ( HUI or EQ-5D ) and HRQoL ( QualEFFO or OPAQ and NHP ) associations ; 2 ) HU variability explained by HRQoL domains ; and 3 ) the percentage of HU variability explained by statistically significant ( p < 0.05 ) HRQoL domains , after adjusting for baseline characteristics . Results Several domains were significantly associated with HU scores . HU variance was well explained ( 41 % to 61 % ) by 4 to 6 ( p < 0.05 ) significant HRQoL domains . After controlling for baseline characteristics , 48 % to 64 % of the HU variance was well explained by 5 to 7 significant ( p < 0.05 ) HRQoL domains . Additional trend analyses detected statistically significant decreases in HRQoL and HU scores with an increased number of vertebral and non-vertebral fractures . Conclusions Both disease-targeted and generic HRQoL domains were well correlated with HU . A large percentage ( 48 % to 64 % ) of the HU variance was explained by HRQoL , after adjusting for baseline characteristics . Both disease-targeted and generic HRQoL measures were significant predictors of HU . HRQoL and HU scores decreased with increased vertebral and non-vertebral fractures BACKGROUND CONTEXT The Neck Disability Index ( NDI ) is a commonly used disease-specific instrument for cervical spine disorders with good responsiveness and psychometric properties compared with general health status measures . However , NDI scores are unitless and do not have an intrinsic value that is comparable to other health status measures , and these scores have limited value in cost-utility analysis . The translation of disease-specific measures to Short Form-6 Dimensions ( SF-6D ) utility scores may be useful in cost-utility analysis . PURPOSE The purpose of this study is to present a model for translating the NDI to SF-6D utility scores , permitting the use of NDI scores in the cost-utility analysis of cervical disorders . STUDY DESIGN / SETTING A secondary analysis of a multicenter prospect i ve clinical trial of the Synthes ProDisc-C ( Synthes , West Chester , PA , USA ) was performed . PATIENT SAMPLE Patients included were r and omized to receive either a total disc arthroplasty or anterior cervical discectomy and fusion for treatment of symptomatic cervical disc disease involving one vertebral level between C3 and C7 . All subjects completed NDI and 36-Item Short Form Health Survey ( SF-36 ) self- assessment s at preoperative and postoperative follow-ups of 6 weeks , 3 , 6 , 12 , 18 , and 24 months . OUTCOME MEASURES The NDI is a vali date d and widely used self-reported question naire design ed to assess patient-determined disability result ing from neck pain , including pain level and effects on activities of daily living . The SF-6D is a preference-based health state classification system derived from six health dimensions of the SF-36 self-reported question naire , including the domains of physical functioning , role limitation , social functioning , bodily pain , mental health , and vitality . METHODS The collected data points were divided into two cohorts : one for model formation and one for the assessment of model validity . SF-36 scores were converted to SF-6D utilities via three previously published methods . Correlation analyses and linear regression modeling between SF-6D and NDI created the models for translating scores . For validation , Spearman and Pearson correlations were calculated between the observed and predicted SF-6D utilities , and prediction errors were calculated . RESULTS Four hundred thirty patients with 2,137 time points were used for creation and validation of the model . Pearson and Spearman correlation coefficients between the NDI and the SF-6D derived from each conversion method were found to be between -0.8255 and -0.8504 ( p<.01 ) . R(2 ) values ranged from 0.68 to 0.71 and root mean squared error ( RMSE ) from 0.092 to 0.084 . Correlations between estimated and observed SF-6D scores ranged from 0.8325 to 0.8372 ( p<.01 ) . The mean prediction error was less than 0.006 , with st and ard deviation ( SD ) between 0.082 and 0.093 . DISCUSSION Correlations between NDI and SF-6D utility scores are strong and statistically significant . The model has a large R(2 ) and small RMSE . The prediction models produce a small mean prediction error , but the SD of the prediction errors is large . High correlations between NDI and SF-6D permit these models to be used to calculate overall utilities , changes in utilities , and quality -adjusted life-years for large data sample s. However , the relatively large observed prediction error SDs may limit the accuracy of translation of individual data points or small sample sizes UNLABELLED One of the objectives in the treatment of the inflammatory bowel disease ( IBD ) is improving the patient 's quality of life . However , we do not dispose of vali date d criteria to determine the question naire 's scoring threshold that has to be reached in order to be able to assert that the patients ' quality of life has normalized . OBJECTIVE To determine the normality punctuation cutoff in the IBD specific quality of life question naire IBDQ-36 . METHOD Cross-sectional study in a r and om sample of IBD patients , who have completed the question naires IBDQ-36 and EuroQol-5D .  