Mapping IWQOL-Lite onto EQ-5D-5L and SF-6Dv2 among overweight and obese population in China

PURPOSE

To develop the mapping functions from the Impact of Weight on Quality of Life-Lite (IWQOL-Lite) scores onto the EQ-5D-5L and SF-6Dv2 utility values among the overweight and obese population in China.

METHODS

A representative sample of the overweight and obese population in China stratified by age, sex, body mass index (BMI), and area of residence was collected by online survey and the sample was randomly divided into development (80%) and validation (20%) datasets. The conceptual overlap between the IWQOL-Lite and the EQ-5D-5L or SF-6Dv2 was evaluated by Spearman's correlation coefficients. Five models, including OLS, Tobit, CLAD, GLM, and PTM were explored to derive mapping functions using the development dataset. The model performance was assessed using MAE, RMSE, and the percentage of AE > 0.05 and AE > 0.1 in the validation dataset.

RESULTS

A total of 1000 respondents (48% female; mean [SD] age: 51.7 [15.3]; mean [SD] BMI: 27.4 [2.8]) were included in this study. The mean IWQOL-Lite scores and the utility values of EQ-5D-5L and SF-6Dv2 were 78.5, 0.851, and 0.734, respectively. The best-performing models predicting EQ-5D-5L and SF-6Dv2 utilities both used IWQOL-Lite total score as a predictor in the CLAD model (MAE: 0.083 and 0.076 for the EQ-5D-5L and SF-6Dv2; RMSE: 0.125 and 0.103 for the EQ-5D-5L and SF-6Dv2; AE > 0.05: 20.5% and 27.5% for the EQ-5D-5L and SF-6Dv2; AE > 0.10: 9.5% and 15.0% for the EQ-5D-5L and SF-6Dv2).

CONCLUSION

CLAD models with the IWQOL-Lite total score can be used to predict both the EQ-5D-5L and SF-6Dv2 utility values among overweight and obese population in China.

Comparative performance and mapping algorithms between EQ-5D-5L and SF-6Dv2 among the Chinese general population

OBJECTIVES

To explore the comparative performance and develop the mapping algorithms between EQ-5D-5L and SF-6Dv2 in China.

METHODS

Respondents recruited from the Chinese general population completed both EQ-5D-5L and SF-6Dv2 during face-to-face interviews. Ceiling/floor effects were reported. Discriminative validity in self-reported chronic conditions was investigated using the effect sizes (ES). Test-retest reliability was evaluated using intra-class correlation coefficient (ICC) and Bland-Altman plots in a subsample. Correlation and absolute agreements between the two measures were estimated with Spearman's rank correlation coefficient and ICC, respectively. Ordinary least squares (OLS), generalized linear model, Tobit model, and robust MM-estimator were explored to estimate mapping equations between EQ-5D-5L and SF-6Dv2.

RESULTS

3320 respondents (50.3% males; age 18-90 years) were recruited. 51.1% and 12.2% of respondents reported no problems on all EQ-5D-5L and SF-6Dv2 dimensions, respectively. The mean EQ-5D-5L utility was higher than SF-6Dv2 (0.947 vs. 0.827, p < 0.001). Utilities were significantly different across all chronic conditions groups for both measures. The mean absolute difference of utilities between the two tests for EQ-5D-5L was smaller (0.033 vs. 0.043) than SF-6Dv2, with a slightly higher ICC (0.859 vs. 0.827). Fair agreement (ICC = 0.582) was observed in the utilities between the two measures. Mapping algorithms generated by the OLS models performed the best according to the goodness-of-fit indicators.

CONCLUSIONS

Both measures showed comparable discriminative validity. Systematic differences in utilities were found, and on average, the EQ-5D-5L generates higher values than the SF-6Dv2. Mapping algorithms between the EQ-5D-5L and SF-6Dv2 are reported to enable transformations between these two measures in China.

