Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences Derivation of Utility Values from European Organization for Research and Treatment of Cancer Quality of Life-Core 30 Questionnaire Values in Lung Cancer Mapping the cancer-specific EORTC QLQ-C30 to the preference-based EQ-5D, SF-6D, and 15D instruments. Converting EORTC QLQ-C30 scores to utility scores in the brigatinib ALTA study Testing alternative regression models to predict utilities: mapping the QLQ-C30 onto the EQ-5D-5L and the SF-6D Mapping of the DLQI scores to EQ-5D utility values using ordinal logistic regression Quality of life after palliative treatment for oesophageal carcinoma -- a prospective comparison between stent placement and single dose brachytherapy. 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 3L, 5L, What the L? A NICE Conundrum Mapping SF-36 onto the EQ-5D index: how reliable is the relationship? Validation of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (QLQ-C30) as a measure of psychosocial function in breast cancer patients. Mapping between the Roland Morris Questionnaire and generic preference-based measures. Mapping the SRS-22r questionnaire onto the EQ-5D-5L utility score in patients with adolescent idiopathic scoliosis Reference data for the quality of life questionnaire EORTC QLQ-C30 in the general German population. Study protocol for valuing EQ-5D-3L and EORTC-8D health states in a representative population sample in Sri Lanka Cancer of Oesophagus or Gastricus - New Assessment of Technology of Endosonography (COGNATE): report of pragmatic randomised trial. Mapping utility scores from a disease-specific quality-of-life measure in bariatric surgery patients. Is baseline quality of life useful for predicting survival with hormone-refractory prostate cancer? A pooled analysis of three studies of the European Organisation for Research and Treatment of Cancer Genitourinary Group. Mapping FACT-melanoma quality-of-life scores to EQ-5D health utility weights. Mapping the clinical chronic obstructive pulmonary disease questionnaire onto generic preference-based EQ-5D values. Quality of life and cost-effectiveness of interferon-alpha in malignant melanoma: results from randomised trial Development of a transformation model to derive general population–based utility: Mapping the pruritus–visual analog scale (VAS) to the EQ‐5D utility Prognostic value of health-related quality-of-life data in predicting survival in patients with anaplastic oligodendrogliomas, from a phase III EORTC brain cancer group study.
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 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 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 Abstract Aims : Health utilities summarize a patient ’s overall health status . This study estimated utilities based on the European Organization for Research and Treatment of Cancer Quality of Life Question naire Core-30 ( QLQ-C30 ) , a widely used measure of health-related quality -of-life ( HRQoL ) in oncology , using published mapping algorithms . Material s and methods : Data were from the Anaplastic Lymphoma Kinase ( ALK ) in Lung Cancer Trial of brigatinib ( ALTA ; NCT02094573 ) , an open-label , international , phase 2 study . ALTA evaluated the efficacy and safety of two r and omized dosing regimens of brigatinib in patients with locally advanced or metastatic ALK + non-small cell lung cancer ( NSCLC ) that had progressed on prior therapy with crizotinib . QLQ-C30 scores were mapped to European Quality -of-Life-5 Dimensions ( EQ-5D ) utility scores using two published algorithms ( Khan et al. for EQ-5D-5L ; Longworth et al. for EQ-5D-3L ) . The impact of brigatinib treatment on health utilities over time was assessed . Results : The analysis included 208 subjects . Mean baseline utility scores for both algorithms ranged between 0.60 − 0.71 and increased to 0.78 by cycle 5 . Utility improvements were sustained during most of the treatment , before disease progression . Minor variations were observed between utility scores ; Khan et al. estimates were approximately 0.01 or 0.02 points lower than Longworth et al. estimates . Limitations : Algorithms considered were limited to those available in the published literature at the time of the study . This utility analysis was exploratory , and the ALTA trial did not include an internal control group ( i.e. st and ard of care ) and was not powered to detect differences in QoL/utility outcomes between treatment arms . Conclusions : Converting QLQ-C30 scores into utilities in trials using established mapping algorithms can improve evaluation of medicines from the patient perspective . Both algorithms suggested that brigatinib  improved health utility in crizotinib-refractory ALK + NSCLC patients , and improvements were maintained during most of the treatment . Clinical trials.gov identifier : 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 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 Metal stent placement and single dose brachytherapy are commonly used treatment modalities for the palliation of inoperable oesophageal carcinoma . We investigated generic and disease-specific health-related quality of life ( HRQoL ) after these palliative treatments . Patients with dysphagia from inoperable oesophageal carcinoma were r and omised to placement of a covered Ultraflex stent ( n = 108 ) or single dose ( 12 Gy ) brachytherapy ( n = 101 ) . We obtained longitudinal data on disease-specific ( dysphagia score , European Organisation for Research and Treatment of Cancer ( EORTC ) OES-23 , visual analogue pain scale ) and generic ( EORTC Quality of Life-Core 30 Question naire ( QLQ-C30 ) , Euroqol (EQ)-5D ) HRQoL at monthly home visits by a specially-trained research nurse . We compared HRQoL between the two treatments and analysed changes in HRQoL during follow-up . Dysphagia improved more rapidly after stent placement than after brachytherapy , but long-term relief of dysphagia was better after brachytherapy . For generic HRQoL , there was an overall significant difference in favour of brachytherapy on four out of five functional scales of the EORTC QLQ-C30 ( role , emotional , cognitive and social ) ( P < 0.05 ) . Generic HRQoL deteriorated over time on all functional scales of the EORTC QLQ C-30 and EQ-5D , in particular physical and role functioning ( on average -23 and -24 on a 100 points scale during 0.5 years of follow-up ) . This decline was more pronounced in the stent group . Major improvements were seen on the dysphagia and eating scales of the EORTC OES-23 , in contrast to other scales of this disease-specific measure , which remained almost stable during follow-up . Reported levels of chest or abdominal pain remained stable during follow-up in both treatment groups , general pain levels increased to a minor extent . The effects of single dose brachytherapy on HRQoL compared favourably to those of stent placement for the palliation of oesophageal cancer . Future studies on palliative care for oesophageal cancer should at least include generic HRQoL scales , since these were more responsive in measuring patients ' functioning and well-being during follow-up than disease-specific HRQoL scales 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 For many years , the National Institute for Health and Care Excellence ( NICE ) has recommended use of the EQ-5D-3L ( 3L ) [ 1 ] and its value set for the UK [ 2 ] . Since 2011 , an exp and ed-level instrument , the EQ-5D-5L ( 5L ) , has been available [ 3 ] and value sets now exist to support its use , including a value set for Engl and [ 4 , 5 ] . This poses a challenge for NICE . Should it recommend the 5L rather than the 3L ? This is neither a trivial nor merely academic matter : the choice of whether to use the 5L ( and English value set ) or the 3L ( and UK value set ) is likely to impact estimates of quality -adjusted life-years ( QALYs ) and incremental cost-effectiveness ratios ( ICERs ) . The size and direction of that impact will depend on the disease and the nature of the health problems . In general , where technologies improve self-reported health , estimates of QALY gains will often be smaller with the 5L [ 6 ] . In contrast , where technologies extend the length of life , estimates of QALY gains will be higher ( to varying degrees ) : each year of additional life is assigned a higher utility . The ultimate impact on health technology assessment ( HTA ) will depend on whether the differences between the 3L and 5L push ICERs from one side of the cost-effectiveness threshold to the other . Given the implication s for NICE ’s technology appraisal process , and other decisions informed by EQ-5D data , the Department of Health for Engl and has called for an independent validation of the 5L value set , given its relevance to policy [ 7 ] . In 2017 , NICE released a ‘ position statement ’ [ 8 ] stating that : The 3L value set continues to be used for reference-case analyses . Where 5L data have been collected , reference-case analyses should calculate utilities by mapping the 5L descriptive system data onto the 3L value set , using the van Hout et al. [ 9 ] mapping function . NICE supports sponsors of prospect i ve clinical studies continuing to use the 5L to collect data on quality of life . A further position statement is planned for August 2018 , to be informed by evidence from various studies underway . These include studies commissioned by the English Department of Health to investigate the implication s for past NICE technology appraisal s had the 5L been used , and to collect 3L and 5L data in parallel to further improve functions for mapping from one to the other . Other studies , funded by the EuroQol Group , are also underway , investigating various aspects of the relationship between the 3L and 5L across disease areas . The 3L and its UK value set has occupied a special place in NICE ’s technology appraisal process since its inception , therefore any transition will inevitably pose challenges ; for example , reconciling potential inconsistencies between past and future decisions . Given that evidence will continue to be su bmi tted using both the 3L and 5L for years to come , if both value sets are able to be used , there is a risk of inconsistency between decisions being made in the future . HTA in other countries may also face similar issues . Given the difficulties with any transition away from the 3L , is there a case for NICE to adopt the 5L as its preferred instrument ? Papers in this issue of Pharmacoeconomics , which are cited in this commentary , address that question by investigating comparative performance of the 3L and 5L 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 The European Organisation for Research and Treatment of Cancer ( EORTC ) quality of life question naire QLQ-C30 has been developed as a quantitative measure of health-related quality of life for use in clinical trials of cancer patients . Validity is an important measurement property of all scientific tests . This study contributes to the iterative process of validating the question naire by focusing on the psychosocial subscales of the QLQ-C30 , using baseline data from 150 patients participating in a r and omised trial of supportive group therapy for metastatic breast cancer . The results provide strong support for the discriminative validity of the global health/ quality of life , role function and social function subscales of the  QLQ-C30  , in patients differing according to clinical criteria . The psychosocial focus of the trial enabled expansion of criteria used to form patient subgroups , beyond medical factors , and consequently support was demonstrated for the discriminative validity of the emotional and cognitive function subscales . The degree of support for these subscales was less substantial than for the other QLQ-C30 subscales as there were fewer relevant criteria . Convergence assessed by correlations with independent measures of psychosocial function provides strong support for the convergent validity of the emotional function , role function and global health/ quality of life subscales of the QLQ-C30 , and moderate support for the social function subscales . There was little opportunity for the cognitive function subscale to associate with conceptually analogous subscales . Further testing is recommended with more comprehensive and specific measures of cognitive status . In general , the psychosocial subscales of the QLQ-C30 appear to be measuring the concepts they are purported to measure 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 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 The objective of this study was to obtain age- and sex-specific reference values for the European Organization for Research and Treatment of Cancer ( EORTC ) Quality of Life Question naire QLQ-C30 . A r and omly selected sample of the German adult population ( 3015 subjects ) was used , 2081 subjects agreed to take part in the investigation . Most of the scales and symptom items of the question naire proved to be dependent on age and sex . Men reported fewer symptoms than women . Age differences were even more pronounced . Younger people reported better functioning and fewer symptoms . Compared with the results of a similar Norwegian study ( Hjermstad MJ , Fayers PM , Bjordal K , Kaasa S. Health related quality of life in the general Norwegian population assessed by the European Organization for research and treatment of cancer core quality -of-life question naire : The QLQ-C30(+3 ) . J Clin Oncol 1998 , 16 , 1188 - 1196 ) the prevalence of some symptoms was markedly less . Norm values for age and sex groups are given and regression analyses are performed which help to calculate expected mean scores . The results show that age and sex differences must be taken into consideration when different groups of cancer patients are compared . The norm values help to interpret quality of life data for clinicians 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 BACKGROUND Endoscopic ultrasonography is recommended for staging gastro-oesophageal cancers , but has never been evaluated . OBJECTIVE COGNATE ( Cancer of Oesophagus or Gastricus - New Assessment of Technology of Endosonography ) therefore aim ed to evaluate whether adding ' endoscopic ultrasound ' ( EUS ) to the usual staging algorithm changes treatment , improves ( quality -adjusted ) survival , and uses re sources cost-effectively . DESIGN Pragmatic parallel-group trial . Patients with gastro-oesophageal cancer received st and ard staging algorithms .  Multidisciplinary teams chose provisional management plans from endoscopic mucosal resection , immediate surgery , surgery after chemotherapy , or chemotherapy and radiotherapy . We used dynamic r and omisation to allocate consenting patients remotely by telephone in equal proportions between EUS and not . Thereafter we recorded changes in management plan , use of health-care re sources , and three aspects of participant-reported quality of life : generic [ measured by European Quality of Life - 5 Dimensions ( EQ-5D ) ] , cancer related [ Functional Assessment of Cancer Therapy - General scale ( FACT-G ) ] and  condition-specific [ FACT - Additional Concerns scale ( FACT-AC ) ] . We followed participants regularly until death or the end of the trial - for between 1 and 4.5 years . We devised a quality assurance programme to maintain st and ards of endosonographic reporting . SETTING Eight British hospitals , of which two - one Scottish teaching hospital and one English district general hospital - contributed 80 % of participants ; we combined the other six for analysis . PARTICIPANTS Patients were eligible if they had a diagnosis of gastro-oesophageal cancer , had not started treatment , were free of metastatic disease , were fit for surgery ( even if not planned ) and had American Society of Anesthesiologists and World Health Organization grade s of less than 3 . INTERVENTIONS Intervention group : st and ard staging algorithm plus EUS ; control group : st and ard staging algorithm . MAIN OUTCOME MEASURES Primary : quality -adjusted survival . Secondary : survival ; health-related quality of life ( EQ-5D , FACT-G and FACT-AC scales ) ; changes in management plan ; and complete resection rate . Although blinding participants was neither possible nor desirable , those responsible for analysis remained blind until the Trial Steering Committee had review ed the definitive analysis . RESULTS We r and omised 223 patients , of whom 213 yielded enough data for primary analysis .  EUS improved survival adjusted for generic quality of life with a hazard ratio of 0.705 [ 95 % confidence interval ( CI ) 0.499 to 0.995 ] , and crude survival with a hazard ratio of 0.706 ( 95 % CI 0.501 to 0.996 ) . The benefits of EUS were significantly greater for those with poor initial quality of life , but did not differ between centres . EUS  reduced net use of health-care re sources by £ 2860 ( 95 % ' bootstrapped ' CI from -£2200 to £ 8000 ) . Combining benefits and savings shows that EUS is likely to be cost-effective , with 96 % probability of achieving the National Institute for Health and Care Excellence criterion of costing of < £ 20,000 to gain a QALY . There were no serious adverse reactions attributable to EUS . EUS enhanced the management plan for many participants , increased the proportion of tumours completely resected from 80 % ( 44 out of 55 ) to 91 % ( 48 out of 53 ) , and improved the survival of those who changed plan ; although underpinning the significant differences in outcome , none of these process differences was itself significant . CONCLUSION Endoscopic ultrasound  significantly improves ( quality -adjusted ) survival , has the potential to reduce health-care re source use ( not statistically significant ) and is probably cost-effective ( with 96 % probability ) . We recommend research into the best time to evaluate new technologies . TRIAL REGISTRATION IS RCT N1444215 . FUNDING This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment ; Vol . 17 , No. 39 . See the HTA programme website for further project information 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 PURPOSE Patients with symptomatic metastatic hormone-resistant prostate cancer ( HRPC ) survive a median of 10 months and are often regarded as a homogeneous group . Few prognostic factors have been identified so far . We examined whether baseline health-related quality of life ( HRQOL ) parameters assessed by the European Organisation for Research and Treatment of Cancer Quality of Life Question naire C30 ( EORTC QLQ-C30 )  were independent prognostic factors of survival and whether they bring extra precision to the predictions achievable with models based on clinical and biochemical factors only . PATIENTS AND METHODS Data of 391 symptomatic ( bone ) metastatic HRPC patients from three r and omized EORTC trials were used in multivariate Cox proportional hazards models . The significance level was set at alpha = .05 . RESULTS Of the 391 patients , 371 died  , most of prostate cancer . Bone scan result , performance status , hemoglobin level , and insomnia and appetite loss as measured by the EORTC QLQ-C30 were independent predictors of survival . This model 's area under the receiver operating curve was 0.65 compared with 0.63 without the two HRQOL factors . CONCLUSION Certain HRQOL sores , at baseline , seem to be predictors for duration of survival in HRPC . However , such measurements do not add to the predictive ability of models based only on clinical and biochemical factors 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 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 A definitive conclusion regarding the value of low-dose extended duration adjuvant interferon-alpha therapy in the treatment of malignant melanoma is only possible once data on health-related quality of life ( HRQoL ) and costs have been considered . This trial r and omised 674 patients to interferon alpha-2a  ( 3 megaunits three times per week for 2 years or until recurrence ) or placebo . Health-related quality of life ( QoL ) was to be assessed up to 60 months using the European Organisation for Research and Treatment of Cancer ( EORTC ) QLQ-C30 . Data for the economic analysis , including cost information and the EQ-5D were also collected . Patients in the observation ( OBS ) group had significantly better mean follow-up quality of on five dimensions of the EORTC QLQ-C30 functional scales : role functioning ( P=0.033 ) , emotional functioning ( P=0.003 ) , cognitive functioning ( P=0.001 ) , social functioning ( P=0.003 ) and global health status ( P=0.001 ) . Patients in the OBS group had significantly better mean follow-up symptom scores on seven dimensions of the EORTC QLQ-C30 V1 symptom scales . Economic data showed that costs were £ 3066 higher in the interferon group and produces an incremental cost per quality -adjusted life year of £ 41 432 at 5 years . The results show that interferon has significant effects on QoL and symptomatology and is unlikely to be cost-effective in this patient group in the UK 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 PURPOSE This is one of a few studies that have explored the value of baseline symptoms and  health-related quality of life ( HRQOL )  in predicting survival in patients with brain cancer . PATIENTS AND METHODS Baseline  HRQOL scores ( from the European Organisation for Research and Treatment of Cancer [ EORTC ] Quality of Life Question naire C30 and the EORTC Brain Cancer Module ) were examined in 247 patients with anaplastic oligodendrogliomas to determine the relationship with overall survival by using Cox proportional hazards regression models .  Refined techniques as the bootstrap resampling procedure and the computation of C indexes and R2 coefficients were used to explore the stability of the models as well as better assess the potential benefit of using HRQOL to predict survival in clinical practice and research . RESULTS Classical analysis controlled for major clinical prognostic factors selected emotional functioning ( P = .0016 ) , communication deficit ( P = .0261 ) , future uncertainty ( P = .0481 ) , and weakness of legs ( P = .0001 ) as statistically significant prognostic factors of survival . However , several issues question the validity of these findings and no single model was found to be preferable over all others . C indexes , which estimate the probability of a model to correctly predict which patient among a r and omly chosen pair of patients will survive longer , and R2 coefficients , which measure the proportion of variability explained by the model , did not exhibit major improvement when adding selected or all HRQOL scores to clinical factors . CONCLUSION While classical techniques lead to positive results , more refined analyses suggest that baseline HRQOL scores add relatively little to clinical factors to predict survival . These results may have implication s for future use of HRQOL as a prognostic factor for patients with cancer
RESULTS ( 1 ) EQ-5D was valid and responsive for skin conditions and most cancers ; in vision , its performance varied according to aetiology ; and performance was poor for hearing impairments .
The HUI3 performed well for hearing and vision disorders .
It also performed well in cancers although evidence was limited and there was no evidence in skin conditions .
Response mapping using all the domain scores was the best performing model for the EORTC QLQ-C30 .
In an exploratory analysis , a limited dependent variable mixture model performed better than an equivalent linear model .
3 ) The exploratory valuation study found that bolt-on items for vision , hearing and tiredness had a significant impact on values of the health states , but the direction and magnitude of differences depended on the severity of the health state .
The vision bolt-on item had a statistically significant impact on EQ-5D health state values and a full valuation model was estimated .
EQ-5D performs well in studies of cancer and skin conditions .
Mapping techniques provide a solution to predict EQ-5D values where EQ-5D has not been administered .
For conditions where EQ-5D was found to be inappropriate , including some vision disorders and for hearing , bolt-ons provide a promising solution .
BACKGROUND The National Institute for Health and Care Excellence recommends the use of generic preference-based measures ( GPBMs ) of health for its Health Technology Assessment s ( HTAs ) .
However , these data may not be available or appropriate for all health conditions .
OBJECTIVES To determine whether GPBMs are appropriate for some key conditions and to explore alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate .
( 2 ) Potential modelling approaches to ' map ' EQ-5D values from condition-specific and clinical measures of health [ European Organisation for Research and Treatment of Cancer Quality -of-life Question naire Core 30 ( EORTC QLQ-C30 ) and Functional Assessment of Cancer Therapy - General Scale ( FACT-G ) ] are compared for predictive ability and goodness of fit using two separate data sets . (