Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences Mapping between the Roland Morris Questionnaire and generic preference-based measures. Mapping of the DLQI scores to EQ-5D utility values using ordinal logistic regression Preference-Based Measurement of Health-Related Quality of Life (HRQL) in Children with Chronic Musculoskeletal Disorders (MSKDs) Mapping SF-36 onto the EQ-5D index: how reliable is the relationship? Mapping scores from the Strengths and Difficulties Questionnaire (SDQ) to preference-based utility values 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 analyses to estimate health utilities based on responses to the OM8-30 otitis media questionnaire Mapping Between the Sydney Asthma Quality of Life Questionnaire (AQLQ-S) and Five Multi-Attribute Utility Instruments (MAUIs) Paving the way for the use of the SDQ in economic evaluations of school-based population health interventions: an empirical analysis of the external validity of SDQ mapping algorithms to the CHU9D in an educational setting Validity of the Assessment of Quality of Life (AQoL) utility instrument in patients with operable and inoperable lung cancer. Estimation of a Preference-Based Index from a Condition-Specific Measure: The King's Health Questionnaire Mapping utility scores from a disease-specific quality-of-life measure in bariatric surgery patients. Development of the EXACT-U: a preference-based measure to report COPD exacerbation utilities. Documentation of Care Outcomes in an Academic Nursing Clinic: An Assessment EQ-5D-derived health utility values in patients undergoing surgery for chronic rhinosinusitis. Study protocol for valuing EQ-5D-3L and EORTC-8D health states in a representative population sample in Sri Lanka
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 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 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 Background . Health-related quality of life can be measured by patients ' health preferences ( utilities or values ) . No method for measuring health state preferences has been st and ardized for children with arthritis or other musculoskeletal disorders ( MSKDs ) . Such a method is needed for economic evaluations of current and new pediatric treatments . Objectives . 1 ) To assess the feasibility of utility measurements in children with MSKDs , 2 ) to test the validity of the Health Utility Index ( HUI ) for these children , 3 ) to assess whether rating scale values can be mathematically converted into meaningful st and ard gamble ( SG ) utilities , and 4 ) to study whether parents can act as proxies for their children with respect to health state preferences . Methods . Eighty parents of children with MSKDs were consecutively sample d. Their children , if 8 years of age or older ( n = 55 ) , were studied concurrently . Utilities of current health states were obtained by using the SG and the HUI in r and om order . In addition , health state preferences were assessed using categorical and analog rating scales . Traditional nonutility measures of health status ( the Childhood Health Assessment Question naire [ CHAQ ] and the Activities Scale for Kids [ ASK ] ) were also completed . Intraclass correlation coefficients ( ICCs ) were calculated to assess concordance between the different utility measures and also between the ratings of the parents and their children . Results . Children 8 years of age or older were able to express the strength of their health state preferences using the HUI and rating scales . Children older than 10 years of age were able to use the SG method . The health state utilities of the parents were higher than those of their children . The utilities varied widely depending on the elicitation method . The expected high agreement between the SG and the HUI was not found ( ICC = 0.028 for parents , ICC = 0.016 for patients ) . Unlike the SG , the global utilities derived from the HUI agreed better with preferences derived from rating scales ( ICC = 0.23 - 0.25 ) and correlated with traditional health status measures ( with CHAQ , r = -0.56 ; with ASK , r = 0.46 ) both for parents and children . It was not possible to mathematically convert rating scale preferences into SG utilities . The SG utilities were unrelated to results from the rating scales , the CHAQ , and the ASK . Especially for parents , the SG utilities were very high , even when ratings of the other measures indicated poor health . Conclusions . Although it is possible to measure health utilities for children with MSKDs , the results are highly method dependent . The properties of the HUI in this population are more like those of the traditional health status measures rather than those of the SG . Preferences derived from rating scales , although easily performed , can not readily be converted into SG utilities . Parents ' ratings for their children are impaired by risk aversion 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 