Mapping Studies to Estimate Health-State Utilities From Nonpreference-Based Outcome Measures: A Systematic Review on How Repeated Measurements are Taken Into Account

OBJECTIVES

Mapping algorithms are developed using data sets containing patient responses to a preference-based questionnaire and another health-related quality-of-life questionnaire. When data sets include repeated measurements from the same individuals over time, the assumption of observations' independence, required by standard models, is violated, and standard errors are underestimated. This review aimed to identify how studies deal with methodological challenges of repeated measurements, provide an overview of practice to date, and potential implications for future work.

METHODS

We conducted a systematic literature search of MEDLINE, Cumulative Index to Nursing and Allied Health Literature, specialized databases, and previous systematic reviews. A data template was used to extract, among others, start and target instruments if the data set(s) used for estimation and validation had repeated measurements per patient, used regression techniques, and which (if any) adjustments were made for repeated measurements.

RESULTS

We identified 278 publications developing at least 1 mapping algorithm. Of the 278 publications, 121 used a data set with repeated measurements, among which 92 used multiple time points for estimation, and 39 selected specific time points to have 1 observation per participant. A total of 36 studies did not account for repeated measurements. An adjustment was conducted using cluster-robust standard errors (21), random-effects models (30), generalized estimating equations (7), and other methods (7).

CONCLUSIONS

The inconsistent use of methods to account for interdependent observations in the literature indicates that mapping guidelines should include recommendations on how to deal with repeated measurements, and journals should update their guidelines accordingly.

Mapping of the World Health Organization Quality of Life Brief (WHOQOL-BREF) to the EQ-5D-5L in the General Thai Population

PURPOSE

This study aimed at mapping the World Health Organization Quality of Life Brief (WHOQOL-BREF) and the EQ-5D-5L in the general Thai population and to determine the impact on the incremental cost-utility ratio (ICUR) through five hypothetical scenarios.

METHODS

A total of 1,200 Thai participants were randomly allocated into the 'estimation' and 'validation' groups. A curve estimation with nine regression models was performed to identify the best-fit regression model of significant WHOQOL-BREF dimension scores for the EQ-5D-5L index score predictions in the estimation group. The identified model was then used for the calculation of the predicted EQ-5D-5L index scores in the validation group. The percentage change from the hypothetical base-case scenario with predefined parameters was used to determine the impact on the ICUR.

RESULTS

An inverse model was the best-fit regression model to predict the EQ-5D-5L index scores. The absolute difference between the predicted and observed index scores was 0.064, and the percentage of the sample that was mispredicted by ≥ 0.05 and ≥ 0.1 was 43.8% and 16.8%, respectively. Moreover, the percentage change in ICUR ranged between 0.13 and 1.84% from the hypothetical base-case scenario.

CONCLUSIONS

An inverse relationship between the studied scores was identified. The minimal impact on the ICUR suggests that the Health Utility Index of the mapped equation can be applied to economic analyses.

Improving the lives of ethnically diverse family carers and people living with dementia using digital media resources - Protocol for the Draw-Care randomised controlled trial

Objectives

Ethnically diverse family carers of people living with dementia (hereafter carers and people with dementia) experience more psychological distress than other carers. To reduce this inequality, culturally adapted, multilingual, evidence-based practical assistance is needed. This paper details the Draw-Care study protocol including a randomised control trial (RCT) to test the effectiveness of a digital intervention comprising a multilingual website, virtual assistant, animated films, and information, on the lives of carers and people with dementia in Australia.

Methods

The Draw-Care intervention will be evaluated in a 12-week active waitlist parallel design RCT with 194 carers from Arabic, Cantonese, Greek, Hindi, Italian, Mandarin, Spanish, Tamil, and Vietnamese-speaking language groups. Our intervention was based on the World Health Organization's (WHO) iSupport Lite online carer support messages and was co-designed with carers, people with dementia, service providers, and clinicians. Culturally adapted multilingual digital resources were created in nine languages and English.

Results

In Phase I (2022), six co-design workshops with stakeholders and interviews with people with dementia informed the development of the intervention which will be trialled and evaluated in Phases II and III (2023 and 2024).