The IBDQ-36 normality was calculated according to its equivalence with the EuroQol-5D tariff ≥ 0.90 , which corresponds to the 95 % CI of the average obtained in a Spanish general population . RESULTS 218 patients were included . According to the EuroQol-5D tariff , 70 patients were considered to have a normal quality of life and 148 a quality of life poorer than the general population . The IBDQ-36 scoring was significantly higher in the normal quality of life group ( 222.9 ± 22.8 vs. 171.4 ± 44.8 in the bad quality of life group , p<0.001 ) . According to the linear regression between IBDQ-36 and EuroQol-5D , the cutoff point is 209 , with a sensitivity and specificity to predict normality of 0.74 and 0.71 respectively . CONCLUSIONS Scores of the IBDQ-36 equal or superior to 209 suggest quality of life comparable to that perceived by the general population . This study allowed to set a threshold of normality in the management of the inflammatory bowel diseases This is a prospect i ve study to establish prediction models that map the refined Scoliosis Research Society 22-item ( SRS-22r ) onto EuroQoL-5 dimension 5-level ( EQ-5D-5L ) utility scores in adolescent idiopathic scoliosis ( AIS ) patients . Comparison of treatment outcomes in AIS can be determined by cost-utility analysis . However , the mainstay spine-specific health-related quality of life outcome measure , the SRS-22r question naire does not provide utility assessment . In this study , AIS patients were prospect ively recruited to complete both the EQ-5D-5L and SRS-22r question naires by trained interviewers . Ordinary least squares regression was undertaken to develop mapping models , which the validity and robustness were assessed by using the 10-fold cross-validation procedure .  EQ-5D-5L utility scores were regressed on demographics , Cobb angle , curve types , treatment modalities , and five domains of the SRS-22r question naire . Three models were developed using stepwise selection method . EQ-5D-5L scores were regressed on 1 ) main effects of SRS-22r subscale scores , 2 ) as per 1 plus squared and interaction terms , and 3 ) as per 2 plus demographic and clinical characteristics . Model goodness-of-fit was assessed using R-square , adjusted R-square , and information criteria ; whereas the predictive performance was evaluated using root mean square error ( RMSE ) , mean absolute error ( MAE ) , and the proportion of absolute error within the threshold of 0.05 and 0.10 . A total of 227 AIS patients with mean age of 15.6 years were recruited . The EQ-5D-5L scores were predicted by four domains of SRS-22r ( main effects of ‘ Function ’ , ‘ Pain ’ , ‘ Appearance ’ and ‘ Mental Health ’ , and squared term of ‘ Function ’ and ‘ Pain ’ ) , and Cobb angle in Model 3 with the best goodness-of-fit ( R-square/adjusted R-square : 62.1%/60.9 % ) . Three models demonstrated an acceptance predictive performance in error analysis applying 10-fold cross-validation to three models where RMSE and MAE were between 0.063–0.065 and between 0.039–0.044 , respectively . Model 3 was therefore recommended out of three mapping models established in this paper . To our knowledge , this is the first study to map a spine-specific health-related quality of life measure onto EQ-5D-5L for AIS patients . With the consideration and incorporation of demographic and clinical characteristics , over 60 % variance explained by mapping model 3 enabled the satisfactory prediction of EQ-5D-5L utility scores from existing SRS-22r data for health economic appraisal of different treatment options 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 OBJECTIVE Disease-oriented quality of life ( QoL ) measures that are not preference-based lack legitimacy for direct use in cost-utility analyses . This has prompted the search for other methods for deriving utilities . The QoL Assessment of Growth Hormone Deficiency in Adults question naire ( QoL-AGHDA ) is a disease-oriented measure used to assess impairment in QoL in adults with growth hormone deficiency . The present study was design ed to generate a model for deriving utilities from the QoL-AGHDA . METHODS The EQ-5D , the QoL-AGHDA , and demographic questions were mailed to a r and om sample ( n = 3005 ) of the Swedish population ( response rate 65 % ) .  Multiple regression analysis was used to obtain cross-vali date d parameters of QoL-AGHDA-based utilities . Two models were developed ( simple and full versions ) . The simple version used the EQ-5D(index ) ( derived from European values ) as the dependent variable , and age , sex , and QoL-AGHDA score as independent variables in a regression analysis . The full model utilized all available demographic information . The QoL-AGHDA scores were thus transformed into a single score ( 0 - 1 ) , corresponding to the QoL-AGHDA-based utility . RESULTS The simple transformation algorithm was U ( QoL-AGHDA-based utilities ) = 1.05 - 0.0189 x QoL-AGHDA score - 0.00238 x age - 0.0127 x sex ( male = 0 ; female = 1 ) . The mean of the weighted estimate for the population ( n = 1752 ) was 0.85 ( SD 0.10 ) . The estimate for men ( n = 861 ; mean 0.86 ; SD 0.10 ) was higher ( P < 0.001 ) than for women ( n = 891 ; mean 0.84 ; SD 0.10 ) . CONCLUSION For practical reasons , the simple model can be recommended for deriving utilities directly from the QoL-AGHDA for the Swedish population Purpose To establish and compare generalized or “ global ” mapping relationships between QLQ-C30 and SF-6D , applicable across different cancer types . Methods Patients ( N = 671 ) with breast , myeloma , colorectal , lymphoma , bone marrow , prostate , lung and gastroenteric cancer were r and omly split into estimation ( 75 % ) and validation ( 25 % ) data sets . SF-6D was estimated from QLQ-C30 scores via ordinary least squares , generalized linear models and median ( least-absolute deviations ) regression approaches , and with Bayesian additive regression kernels . Predictive ability was assessed with root mean square error , mean absolute error and proportions of predictions with absolute errors > 0.05 and > 0.1 , whereas explanatory power with adjusted R2 or equivalent fit measures . Two external sample s ( breast and colorectal cancer ) were used to further test the models . Results The QLQ-C30 's global health item , the physical , emotional and social functioning scales , and the fatigue , pain and diarrhea symptom scales were significant predictors ( p < 0.05 or better ) in all models . Negligible deviations in models ’ performance were observed . All models overpredicted utilities for patients in worst health and underpredicted them for those in better health ( p < 0.01 or better ) . Regarding external validation , performance was better in the colorectal cancer than in the breast cancer sample . Conclusions This study has provided evidence to support the use of “ global ” mapping models to predict SF-6D utilities from QLQ-C30 in patients with different cancers . Testing with diverse patient sample s is required to confirm the generalizability ( or not ) of mapping models across cancer conditions 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 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 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 Purpose To investigate the statistical relationship between the OM8 - 30 health-related quality of life measure for children with otitis media with effusion ( OME ) and measures of health utility ( Health Utilities Index [ HUI ] Mark 3 and Mark 2 ) and to develop models to estimate HUI3 and HUI2 health utilities from OM8 - 30 scores . Methods A placebo-controlled , r and omised trial ( GNOME ) evaluating intranasal mometasone in 217 children with OME provided concurrent responses to OM8 - 30 and HUI at three time points . Ordinary least squares ( OLS ) , generalised linear models and two-step regression analyses were used to predict HUI3 and HUI2 utilities based on OM8 - 30 facet and domain scores . Results OLS models including all nine OM8 - 30 facets with or without predicted hearing level ( HL ) produced the best predictions of HUI3 utilities ( mean absolute error : 0.134 with HL and 0.132 without ; R2 : 0.63 with HL and 0.596 without ) . An OLS model predicting HUI3 utilities based on the two OM8 - 30 domain scores , reported hearing difficulties , predicted HL , age and sex also produced accurate predictions . Conclusion Regression equations predicting HUI3 and HUI2 utilities based on OM8 - 30 facet and domain scores have been developed . These provide an empirical basis for estimating quality -adjusted life years ( QALYs ) for interventions in children with OME Study Design . Cross-sectional cohort . Objective . This study aims to provide an algorithm to estimate Short Form-6D ( SF-6D ) utilities using data from the Neck Disability Index ( NDI ) , neck pain , and arm pain scores . Summary of Background Data . Although cost-utility analysis is increasingly used to provide information about the relative value of alternative interventions , health state values or utilities are rarely available from clinical trial data . The Neck Disability Index ( NDI ) and numerical rating scales for neck and arm pain are widely used diseasespecific measures in patients with cervical degenerative disorders . The purpose of this study is to provide an algorithm to allow estimation of SF-6D utilities using data from the NDI , and numerical rating scales for neck and arm pain . Methods . SF-36 , NDI , neck and arm pain rating scale scores were prospect ively collected before surgery , at 12 and 24 months after surgery in 2080 patients undergoing cervical fusion for degenerative disorders . SF-6D utilities were computed , and Spearman correlation coefficients were calculated for paired observations from multiple time points between NDI , neck and arm pain scores , and SF-6D utility scores . SF-6D scores were estimated from the NDI , neck and arm pain scores were estimated using a linear regression model . Using a separate , independent data set of 396 patients in which NDI scores were available , SF-6D was estimated for each subject and compared to their actual SF-6D . Results . The mean age for those in the development sample was 50.4 ± 11.0 years and 33 % were male . In the validation sample , the mean age was 53.1 ± 9.9 years and 35 % were male . Correlations between the SF-6D and the NDI , neck and arm pain scores were statistically significant ( P < 0.0001 ) with correlation coefficients of 0.82 , 0.62 , and 0.50 , respectively . The regression equation using NDI aloneto predict SF-6D had an R2 of 0.66 and a root mean square error of 0.056 . In the validation analysis , there was no statistically significant difference ( P = 0.961 ) between actual mean SF-6D ( 0.49 ± 0.08 ) and the estimated mean SF-6D score ( 0.49 ± 0.08 ) , using the NDI regression model . Conclusion . This regression-based algorithm may be a useful tool to predict SF-6D scores in studies of cervical degenerative disease that have collected NDI but not utility scores Introduction : Cancer clinical trials frequently incorporate quality of life ( QoL ) measures but rarely patient utility . Utility information is required for cost utility evaluations of novel cancer therapies . We assessed the feasibility of converting QoL data into utility scores using the European Organization for Research and Treatment of Cancer Quality of Life-Core  30 question naire ( EORTC QLQ-C30 ) and the EQ-5D in patients with non-small cell lung cancer ( NSCLC ) . Methods : Out patients with all different disease states of NSCLC attending a major Canadian cancer center completed the QLQ-C30 and EQ5D on a single visit . Results of the QLQ-C30 summary scores were mapped to predict EQ-5D utility scores using linear regression . Backward variable elimination using the Akaike Information Criterion was used to reduce the full model that included all QLQ-C30 summary scores to examine which QLQ-C30 dimensions best predict a patient 's utility score . To test the predictive power of the model , 10-fold cross-validation was used . Results : A total of 172 patients participated in the study . Median age of the sample was 66 years ( range , 32–85 years ) ; 46.5 % were men . The cross-validation estimate of mean utility score was 0.76 ( SD : 0.20 ) , which was the same as the actual mean utility score . Of the 15 QLQ-C30 dimensions , 4 functional dimensions ( physical , role , emotional , and social ) and the pain symptom dimension were predictive of patient utility scores . Conclusions : Our study demonstrates the feasibility of deriving utility scores from prospect i ve QoL data . Validation of the QLQ-C30 predictors found in this study could further the ability to estimate cost utility of therapies for economic evaluations Purpose The macular degeneration quality of life ( MacDQoL ) instrument is a vali date d condition-specific measure of quality of life in patients with macular degeneration . This paper presents the first mapping algorithm to predict EQ-5D from responses to the MacDQoL instrument . Methods Responses to the MacDQoL and EQ-5D-3L instruments from 482 patients were collected from the IVAN multicentre trial of two alternative drug treatments for neovascular age-related macular degeneration . Regression specifications were estimated using OLS , censored least absolute deviation , Tobit and two-part models . Their predictive performance was assessed using mean squared error . An internal validation sample based on a r and om selection of 25 % of patients was used to assess the performance of the model estimated on the remaining 75 % of patients . Results A two-part model had the best predictive performance on the full sample . The covariates of this model include responses and weighted impact scores for all 23 condition-specific domains of the MacDQoL , and responses to a general MacDQoL quality of life question . The selected models were successful at predicting means and st and ard deviations of target population s , but prediction is weaker at the upper and lower extremes of the EQ-5D-3L distribution . Conclusion The mapping algorithms provide a means of predicting EQ-5D-3L index scores from MacDQoL scores , and could facilitate cost-effectiveness analyses when the latter but not the former are available to research ers . Further validation of the performance of the algorithms using external data would provide a means of establishing the robustness of the algorithms OBJECTIVE To map the Western Ontario and McMaster Universities Osteoarthritis Index ( WOMAC ) onto the EuroQol 5 Dimension ( EQ-5D ) utility index in patients with knee osteoarthritis ( OA ) . METHODS A consecutive sample of patients ( n=258 ) diagnosed with knee OA completed both the WOMAC and the EQ-5D . Regression models with the ordinary least squares ( OLS ) or the censored least absolute deviations as the estimator were used to establish the mapping function . The WOMAC was represented as explanatory variables in four ways : 1 ) total score ; 2 ) domain scores ( i.e. , pain , stiffness , and physical function ) ; 3 ) domain scores plus pair-wise interaction terms to account for possible nonlinearities ; and 4 ) individual item scores . Goodness-of-fit criteria included the mean absolute error ( the primary criterion ) and the root mean squared error , and were obtained using an iterative r and om sampling procedure . Prediction precision was evaluated at individual patient level and at the group level . RESULTS The model using the OLS estimator and the WOMAC domain scores as explanatory variables had the best fit and was chosen as the preferred mapping model . The prediction error at the individual level exceeded the maximal tolerance value ( i.e. , the minimally important difference of the EQ-5D ) in about 16 % of the patients . At the group level , the width of the 95 % confidence interval of prediction errors varied from 0.0176 at a sample size of 400 to 0.0359 at a sample size of 100 . CONCLUSIONS EQ-5D scores can be predicted using WOMAC domain scores with an acceptable precision at both individual and group levels in patients with mild to moderate knee OA 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 OBJECTIVE The main objective of the study was to estimate a preference-based Short Form (SF)-6D index from the SF-36 for Japan and compare it with the UK results . STUDY DESIGN AND SETTING The SF-6D was translated into Japanese . Two hundred and forty-nine health states defined by this version of the SF-6D were then valued by a representative sample of 600 members of the Japanese general population using st and ard gamble ( SG ) . These health-state values were modeled using classical parametric r and om-effect methods with individual-level data and ordinary least squares ( OLS ) on mean health-state values , together with a new nonparametric approach using Bayesian methods of estimation . RESULTS All parametric models estimated on Japanese data were found to perform less well than their UK counterparts in terms of poorer goodness of fit , more inconsistencies , larger prediction errors and bias , and evidence of systematic bias in the predictions . Nonparametric models produce a substantial improvement in out-of- sample predictions . The physical , role , and social dimensions have relatively larger decrements than pain and mental health compared with those in the United Kingdom . CONCLUSION The differences between Japanese and UK valuations of the SF-6D make it important to use the Japanese valuation data set estimated using the nonparametric Bayesian technique presented in this article ABSTRACT Aim : To map health-related quality of life ( Qol ) with clinical parameters BASFI and ASDAS-CRP measure , and other covariates . Methods : Our prospect i ve multicenter non-interventional observation study of ankylosing spondylitis ( AS ) collected data about QoL and clinical outcomes on the initial and four subsequent visits . We employed simple linear regression analysis of a  cross-sectional  data set , and fixed effect , r and om effect and pooled linear regression of a longitudinal data set . Results : We showed that BASFI and ASDAS-CRP are very strong , robust predictors of EQ-5D utilities in all regression specifications together with sex ( female ) , invalidity , and activity impairment . Additionally , the longitudinal regression analysis showed that a fixed effect model may be a viable alternative to the most commonly used r and om effect model or pooled linear regression due to the nature of our data set . Conclusion : This is one of the first studies using a fixed effect model in longitudinal patient-level data , although , this method has been widely used in economics 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 . Mapping disease-specific instruments into generic health outcomes or utility values is an exp and ing field of interest in health economics . This article constructs an algorithm to translate the modified Rankin scale ( mRS ) into EQ-5D utility values . Methods .  mRS and  EQ-5D  information was derived from stroke or transient ischemic attack ( TIA ) patients identified as part of the Oxford Vascular study ( OXVASC ) .  Ordinary least squares ( OLS ) regression was used to predict UK EQ-5D tariffs from mRS scores . An alternative method , using multinomial logistic regression with a Monte Carlo simulation approach ( MLogit ) to predict responses to each EQ-5D question , was also explored . The performance of the models was compared according to the magnitude of their predicted-to-actual mean EQ-5D tariff difference , their mean absolute and mean squared errors ( MAE and MSE ) , and associated 95 % confidence intervals ( CIs ) . Out-of- sample validation was carried out in a subset of coronary disease and peripheral vascular disease ( PVD ) patients also identified as part of OXVASC but not used in the original estimation . Results . The OLS and MLogit yielded similar MAE and MSE in the internal and external validation data sets . Both approaches also underestimated the uncertainty around the actual mean EQ-5D tariff producing tighter 95 % CIs in both data sets . Conclusions . The choice of algorithm will be dependent on the study aim . Individuals outside the United Kingdom may find it more useful to use the multinomial results , which can be used with different country-specific tariff valuations . However , these algorithms should not replace prospect i ve collection of utility data 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 The Health Utilities Index Mark 2 ( HUI:2 ) is a generic multiattribute , preference-based system for assessing health-related quality of life .  Health Utilities Index Mark 2 consists of two components : a seven-attribute health status classification system and a scoring formula . The seven attributes are sensation , mobility , emotion , cognition , self-care , pain , and fertility . A r and om sample of general population parents were interviewed to determine cardinal preferences for the health states in the system . The health states were defined as lasting for a 60-year lifetime , starting at age 10 . Values were measured using visual analogue scaling . Utilities were measured using a st and ard gamble technique . A scoring formula is provided , based on a multiplicative multiattribute utility function from the responses of 194 subjects . The utility scores are death-anchored ( death = 0.0 ) and form an interval scale . Health Utilities Index Mark 2 and its utility scores can be useful to other research ers in a wide variety of setting s who wish to document health status and assign preference scores Purpose Many trials do not measure quality -adjusted life years ( QALYs ) . Therefore , decision analysts often map condition-specific outcomes to preference scores . We estimated the relationship between changes in preference scores and commonly reported condition-specific outcomes in patients with urinary incontinence ( UI ) due to neurogenic detrusor overactivity . Methods In 59 patients recruited to a neurogenic UI trial , clinical outcomes ( UI episodes ) , condition-specific quality of life ( Incontinence Quality of Life Instrument ( I-QOL ) ) , and SF-6D preference scores were measured at enrollment and 24 weeks . We used multiple linear regression to estimate the impact on SF-6D scores of 50 ; 50–99 and 100 % reductions in UI episodes and a 10-point improvement in I-QOL . Results By 24 weeks , mean ( 95 % CI ) daily UI episodes fell by 0.85 ( 0.04 , 1.3 ) and mean I-QOL scores improved by 18 ( 12 , 24 ) . SF-6D scores increased by 0.03 ( 0.003 , 0.058 ) , due to improvements in role limitations . A ≥ 50 % reduction in UI episodes was achieved by 49 % of patients and corresponded to a 0.09 ( 0.02 , 0.16 ) SF-6D increase . A ≥ 10-point increase in I-QOL was attained by 65 % of patients and was associated with a 0.05 ( −0.02 , 0.12 ) SF-6D increase . Conclusions These estimates provide preliminary data for decision analysts wishing to map neurogenic UI outcomes to preference scores 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 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 . 