Abstract Purpose Quality of life mapping methods such as “ Transfer to Utility ” can be used to translate scores on disease-specific measures to utility values , when traditional utility measurement methods ( e.g. st and ard gamble , time trade-off , preference-based multi-attribute instruments ) have not been used . The aim of this study was to generate preliminary ordinary least squares ( OLS ) regression-based algorithms to transform scores from the Strengths and Difficulties Question naires ( SDQ ) , a widely used measure of mental health in children and adolescents , to utility values obtained using the preference-based Child Health Utility ( CHU9D ) instrument . Methods Two hundred caregivers of children receiving community mental health services completed the  SDQ and CHU9D  during a telephone interview . Two OLS regressions were run with the CHU9D utility value as the dependent variable and SDQ subscales as predictors . Result ing algorithms were vali date d by comparing predicted and observed group mean utility values in r and omly selected sub sample s. Results Preliminary validation was obtained for two algorithms , utilising five and three subscales of the SDQ , respectively . Root mean square error values ( .124 ) for both models suggested poor fit at an individual level , but both algorithms performed well in predicting mean group observed utility values . Conclusion This research generated algorithms for translating SDQ scores to utility values and providing research ers with an additional tool for conducting health economic evaluations with child and adolescent mental health data Background 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 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 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 The Strengths and Difficulties Question naire ( SDQ ) is a behavioural screening tool for children . The SDQ is increasingly used as the primary outcome measure in population health interventions involving children , but it is not preference based ; therefore , its role in allocative economic evaluation is limited . The Child Health Utility 9D ( CHU9D ) is a generic preference-based health-related quality of-life measure . This study investigates the applicability of the SDQ outcome measure for use in economic evaluations and examines its relationship with the CHU9D by testing previously published mapping algorithms . The aim of the paper is to explore the feasibility of using the SDQ within economic evaluations of school-based population health interventions . Methods Data were available from children participating in a cluster r and omised controlled trial of the school-based roots of empathy programme in Northern Irel and . Utility was calculated using the original and alternative CHU9D tariffs along with two SDQ mapping algorithms . t tests were performed for pairwise differences in utility values from the preference-based tariffs and mapping algorithms . Results Mean ( st and ard deviation ) SDQ total difficulties and prosocial scores were 12 ( 3.2 ) and 8.3 ( 2.1 ) . Utility values obtained from the original tariff , alternative tariff , and mapping algorithms using five and three SDQ subscales were 0.84 ( 0.11 ) , 0.80 ( 0.13 ) , 0.84 ( 0.05 ) , and 0.83 ( 0.04 ) , respectively . Each method for calculating utility produced statistically significantly different values except the original tariff and five SDQ subscale algorithm . Conclusion Initial evidence suggests the SDQ and CHU9D are related in some of their measurement properties . The mapping algorithm using five SDQ subscales was found to be optimal in predicting mean child health utility . Future research valuing changes in the SDQ scores would contribute to this research There have been few longitudinal studies of quality of life in patients with all stages of lung cancer , particularly those that have included measures of utility . The purpose of this study was to examine the psychometric properties of the Assessment of Quality of Life instrument ( AQoL )  in patients with lung cancer . The AQoL is a health-related quality of life question naire and provides a descriptive system for a multi-attribute utility instrument ( MAU ) , so that scores can be used in cost-utility evaluations . In the present study the reliability ( internal consistency ) of the AQoL was examined and the concurrent validity was assessed using the Medical Outcomes 36-item Short Form Health Survey ( SF-36 ) as the comparator instrument . The sensitivity to different health states of the AQoL and the responsiveness to change over time was also examined . A prospect i ve , non-experimental cohort study was undertaken . Ninety-two participants with all stages of lung cancer were recruited from a tertiary multi-disciplinary lung cancer clinic . Ninety participants had non-small cell lung cancer ( NSCLC ) and two had limited stage small cell lung cancer . The  AQOL and SF-36 surveys  were administered concurrently at baseline . In patients with NSCLC the surveys were then repeated 3 and 6 months later . Correlations between the baseline AQoL summary scales and SF-36 summary scales support the divergent and convergent validity of the AQoL.  