Conclusions

Digital media content is a novel approach to providing cost-effective access to health care information. This study protocol details the three study phases including the RCT of a co-designed, culturally adapted, multilingual, digital intervention for carers and people with dementia to advance the evidence in dementia and digital healthcare research and help meet the needs of carers and people with dementia in Australia and globally.

Mapping algorithms for predicting EuroQol-5D-3L utilities from the assessment test of chronic obstructive pulmonary disease

To predict 3-Level version of European Quality of Life-5 Dimensions (EQ-5D-3L) questionnaire utility from the chronic obstructive pulmonary disease (COPD) assessment test (CAT), the study attempts to collect EQ-5D-3L and CAT data from COPD patients. Response mapping under a backward elimination procedure was used for EQ-5D score predictions from CAT. A multinomial logistic regression (MLR) model was used to identify the association between the score and the covariates. Afterwards, the predicted scores were transformed into the utility. The developed formula was compared with ordinary least squares (OLS) regression models and models using Mean Rank Method (MRM). The MLR models performed as well as other models according to mean absolute error (MAE) and root mean squared error (RMSE) evaluations. Besides, the overestimation for low utility patients (utility ≤ 0.6) and underestimation for near health (utility > 0.9) in the OLS method was improved through the means of the MLR model based on bubble chart analysis. In conclusion, response mapping with the MLR model led to performance comparable to the OLS and MRM models for predicting EQ-5D utility from CAT data. Additionally, the bubble charts analysis revealed that the model constructed in this study and MRM could be a better predictive model.

Mapping World Health Organization Quality of Life-BREF Onto 5-Level EQ-5D in Thai Patients With Chronic Diseases

OBJECTIVES

This study aimed to map the World Health Organization Quality of Life-BREF (WHOQOL-BREF) onto the 5-level EQ-5D (EQ-5D-5L) using a real Thai valuation set of the EQ-5D-5L. The second objective was to explore the impacts of the differences between observed and predicted EQ-5D-5L index scores on the incremental cost-utility ratio (ICUR) using 5 hypothetical scenarios.

METHODS

This is a secondary data analysis. A total of 800 outpatients with chronic diseases were recruited from 2 university hospitals in Bangkok, Thailand, between July 2014 and March 2015. The 800 patients were randomly divided into 2 samples: estimation and validation samples. The estimation sample was used to assess the relationships between the EQ-5D-5L index score and 4 WHOQOL-BREF dimension scores and to find the best-fit model and its equation. For the validation sample, the equation of the best-fit model from the estimation sample was used to calculate predicted EQ-5D-5L index scores.

RESULTS

A multiple linear regression showed that only the physical domain of the WHOQOL-BREF was significantly associated with the EQ-5D-5L. Among 11 regression models, the curve estimation found that the inverse model was the best-fit model. The prediction equation of EQ-5D-5L was equal to 1.385 minus 7.572/physical domain of the WHOQOL-BREF. The impacts of the differences between the observed and predicted EQ-5D-5L index scores on ICUR were only 0.4% to 1.8% from the base case.

CONCLUSIONS

A nonlinear relationship between the physical domain of the WHOQOL-BREF and EQ-5D-5L utility was shown. The impacts of the differences between the observed and predicted EQ-5D-5L index scores on ICUR were minimal.

Current Status of Research on the Mapping Function of Health Utility Values in the Asia Pacific Region: A Systematic Review

OBJECTIVES

This systematic review aimed to analyze the published studies on the use of the mapping method between generic scales and disease-specific scales as well as between 2 universal scales.

METHODS

A systematic literature search was conducted using PubMed, ScienceDirect, Web of Science, CNKI, Weipa Database, Wanfang Database, and HERC Database to collect articles about the application of the mapping method to the measurement of health utility value from January 2000 to December 2019.

RESULTS

Overall, 59 articles met the inclusion requirements, and most of them were a mapping study between a disease-specific scale and a generic scale. Then all these articles were classified by the following study types: a clear functional relationship; unclear functional relationship; disease-specific scale and universality; mapping between generic scales and disease-specific scales, and mapping between universal scales. Most studies derived the best mapping model from the ordinary least squares regression, and fewer studies chose to use new regression methods. Sample sizes in the retrieved studies generally affected the reliability of the study results.

CONCLUSIONS

In recent years, as more attention has been paid to the research of the mapping method, a large number of problems have followed, such as the selection of scale types, the coverage of the study sample, and the selection of evaluation index of model performance and sample size. It is hoped that these problems can be properly solved in the future research.

Assessing the severity of psychiatric disorders using the Health of the Nation Outcome Scales: An equipercentile linking analysis

OBJECTIVE

The Health of the Nation Outcome Scales was developed as an overall measure of mental health, applicable to the complete range of psychiatric disorders. Meanwhile, it is a benchmark tool for service providers and is also used for the allocation of costs and funding. The ability of the Health of the Nation Outcome Scales to assess and differentiate the severity of psychiatric disorders is largely unknown, as it is the interpretation of a change in score. We aim to establish Health of the Nation Outcome Scales cut-off and benchmark values for severity and improvement - respectively change, using equipercentile linking to the Clinical Global Impression scales.

METHODS

In a clinical sample of 30,616 individuals with a psychiatric disorder, we used a multivariate regression analysis to determine the correlation between the scales and possible confounders. We used an equipercentile linking analysis of the Clinical Global Impressions severity scale with the Health of the Nation Outcome Scales sum score to establish cut-off values for severity. The linking of the Health of the Nation Outcome Scales sum score difference and the percentage of change to the Clinical Global Impression improvement scale determined benchmark values for change (i.e. improvement or deterioration).

RESULTS

The Health of the Nation Outcome Scales and Clinical Global Impression scales showed a Spearman correlation of 0.38 (p < 0.000). Clinical Global Impression-Severity: 'borderline-ill' corresponded to Health of the Nation Outcome Scales score 3-5; 'mildly ill' to 6-10; 'moderately ill' to 11-16; 'markedly ill' to 17-25; 'severely ill' to 26-35; and 'extremely ill' to a score ⩾36. The Spearman correlation between the percentage change of the Health of the Nation Outcome Scales was 0.39 (p > 0.000); Clinical Global Impression-Improvement: 'minimally improved' corresponded to Health of the Nation Outcome Scales reduction of 4 points or 9%; 'much-improved' to 12 points or 48%; 'very-much-improved' to ⩾20 points or ⩾90%. Clinical Global Impression-Improvement: 'minimally worse' corresponded to an increase of 6 points or 25%; 'much-worse' to 12 points or 54%; and finally, 'very-much-worse' to >18 points or ⩾82%.

CONCLUSION

Our results allow for the comparison of severity and response to treatment of patients with a psychiatric disorder, independent of diagnosis.

What Is a Valid Mapping Algorithm in Cost-Utility Analyses? A Response From a Missing Data Perspective

OBJECTIVES

Although numerous mapping algorithms from a non-preference-based measure to a target health utility measure have been developed and applied in cost-utility analyses (CUAs), conditions for a mapping algorithm to work well in a CUA are still unclear. In this research, we formulate the mapping problem as a missing data problem and clarify these conditions.

METHODS

We defined a valid mapping algorithm based on the purpose of mapping (ie, not for prediction but for CUA), and derived a sufficient set of conditions for a valid mapping algorithm. We also conducted a simulation study to investigate properties of a mapping algorithm under situations where the conditions are satisfied and violated.

RESULTS

The derived sufficient conditions indicate that the complete overlap of the source measure with the target health utility measure is important and that a covariate that is omitted from a mapping algorithm but has an effect on the target health utility measure not captured by the source measure may invalidate a mapping algorithm. The conditions cannot be verified from data in a CUA but can be supported using external data. A simulation study showed that when at least 1 of the 3 conditions was violated, a mapping algorithm provided biased health utility estimates in a CUA, and that prediction accuracy did not necessarily reflect performance of a mapping algorithm in a CUA.

CONCLUSION

The derived conditions provide a fundamental basis for better practices in developing and selecting a mapping algorithm.

Mapping Dermatology Life Quality Index (DLQI) scores to EQ-5D utility scores using data of patients with atopic dermatitis from the National Health and Wellness Study

PURPOSE

To develop a mapping algorithm for generating EQ-5D-5-level (EQ-5D-5L) utility scores from the Dermatology Life Quality Index (DLQI) in patients with atopic dermatitis (AD).

METHODS

The algorithm was developed using data from 1232 patients from four countries participating in the National Health and Wellness Study. Spearman's rank correlation coefficient was used to evaluate the conceptual overlap between DLQI and EQ-5D-5L. Six mapping models (ordinary least squares [OLS], Tobit, three different two-part models, and a regression mixture model) were tested with different specifications to determine model performance and were ranked based on the sum of mean absolute error (MAE), and root mean squared error (RMSE).

RESULTS

The mean DLQI score was 7.23; mean EQ-5D-5L score was 0.78; and there were moderate negative correlations between DLQI and EQ-5D-5L scores (p = - 0.514). A regression mixture model with total DLQI, and age and sex as independent variables performed best for mapping DLQI to EQ-5D-5L (RMSE = 0.113; MAE = 0.079).

CONCLUSION

This was the first study to map DLQI to EQ-5D-5L exclusively in patients with AD. The regression mixture model with total DLQI, and age and sex as independent variables was the best performing model and accurately predicted EQ-5D-5L. The results of this mapping can be used to translate DLQI data from clinical studies to health state utility values in economic evaluations.

Development of algorithms to estimate EQ-5D and derive health utilities from WHOQOL-HIV Bref: a mapping study

PURPOSE

This study aimed to develop and evaluate different families of applicable models available for utility mapping between World Health Organization Quality of Life for HIV-abbreviated version (WHOQOL-HIV Bref) and EQ-5D-3L and to propose an optimised algorithm to estimate health utilities of people living with HIV.

METHODS

Estimation dataset was collected between July 2014 and September 2016 in a cross-sectional study including 1526 people living with HIV/Aids (PLWH) under care at the Instituto Nacional de Infectologia Evandro Chagas-FIOCRUZ, in Brazil. Data of WHOQOL-HIV Bref and EQ-5D-3L questionnaires were collected. Fisher's exact tests were used for testing WHOQOL-HIV Bref response frequencies among groups of responses to each of the five EQ-5D-3L domains. Multiple correspondence analyses (MCA) were used to inspect the relationships between both instrument responses. Different families of applicable models available for utility mapping between WHOQOL-HIV Bref and EQ-5D-3L were adjusted for the prediction of disutility.

RESULTS

Candidate models' performances using mean absolute error (MAE), mean squared error (MSE), and root mean squared error (RMSE) were similarly good, which was evidenced by the overlapping of its 95% confidence intervals of the mean tenfold cross-validation or estimated generalisation errors. However, the Hurdle Logistic-Log-Normal model was better on average according to generalisation errors both in the prediction of Brazilian utility values (MAE = 0.1037, MSE = 0.0178, and RMSE = 0.1332) and for those of the UK (MAE = 0.1476, MSE = 0.0443, and RMSE = 0.2099).

CONCLUSIONS

Mapping EQ-5D-3L responses or deriving health utilities directly from WHOQOL-HIV Bref responses can be a valid alternative for settings with no preference-based health utility data.

Assessing the severity of functional impairment of psychiatric disorders: equipercentile linking the mini-ICF-APP and CGI

Background

The assessment of functioning and impairment due to psychiatric illness has been acknowledged to be crucial for research and practice. This led to the development of the mini-ICF-APP, which provides a reliable and time-efficient measure of functioning and impairment. Although its use is increasing, it remains unclear how it reflects severity and how change might be interpreted from a clinical perspective.

Methods

In a clinical sample of 3067 individuals hospitalized for mental health treatment, we used an equipercentile approach to link the mini-ICF-APP with the Clinical Global Impression scale (CGI) at admission and discharge. We linked the mini-ICF-APP sum score to the CGI-S scale and the mini-ICF-APP proportional change between admission and discharge to the CGI-I scale.

Results

The mini-ICF-APP and CGI scales showed a Spearman correlation of 0.50 (p < .000). CGI-S: “borderline-ill” corresponded to a mini-ICF-APP score 1–2; “mildly-ill” to 3–7; “moderately-ill” to 8–15; “markedly-ill” to 16–24; “severely-ill” to 25–37; and “extremely-ill” to a score ≥ 38. The Spearman correlation between the percentage change of mini-ICF-APP sum score and the CGI-I was 0.32 (p > .000); “no-change” in the CGI-I corresponded to an increase or decrease of 2%; “minimally-improved” to a mini-ICF-APP reduction of 3–30%; “much-improved” to a reduction of 31–63%; “very-much-improved” to a reduction of ≥64% “minimally-worse” to an increase of 3–34% “much-worse” to an increase of 35–67%; and finally “very-much-worse” with an increase of ≥68%.

Conclusions

Our findings improve understanding of the clinical meaning of the mini-ICF-APP sum score and percentage change in patients hospitalized for treatment.

Evaluation of the Association Between Health State Utilities and Obesity in Sub-Saharan Africa: Evidence From World Health Organization Study on Global AGEing and Adult Health Wave 2

BACKGROUND

Obesity is a major public health challenge and its prevalence has increased across the age spectrum from 1980 to date in most parts of the world including sub-Saharan Africa. Studies that derive health state utilities (HSUs) stratified by weight status to support the conduct of economic evaluations and prioritization of cost-effective weight management interventions are lacking in sub-Saharan Africa.

OBJECTIVES

To estimate age- and sex-specific HSUs for Ghana, along with HSUs by weight status. Associations between HSUs and overweight and obesity will be examined.

STUDY DESIGN

Cross-sectional survey of the Ghanaian population.

METHODS

Data were sourced from the World Health Organization Study of Global AGEing and Adult Health (WHO SAGE), 2014 to 2015. Using a "judgment-based mapping" method, responses to items from the World Health Organization Quality-of-Life (WHOQOL-100) used in the WHO SAGE were mapped to EQ-5D-5L profiles, and the Zimbabwe value set was applied to calculate HSUs. Poststratified sampling weights were applied to estimate mean HSUs, and a multivariable linear regression model was used to examine associations between HSUs and overweight or obesity.

RESULTS

Responses from 3966 adults aged 18 to 110 years were analyzed. The mean (95% confidence interval) HSU was 0.856 (95% CI: 0.850, 0.863) for the population, 0.866 (95% CI: 0.857, 0.875) for men, and 0.849 (95% CI: 0.841, 0.856) for women. Lower mean HSUs were observed for obese individuals and with older ages. Multivariable regression analysis showed that HSUs were negatively associated with obesity (-0.024; 95% CI: -0.037, -0.011), female sex (-0.011; 95% CI: -0.020, -0.003), and older age groups in the population.

CONCLUSIONS

The study provides HSUs by sex, age, and body mass index (BMI) categories for the Ghanaian population and examines associations between HSU and high BMI. Obesity was negatively associated with health state utility in the population. These data can be used in future economic evaluations for Ghana and sub-Saharan African populations.

An Updated Systematic Review of Studies Mapping (or Cross-Walking) Measures of Health-Related Quality of Life to Generic Preference-Based Measures to Generate Utility Values

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 methodological developments in this area since a previous review up to 2007.

OBJECTIVE

To provide an updated review of all mapping studies that map from HRQoL measures to target generic preference-based measures (EQ-5D measures, SF-6D, HUI measures, QWB, AQoL measures, 15D/16D/17D, CHU-9D) published from January 2007 to October 2018.

DATA SOURCES

A systematic review of English language articles using a variety of approaches: searching electronic and utilities databases, citation searching, targeted journal and website searches.

STUDY SELECTION

Full papers of studies that mapped from one health measure to a target preference-based measure using formal statistical regression techniques.

DATA EXTRACTION

Undertaken by four authors using predefined data fields including measures, data used, econometric models and assessment of predictive ability.

RESULTS

There were 180 papers with 233 mapping functions in total. Mapping functions were generated to obtain EQ-5D-3L/EQ-5D-5L-EQ-5D-Y (n = 147), SF-6D (n = 45), AQoL-4D/AQoL-8D (n = 12), HUI2/HUI3 (n = 13), 15D (n = 8) CHU-9D (n = 4) and QWB-SA (n = 4) HSUVs. A large number of different regression methods were used with ordinary least squares (OLS) still being the most common approach (used ≥ 75% times within each preference-based measure). The majority of studies assessed the predictive ability of the mapping functions using mean absolute or root mean squared errors (n = 192, 82%), but this was lower when considering errors across different categories of severity (n = 92, 39%) and plots of predictions (n = 120, 52%).

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.

Mapping the medical outcomes study HIV health survey (MOS-HIV) to the EuroQoL 5 Dimension (EQ-5D-3 L) utility index

Background

Mapping of health-related quality-of-life measures to health utility values can facilitate cost-utility evaluation. Regression-based methods tend to lead to shrinkage of variance. This study aims to map the Medical Outcomes Study HIV Health Survey (MOS-HIV) to EuroQoL 5 Dimensions (EQ-5D-3 L) utility index, and to characterize the performance of three mapping methods, including ordinary least squares (OLS), equi-percentile method (EPM), and a recently proposed method called Mean Rank Method (MRM).

Methods

This is a secondary analysis of data from a randomized HIV treatment trial. Baseline data from 421 participants were used to develop mapping functions. Follow-up data from 236 participants was used to validate the mapping functions.

Results

In the training dataset, MRM and OLS, but not EPM, reproduced the observed mean utility (0.731). MRM, OLS and EPM under-estimated the standard deviation by 0.3, 26.6 and 1.7%, respectively. MRM had the lowest mean absolute error (0.143) and highest intraclass correlation coefficient (0.723) with the observed utility values, whereas OLS had the lowest mean squared error (0.038) and highest R-squared (0.542). Regressing the MRM- and OLS-mapped utility values upon body mass index and log-viral load gave covariate associations comparable to those estimated from the observed utility data (all P > 0.10). EPM did not achieve this property. Findings from the validation data were similar.

Conclusions

Functions are available for mapping the MOS-HIV to the EQ-5D-3 L utility values. MRM and OLS were comparable in terms of agreement with the observed utility values at the individual level. MRM had better performance at the group level in terms of describing the utility distribution.

Trial registration

NCT00988039. Registered 30 September 2009.

Electronic supplementary material

The online version of this article (10.1186/s12955-019-1135-8) contains supplementary material, which is available to authorized users.

Measurement equivalence of the English, Chinese and Malay versions of the World Health Organization quality of life (WHOQOL-BREF) questionnaires

Background

The WHOQOL-BREF is a widely used questionnaire for measuring quality of life. It is important to establish the measurement equivalence of various language versions of WHOQOL-BREF so that scores from different language versions may be pooled together. The primary aim of this article was to evaluate the measurement equivalence of the English, Chinese and Malay versions of the WHOQOL-BREF.

Methods

We analysed data from the previously published, cross-sectional, WONDERS study and used linear regression models to adjust for potential confounding variables. Based on equivalence clinical trial methods, measurement equivalence was assessed by comparing 90% confidence interval (CI) of differences in scores across language versions with a predefined equivalence margin of 0.3 SD. Equivalence was achieved if the 90% CI fell within 0.3 SD. Data from 1203 participants, aged above 21 years, were analysed.

Results

Participants who completed the different language versions of WHOQOL-BREF expectedly differed in age, ethnicity, highest education level, marital status, smoking status and Body Mass Index (BMI). The English and Malay language versions were definitely equivalent for all domains. The English and Chinese language versions were definitely equivalent for physical and environmental domains but inconclusive for psychological and social domains. Likewise, for Chinese and Malay versions.

Conclusion

The English, Chinese and Malay language versions of the WHOQOL-BREF questionnaire may be considered equivalent, with evidence being more robust for some domains than the others. Given the large number of people who speak/ read Chinese and Malay, this study has widespread relevance.

Development of Conversion Functions Mapping the FACT-B Total Score to the EQ-5D-5L Utility Value by Three Linking Methods and Comparison with the Ordinary Least Square Method

INTRODUCTION

Health-related quality-of-life (HRQoL) measures are commonly mapped to a value that represents a utility for economic evaluation via regression models, which may lead to shrinkage of the variance.

OBJECTIVES

This study aimed to develop and compare conversion functions that map the Functional Assessment of Cancer Therapy-Breast (FACT-B) total score to the EuroQoL 5-Dimensions, 5-Levels (EQ-5D-5L) utility value via four methods.

METHODS

We used the HRQoL scores of 238 Singapore patients with breast cancer to develop the conversion function for the equipercentile, linear equating, mean rank and ordinary least squares (OLS) methods. We compared the distributions of the observed values and the four sets of mapped values and performed regression analyses to assess whether the association with risk factors was preserved by utility values derived from mapping.

RESULTS

At baseline, the observed EQ-5D-5L utility value had a mean ± standard deviation (SD) of 0.820 ± 0.152, and 24.8% of the respondents attained a value of 1. The OLS method (mean 0.820; SD 0.112; proportion 0%) better agreed with the observed data than the equipercentile (mean 0.831; SD 0.152; proportion 23.5%), linear equating (mean 0.814; SD 0.145; proportion 11.8%) and mean rank method (mean 0.821; SD 0.147; proportion 23.9%). The significance of association was preserved for all parameters involved in the regression analyses by the equipercentile and linear equating methods, but the mean rank and OLS methods were inconsistent with the observed data for one and two parameters, respectively.

CONCLUSION

The problem of shrinkage in the variance occurred in the OLS method, but it provided an unbiased estimate for the mean and better agreement. Among the other three linking methods, the mean rank method better described the distribution, whereas the equipercentile and linear equating methods better assessed the association with risk factors.

Mapping the Alzheimer's Disease Cooperative Study-Activities of Daily Living Inventory to the Health Utility Index Mark III

PURPOSE

To map the Alzheimer's Disease Cooperative Study-Activities of Daily Living Inventory (ADCS-ADL) to the Health Utility Index Mark III (HUI3) in people living with dementia (PWD) and to compare the performance of five methods for mapping.

METHODS

A cross-sectional study of 346 dyads of community-dwelling PWD and family caregiver was carried out in Singapore. ADCS-ADL and HUI3 were rated by the family caregivers. Disease severity ratings and Mini Mental State Examination (MMSE) results were retrieved from medical records. A recently proposed mapping method called the Mean Rank Method (MRM) was described and applied, and the results were compared with regression-based mapping, including ordinary least squares, censored least absolute deviation (CLAD), Tobit and response mapping.

RESULTS

The MRM produced a mapped utility distribution that closely resembled the observed utility distribution. The standard deviations (SDs) of the observed and MRM-mapped utility were both 0.340, whereas the SDs of the other mapped utilities ranged from 0.243 (response mapping) to 0.283 (CLAD). Regressing the MRM- and CLAD-mapped and observed utility values upon disease severity and MMSE gave similar regression lines (each P > 0.05). Regressing the other mapped utility values upon the covariates under- (over-) estimated the utility of good (poor) clinical states. However, regression-based mapping methods gave a better fit at the individual level, as measured by root mean square error, mean absolute error and R². K fold cross-validation gave similar results.

CONCLUSIONS

The MRM is accurate at the group level. The regression-based mapping methods are more accurate for making individual-level prediction. In addition, CLAD also performed reasonably well at the group level.