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 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 Abstract The aim of this study was to estimate the mapping model for EuroQol-5D ( EQ-5D ) utility values using the health assessment question naire disability index ( HAQ-DI ) , pain visual analog scale ( VAS ) , and disease activity score in 28 joints ( DAS28 ) in a large , nationwide cohort of rheumatoid arthritis ( RA ) patients in Korea . The KORean Observational study Network for Arthritis ( KORONA ) registry data on 3557 patients with RA were used . Data were r and omly divided into a modeling set ( 80 % of the data ) and a validation set ( 20 % of the data ) . The ordinary least squares ( OLS ) , Tobit , and two-part model methods were employed to construct a model to map to the EQ-5D index . Using a combination of HAQ-DI , pain VAS , and DAS28 , four model versions were examined . To evaluate the predictive accuracy of the models , the root-mean-square error ( RMSE ) and mean absolute error ( MAE ) were calculated using the validation data set . A model that included HAQ-DI , pain VAS , and DAS28 produced the highest adjusted R2 as well as the lowest Akaike information criterion , RMSE , and MAE , regardless of the statistical methods used in modeling set . The mapping equation of the OLS method is given as EQ-5D = 0.95−0.21 × HAQ-DI−0.24 × pain VAS/100–0.01 × DAS28 ( adjusted R2 = 57.6 % , RMSE = 0.1654 and MAE = 0.1222 ) . Also in the validation set , the RMSE and MAE were shown to be the smallest . The model with HAQ-DI , pain VAS , and DAS28 showed the best performance , and this mapping model enabled the estimation of an EQ-5D value for RA patients in whom utility values have not been measured Background Economic evaluation normally requires information to be collected on outcome improvement using utility values . This is often not collected during the treatment of substance use disorders making cost-effectiveness evaluations of therapy difficult . One potential solution is the use of mapping to generate utility values from clinical measures . This study develops and evaluates mapping algorithms that could be used to predict the EuroQol-5D ( EQ-5D-5 L ) and the ICEpop CAPability measure for Adults ( ICECAP-A ) from the three commonly used clinical measures ; the CORE-OM , the LDQ and the TOP measures . Methods Models were estimated using pilot trial data of heroin users in opiate substitution treatment . In the trial the EQ-5D-5 L , ICECAP-A , CORE-OM , LDQ and TOP were administered at baseline , three and twelve month time intervals . Mapping was conducted using estimation and validation data sets . The normal estimation data set , which comprised of baseline sample data , used ordinary least squares ( OLS ) and tobit regression methods . Data from the baseline and three month time periods were combined to create a pooled estimation data set . Cluster and mixed regression methods were used to map from this data set . Predictive accuracy of the models was assessed using the root mean square error ( RMSE ) and the mean absolute error ( MAE ) . Algorithms were vali date d using sample data from the follow-up time periods . Results Mapping algorithms can be used to predict the ICECAP-A and the EQ-5D-5 L in the context of opiate dependence . Although both measures can be predicted , the ICECAP-A was better predicted by the clinical measures . There were no advantages of pooling the data . There were 6 chosen mapping algorithms , which had MAE scores ranging from 0.100 to 0.138 and RMSE scores ranging from 0.134 to 0.178 . Conclusion It is possible to predict the scores of the ICECAP-A and the EQ-5D-5 L with the use of mapping . In the context of opiate dependence , these algorithms provide the possibility of generating utility values from clinical measures and thus enabling economic evaluation of alternative therapy options . Trial registration IS RCT N22608399 . Date of registration : 27/04/2012 . Date of first r and omisation : 14/08/2012 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 OBJECTIVES To develop an algorithm to predict the three-level EuroQol five-dimensional question naire ( EQ-5D-3L ) utility scores from the Dermatology Life Quality Index ( DLQI ) in psoriasis . METHODS This mapping study used data from the British Association of Dermatologists Biologic Interventions Register-a pharmacovigilance register comprising patients with moderate to severe psoriasis on systemic therapies . Conceptual overlap between the EQ-5D-3L and DLQI was assessed using Spearman rank correlation coefficients and exploratory factor analysis . Six regression methods to predict the EQ-5D-3L index ( direct mapping ) and two regression methods to predict EQ-5D-3L domain responses ( response mapping ) were tested . R and om effects models were explored to account for repeated observations from the same individual . Estimated and actual EQ-5D-3L utility scores were compared using 10-fold cross-validation ( in- sample ) to evaluate predictive performance . Final models were selected using root mean squared error , mean absolute error , and mean error . RESULTS The data set comprised 22,085 observations for which DLQI and EQ-5D-3L were recorded on the same day . A moderate correlation was found between the measures ( r = -0.47 ) . Exploratory factor analysis showed that two EQ-5D-3L domains ( pain/discomfort and depression/anxiety ) were associated with all six DLQI domains . The best-performing model used ordinary least squares with DLQI items , age , and sex as explanatory variables ( with squared , cubic , and interaction terms ) . A tool was produced to allow users to map their data to the EQ-5D-3L , and includes algorithms that require fewer variables ( e.g. , total DLQI scores ) . CONCLUSIONS This study produced mapping algorithms that can generate EQ-5D-3L utility scores from DLQI data for economic evaluations of health interventions for patients with psoriasis 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 In addition to theoretical justifications , many statistical methods have been used for selecting covariates to include in algorithms mapping nonutility measures onto utilities . However , it is not clear whether using exploratory factor analysis ( EFA ) as one such method improves the predictive ability of these algorithms . OBJECTIVE This question is addressed within the context of mapping a non-utility-based outcome , the core 23-item Women 's Health Question naire ( WHQ-23 ) , onto two utility instruments : five-level EuroQol five-dimensional question naire ( EQ-5D-5L ) and the six-dimensional health state short form ( derived from short form 36 health survey ) ( SF-6D ) . METHODS Data on all three outcomes were collected from 455 women from the Australian general population participating in a study assessing attitudes toward in vitro fertilization . Statistical methods for selecting covariates included stepwise regression ( SW ) , including all covariates ( Include all ) , multivariable fractional polynomial ( MFP ) , and EFA . The predictive accuracy of 108 regression models was assessed using five criteria : mean absolute error , root mean squared error , correlation , distribution of predicted utilities , and proportion of predictions with absolute errors of less than 0.0.5 . Validation of " primary " models was carried out on r and om sample s of the in vitro fertilization study . RESULTS The best results for EQ-5D-5L and SF-6D predictions were obtained from models using SW , " Include all , " and MFP covariate- selection approaches . Root mean squared error ( 0.0762 - 0.1434 ) and mean absolute error ( 0.0590 - 0.0924 ) estimates for these models were within the range of published estimates . EFA was outperformed by other covariate- selection methods . CONCLUSIONS It is possible to predict valid utilities from the WHQ-23 using regression methods based on SW , " Include all , " and MFP covariate- selection techniques 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 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 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 Multi-dimensional Bayesian network classifiers ( MBCs ) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems , where each instance in the data set has to be assigned to more than one class variable . In this paper , we propose a Markov blanket-based approach for learning MBCs from data . Basically , it consists of determining the Markov blanket around each class variable using the HITON algorithm , then specifying the directionality over the MBC subgraphs . Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions ( EQ-5D ) from the 39-item Parkinson 's Disease Question naire ( PDQ-39 ) in order to estimate the health-related quality  of  life of Parkinson 's patients . Fivefold cross-validation experiments were carried out on r and omly generated synthetic data sets , Yeast data set , as well as on a real-world Parkinson 's disease data set containing 488 patients . The experimental study , including comparison with additional Bayesian network-based approaches , back propagation for multi-label learning , multi-label k-nearest neighbor , multinomial logistic regression , ordinary least squares , and censored least absolute deviations , shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables
target: 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: 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 .