Reliability was also found to be sufficient ( Cronbach 's Alpha=0.76 ) . In addition , in patients with inoperable NSCLC , baseline AQoL scores were found to be predictive of survival at 6 months in Cox proportional hazards multivariate analysis . However , the physical components summary score of the SF-36 was more sensitive to differences in health states between patients with different stages of NSCLC at 6 months of follow-up and more responsive to change over time in both operable and inoperable patients with NSCLC than the AQoL. The findings support the construct validity and reliability of the  AQoL  in this population . However , there remains some uncertainty about whether the AQoL has sufficient sensitivity to different health states in this population . Further studies using other MAU instruments may determine whether alternative instruments are more sensitive to different health states in individuals with lung cancer Background . Generic preference-based measures of health may not adequately cover the impact of some conditions . There is therefore increasing interest in developing condition-specific preference-based measures . Objectives . The purpose of this study was to estimate a preference-based measure from a condition-specific measure of health for urinary incontinence , the 21-item King 's Health Question naire , for use in economic evaluation . Methods . The King 's Health Question naire ( KHQ ) was revised into a 5-dimensional health state classification amenable to valuation using items selected using psychometric evidence . Forty-nine states were valued using st and ard gamble by a representative sample of patients with urinary incontinence attending UK hospital outpatient clinics . Each respondent was asked to value 9 health states . Models have been estimated for predicting health state valuations for all 1024 states defined by the KHQ classification . The modeling had to cope with the clustering of data by respondent and its skewed distribution . Results . In total , 110 usable interviews were obtained from 169 patients approached to participate in the study . These responders generated 959 health state valuations . Mean health state values ranged from 0.77 to 0.98 . Models were estimated using mean health state values and r and om effects models of individual-level health state values . These models generated robust estimates of the ` main effects , ` and in general , the results support the ordinality of the KHQ health state classification . There were problems modeling interaction effects , and a number of alternatives were explored . Conclusion . The recommended model for estimating a preference-based measure from the condition-specific KHQ is presented 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 BACKGROUND The exacerbations of chronic obstructive pulmonary disease tool ( EXACT ) is a condition-specific daily diary recently developed to evaluate the frequency , severity , and duration of chronic obstructive pulmonary disease ( COPD ) exacerbations . A preference-based algorithm for the EXACT would allow utilities to be reported from patients during an exacerbation when EQ-5D data are not available . OBJECTIVE To develop the exacerbations of chronic obstructive pulmonary disease tool-utility ( EXACT-U ) , a condition-specific preference-based measure to report utilities from the EXACT for use in cost-effectiveness studies . METHODS Five items with three to five levels comprise the EXACT-U. Two groups of health states and respondents were constructed to allow for model development ( Development group ) and predictive validity testing ( Validation group ) using independent sample s. Members of the UK general public each valued 11 r and omized health states using time trade-offs ( TTOs ) scaled from full health/dead with 10-year duration s. Regression models estimated from the Development group using individual data , mean data , and panel design s. Models assessed by number of inconsistent coefficients estimated and R(2 ) and tested against observed utilities from the Validation group using mean absolute error ( MAE ) and root mean squared error ( RMSE ) . RESULTS A total of 55 health states , including the best and worst states , were valued in TTO interviews conducted with 400 respondents . Ten models were developed . The final preferred model contained no logical inconsistencies and found MAE = 0.04 and RMSE = 0.05 with a predicted utility range from 0.09 to 0.95 . CONCLUSIONS The EXACT-U is a condition-specific preference-based measure with strong predictive validity to report daily utilities during an exacerbation PURPOSE To assess documentation of client data collected at an academic nursing clinic using the Wilson and Cleary Health Related Quality of Life ( HRQOL ) conceptual model as a framework . DATA SOURCES A chart audit of 100 r and omly selected active client records was conducted . CONCLUSIONS Although several significant HRQOL variables were documented , data regarding general health perception and quality of life were not present . The HRQOL conceptual model provided an appropriate structure for evaluating the documentation . Further effort must be made to include key HRQOL dimensions in the clinic 's documentation system . IMPLICATION S FOR PRACTICE Documenting the quality of care provided in nursing clinics is essential in order for other professionals and the public to recognize nursing professionals as accountable and credible . This project formed the basis for a computerized outcomes -based client record system OBJECTIVES /HYPOTHESIS Health utility value ( HUV ) is an index used to measure health-related quality of life for the valuation and comparison of treatments . The Euroqol 5-Dimension ( EQ-5D ) question naire is a widely used method for determining HUV , but it has not been applied for this purpose in patients with chronic rhinosinusitis ( CRS ) who undergo sinus surgery . STUDY DESIGN Prospect i ve cohort study . METHODS Patients with CRS , who were recruited from 11 different otolaryngologic practice s , completed the EQ-5D question naire at baseline , as well as 3 , 12 , and 24 months after surgery . HUVs calculated from the results of this question naire were compared to those reported in the general U.S. population and to patients suffering from other chronic diseases . RESULTS Baseline EQ-5D surveys were completed by 242 patients .  Mean baseline HUV ( st and ard deviation ) was 0.81 ( 0.13 ) . Female gender , revision surgery , and the use of intraoperative image guidance were associated was significantly lower baseline values . HUV rose at 3 months to 0.89 ( 0.12 ) and remained improved at 12 months 0.88 ( 0.10 ) and 24 months 0.89 ( 0.10 ) ( P < 0.001 ) . Baseline HUV in CRS ( 0.81[0.13 ] ) is lower than the general U.S. population ( 0.85 [ 0.18 ] ) and appears appropriately positioned among other common chronic conditions including asthma ( 0.82 - 0.92 ) , migraine ( 0.81 - 0.91 ) , and seasonal allergies ( 0.94 ) . CONCLUSIONS Sinus surgery provides improvement in HUV in patients with CRS . These values may be paired with costs of care to perform cost-utility analysis on this group of patients . LEVEL OF EVIDENCE 2c Background Economic evaluations to inform decisions about allocation of health re sources are scarce in Low and Middle Income Countries , including in Sri Lanka . This is in part due to a lack of country-specific utility weights , which are necessary to derive appropriate Quality Adjusted Life Years . The EQ-5D-3L , a generic multi-attribute instrument ( MAUI ) , is most widely used to measure and value health states in high income countries ; nevertheless , the sensitivity of generic MAUIs has been criticised in some conditions such as cancer . This article describes a protocol to produce both a generic EQ-5D-3L and cancer specific EORTC-8D utility index in Sri Lanka . Method EQ-5D-3L and EORTC-8D health states will be valued using the Time Trade-Off technique , by a representative population sample ( n = 780 invited ) identified using stratified multi-stage cluster sampling with probability proportionate to size method . Households will be r and omly selected within 30 clusters across four districts ; one adult ( ≥18 years ) within each household will be selected using the Kish grid method . Data will be collected via face-to-face interview , with a Time Trade-Off board employed as a visual aid . Of the 243 EQ-5D-3L and 81,290 EORTC-8D health states , 196 and 84 respectively will be directly valued . In EQ-5D-3L , all health states that combine level 3 on mobility with either level 1 on usual activities or self-care were excluded . Each participant will first complete the EQ-5D-3L , rank and value 14 EQ-5D-3L states ( plus the worst health state and “ immediate death ” ) , and then rank and value seven EORTC-8D states ( plus “ immediate death ” ) . Participant demographic and health characteristics will be also collected . Regression models will be fitted to estimate utility indices for EQ-5D-3L and EORTC-8D health states for Sri Lanka . The dependent variable will be the utility value . Different specifications of independent variables will be derived from the ordinal EQ-5D-3L to test for the best-fitting model . Discussion In Sri Lanka , a LMIC health state valuation will have to be carried out using face to face interview instead of online methods . The proposed study will provide the first country-specific health state valuations for Sri Lanka , and one of the first valuations to be completed in a South Asian Country
Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .