Development of Methods for the Mapping of Utilities Using Mixture Models: Mapping the AQLQ-S to the EQ-5D-5L and the HUI3 in Patients with Asthma

Development of algorithms to estimate the EQ-5D-5L from the FACT-L in patients with lung cancer: a mapping study

OBJECTIVE

This study aimed to develop a mapping algorithm to evaluate the EQ-5D-5L according to the FACT-L when the EQ-5D-5L is not available.

METHODS

EQ-5D-5L and FACT-L data were collected from patients with lung cancer in Departments of Thoracic Surgery, Medical Oncology, Radiation Oncology, Sichuan Cancer Hospital. We used the ordinary least squares model (OLS), Tobit model (Tobit), two-part model (TPM), beta mixture regression (BM), and censored least absolute deviation model (CLAD) to map the results of the FACT-L according to EQ-5D-5L scores. To establish these models, the total score, dimension scores, squared items, and interaction items were introduced. Performance metrics including Adjusted R2, root mean square error (RMSE), and mean absolute error (MAE) were used to select the optimized model.

RESULTS

The model with the best mapping performance was the BM model (BETAMIX4) with the PWB (physical well-being) dimension, FWB (functional well-being) dimension, the squared term of the PWB dimension, and the squared term of the FWB dimension as covariates. The final prediction metrics were Adjusted R2 = 0.695, RMSE = 0.206, and MAE = 0.109. Fivefold cross-validation (CV) results also demonstrated that the BM model had the best mapping power.

CONCLUSIONS

This study developed an optimized mapping algorithm to predict the utility index from the FACT-L to the EQ-5D-5L, which provides an effective alternative reference for EQ-5D-5L estimation when the preference-based health utility values were unavailable.

Mapping the EORTC QLQ-C30 and QLQ H&N35 to the EQ-5D-5L and SF-6D for papillary thyroid carcinoma

PURPOSE

Empirical evidence for the EORTC QLQ C30 scale in thyroid cancer mapping algorithms has not been found in China, which limits the cost-utility analysis of patients with papillary thyroid carcinoma (PTC) population. We developed mapping algorithms that use the EORTC QLQ-C30 and QLQ H&N35 to predict EQ-5D-5L and SF-6D health utility scores for PTC patients.

METHODS

Data from 1050 Chinese PTC patients who completed the EORTC QLQ-C30, QLQ H&N35, EQ-5D-5L and SF-6D instruments were collected. Direct mapping (OLS, Tobit, Betamix) and indirect mapping functions (Order Probit) were used to estimate algorithms. The goodness-of-fit of mapping performance was assessed by MAE, RMSE, AIC, BIC, AE, and ICC. A fivefold cross-validation and random sample validation approach were used to test the stability of the models.

RESULTS

The mean EQ-5D-5L and SF-6D utility scores were 0.8704 and 0.6368, respectively. We recommend the Betamix model for the EQ-5D-5L (MAE = 0.0363, RMSE = 0.0505, AIC = -3458.73, BIC = -3096.91, AE > 0.05(%) = 48.38, AE > 0.1(%) = 8.67, ICC = 0.8288 for the full sample dataset) and the Betamix model for the SF-6D (MAE = 0.0328, RMSE = 0.0417, AIC = -2788.91, BIC = -2605.51, AE > 0.05(%) = 42.76, AE > 0.1(%) = 3.62, ICC = 0.8657 for the full sample dataset), with EORTC QLQ-C30 all items, QLQ H&N35 all items, age and gender as the predicted variables showing the best performance.

CONCLUSION

In the absence of preference-based quality of life tools, the mapping algorithms reported here are effective alternative for predicting the health utility of PTC patients, contributing to the cost-utility analysis studies.

Mapping Short Warwick and Edinburgh Mental Wellbeing Scale (SWEMWBS) to Recovering Quality of Life (ReQoL) to estimate health utilities

BACKGROUND

The Short Warwick and Edinburgh Mental Wellbeing Scale (SWEMWBS) is a widely used non-preference-based measure of mental health in the UK. The primary aim of this paper is to construct an algorithm to translate the SWEMWBS scores to utilities using the Recovering Quality of Life Utility Index (ReQoL-UI) measure.

METHODS

Service users experiencing mental health difficulties were recruited in two separate cross-sectional studies in the UK. The following direct mapping functions were used: Ordinary Least Square, Tobit, Generalised Linear Models. Indirect (response) mapping was performed using seemingly unrelated ordered probit to predict responses to each of the ReQoL-UI items and subsequently to predict using UK tariffs of the ReQoL-UI from SWEMWBS. The performance of all models was assessed by the mean absolute errors, root mean square errors between the predicted and observed utilities and graphical representations across the SWEMWBS score range.

RESULTS

Analyses were based on 2573 respondents who had complete data on the ReQoL-UI items, SWEMWBS items, age and sex. The direct mapping methods predicted ReQoL-UI scores across the range of SWEMWBS scores reasonably well. Very little differences were found among the three regression specifications in terms of model fit and visual inspection when comparing modelled and actual utility values across the score range of the SWEMWBS. However, when running simulations to consider uncertainty, it is clear that response mapping is superior.

CONCLUSIONS

This study presents mapping algorithms from SWEMWBS to ReQoL as an alternative way to generate utilities from SWEMWBS. The algorithm from the indirect mapping is recommended to predict utilities from the SWEMWBS.

Prediction of the SF-6D utility score from Lung cancer FACT-L: a mapping study in China

OBJECTIVE

To develop a mapping algorithm for generating the Short Form Six-Dimension (SF-6D) utility score based on the Functional Assessment of Cancer Therapy-Lung (FACT-L) of lung cancer patients.

METHODS

Data were collected from 625 lung cancer patients in mainland China. The Spearman rank correlation coefficient and principal component analysis were used to evaluate the conceptual overlap between the FACT-L and SF-6D. Five model specifications and four statistical techniques were used to derive mapping algorithms, including ordinary least squares (OLS), Tobit and beta-mixture regression models, which were used to directly estimate health utility, and ordered probit regression was used to predict the response level. The prediction performance was evaluated using the correlations between the root mean square error (RMSE), mean absolute error (MAE), concordance correlation coefficient (CCC), Akaike information criterion (AIC) and Bayesian information criterion (BIC) and the observed and predicted SF-6D scores. A five-fold cross-validation method was used to test the universality of each model and select the best model.

RESULTS

The average FACT-L score was 103.024. The average SF-6D score was 0.774. A strong correlation was found between FACT-L and SF-6D scores (ρ = 0.797). The ordered probit regression model with the total score of each dimension and its square term, as well as age and sex as covariates, was most suitable for mapping FACT-L to SF-6D scores (5-fold cross-validation: RMSE = 0.0854; MAE = 0.0655; CCC = 0.8197; AEs > 0.1 (%) = 53.44; AEs > 0.05 (%) = 21.76), followed by beta-mixture regression for direct mapping. The Bland‒Altman plots showed that the ordered probit regression M5 had the lowest proportion of prediction scores outside the 95% agreement limit (-0.166, 0.163) at 4.96%.

CONCLUSIONS

The algorithm reported in this paper enables lung cancer data from the FACT-L to be mapped to the utility of the SF-6D. The algorithm allows the calculation of quality-adjusted life years for cost-utility analyses of lung cancer.

Enabling QALY estimation in mental health trials and care settings: mapping from the PHQ-9 and GAD-7 to the ReQoL-UI or EQ-5D-5L using mixture models

PURPOSE

Patient-reported outcome measures (PROMs) are commonly collected in trials and some care settings, but preference-based PROMs required for economic evaluation are often missing. For these situations, mapping models are needed to predict preference-based (aka utility) scores. Our objective is to develop a series of mapping models to predict preference-based scores from two mental health PROMs: Patient Health Questionnaire-9 (PHQ-9; depression) and Generalised Anxiety Questionnaire-7 (GAD-7; anxiety). We focus on preference-based scores for the more physical-health-focussed EQ-5D (five-level England and US value set, and three-level UK cross-walk) and more mental-health-focussed Recovering Quality-of-Life Utility Index (ReQoL-UI).

METHODS

We used trial data from the Improving Access to Psychological Therapies (IAPT) mental health services (now called NHS Talking Therapies), England, with a focus on people with depression and/or anxiety caseness. We estimated adjusted limited dependent variable or beta mixture models (ALDVMMs or Betamix, respectively) using GAD-7, PHQ-9, age, and sex as covariates. We followed ISPOR mapping guidance, including assessing model fit using statistical and graphical techniques.

RESULTS

Over six data collection time-points between baseline and 12-months, 1340 observed values (N ≤ 353) were available for analysis. The best fitting ALDVMMs had 4-components with covariates of PHQ-9, GAD-7, sex, and age; age was not a probability variable for the final ReQoL-UI mapping model. Betamix had practical benefits over ALDVMMs only when mapping to the US value set.

CONCLUSION

Our mapping functions can predict EQ-5D-5L or ReQoL-UI related utility scores for QALY estimation as a function of variables routinely collected within mental health services or trials, such as the PHQ-9 and/or GAD-7.

Using a Sample Size Calculation Framework for Clinical Prediction Models When Developing and Selecting Mapping Algorithms Based on Linear Regression

PURPOSE

To propose using a framework for calculating the sample size for clinical prediction models when developing and selecting mapping algorithms from a health-related quality-of-life (HRQOL) measure onto the score of a preference-based measure (PBM) using linear regression.

METHODS

The framework was summarized for health economics researchers. Mapping studies that mapped the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 onto the EQ-5D-3L index using linear regression were evaluated in terms of sample size. The required sample size for each study was calculated using 4 criteria: global shrinkage factor ≥ 0.9, difference between the apparent and adjusted R2 ≤ 0.05, multiplicative margin of error in the estimated residual standard deviation ≤ 1.1, and absolute margin of error in the estimated model intercept ≤ 0.025.

RESULTS

Ten mapping studies were identified. The information required to calculate the sample size was successfully extracted from previous mapping studies. Four of 10 mapping studies did not have sufficient sample sizes.

LIMITATIONS

Further extension of this framework to other regression approaches used in mapping studies is necessary.

CONCLUSIONS

The sample size should be considered when developing and selecting a mapping algorithm based on linear regression.

HIGHLIGHTS

No recommendation or guidance is available for the sample size to develop and select a mapping algorithm from a health-related quality-of-life measure onto the score of a preference-based measure.This research proposes using a framework for calculating the sample size for clinical prediction models in sample size consideration for mapping algorithms using linear regression.A survey showed that the information required to calculate the sample size could be successfully extracted from previous mapping studies and that 4 of 10 mapping studies did not have sufficient sample sizes.

Obtaining SF-6D utilities from FACT-H&N in thyroid carcinoma patients: development and results from a mapping study

Objective

There is limited evidence for mapping clinical tools to preference-based generic tools in the Chinese thyroid cancer patient population. The current study aims to map the FACT-H&N (Functional Assessment of Cancer Therapy-Head and Neck Cancer) to the SF-6D (Short Form Six-Dimension), which will inform future cost-utility analyses related to thyroid cancer treatment.

Methods

A total of 1050 participants who completed the FACT-H&N and SF-6D questionnaires were included in the analysis. Four methods of direct and indirect mapping were estimated: OLS regression, Tobit regression, ordered probit regression, and beta mixture regression. We evaluated the predictive performance in terms of root mean square error (RMSE), mean absolute error (MAE), concordance correlation coefficient (CCC), Akaike information criterion (AIC) and Bayesian information criterion (BIC) and the correlation between the observed and predicted SF-6D scores.

Results

The mean value of SF-6D was 0.690 (SD = 0.128). The RMSE values for the fivefold cross-validation as well as the 30% random sample validation for multiple models in this study were 0.0833-0.0909, MAE values were 0.0676-0.0782, and CCC values were 0.6940-0.7161. SF-6D utility scores were best predicted by a regression model consisting of the total score of each dimension of the FACT-H&N, the square of the total score of each dimension, and covariates including age and gender. We proposed to use direct mapping (OLS regression) and indirect mapping (ordered probit regression) to establish a mapping model of FACT-H&N to SF-6D. The mean SF-6D and cumulative distribution functions simulated from the recommended mapping algorithm generally matched the observed ones.

Conclusions

In the absence of preference-based quality of life tools, obtaining the health status utility of thyroid cancer patients from directly mapped OLS regression and indirectly mapped ordered probit regression is an effective alternative.

Mapping the Seattle Angina Questionnaire to EQ-5D-5L in patients with coronary heart disease

BACKGROUND

Health economic evaluation is critical in supporting novel cardiovascular disease therapies. However, most clinical studies do not include preference-based questionnaires to calculate utilities for health economic evaluations. Thus, this study aimed to develop mapping algorithms that convert the Seattle Angina Questionnaire (SAQ) to EQ-5D-5L health utility scores for patients with coronary health disease (CHD) in China.

METHODS

Data were obtained from a longitudinal study of patients with CHD conducted at the Tianjin Medical University General Hospital in China. Convenience sampling was used to recruit patients with CHD. The inclusion criteria were having been diagnosed with CHD through a medical examination and being aged 18 years or older. The exclusion criteria were a lack of comprehension ability, serious comorbidities, mental illness, and hearing or vision impairment. All eligible patients were invited to participate, and 305 and 75 patients participated at baseline and in the follow-up, respectively. Seven regression models were developed using a direct approach. Furthermore, we predicted the five EQ-5D items using ordered logit model and derived the utility score from predicted responses using an indirect approach. Model performances were evaluated using mean absolute error (MAE), root mean squared error (RMSE), correlation coefficient (ρ), and Lin's concordance correlation coefficient (CCC). A five-fold cross-validation method was used to evaluate internal validation.

RESULTS

The average age was 63.04 years, and 53.72% of the included patients were male. Most (70.05%) patients had unstable angina pectoris, and the mean illness duration was 2.50 years. The EQ-5D scores were highly correlated with five subscales of the SAQ, with Spearman's rank correlation coefficients ranging from 0.6184 to 0.7093. The mixture beta model outperformed the other regression models in the direct approach, with the lowest MAE and RMSE and highest ρ and CCC. The ordered logit model in the indirect approach performed the same as the mixture beta regression with equal MAE, lower RMSE, and higher ρ and CCC.

CONCLUSION

Mapping algorithms developed using mixture beta and ordered logit models accurately converted SAQ scores to EQ-5D-5L health utility values, which could support health economic evaluations related to coronary heart disease.

Mapping the schizophrenia quality of life scale to EQ-5D, HUI3 and SF-6D utility scores in patients with schizophrenia

OBJECTIVES

The current study aimed to map the disease-specific Schizophrenia Quality of Life Scale (SQLS) onto the three- and five-level EuroQol five-dimension (EQ-5D-3 L and EQ-5D-5 L), Health Utility Index Mark 3 (HUI3) and Short Form six-dimensional (SF-6D) preference-based instruments to inform future cost-utility analyses for treatment of patients with schizophrenia.

METHODS

Data from 251 outpatients with schizophrenia spectrum disorders was included for analysis. Ordinary least square (OLS), Tobit and beta regression mixture models were employed to estimate the utility scores. Three regression models with a total of 66 specifications were determined by goodness of fit and predictive indices. Distribution of the original data to the distributions of the data generated using the preferred estimated models were then compared.

RESULTS

EQ-5D-3 L and EQ-5D-5 L were best predicted by the OLS model, including SQLS domain scores, domain-squared scores, age, and gender as explanatory predictors. The models produced the best performance index and resembled most closely with the observed EQ-5D data. HUI3 and SF-6D were best predicted by the OLS and Tobit model respectively.

CONCLUSION

The current study developed mapping models for converting SQLS scores into generic utility scores, which can be used for economic evaluation among patients with schizophrenia.

Mapping the EORTC QLQ-C30 onto the EQ-5D-5L index for patients with paroxysmal nocturnal hemoglobinuria in France

Aim: To map patient-level data collected on the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC) QLQ-C30 to EQ-5D-5L data for estimating health-state utilities in patients with paroxysmal nocturnal hemoglobinuria (PNH). Materials & methods: European cross-sectional PNH patient survey data populated regression models mapping EORTC QLQ-C30 domains (covariates: sex and baseline age) to utilities calculated with the EQ-5D-5L French value set. A genetic algorithm allowed selection of the best-fitting between a set of models with and without interaction terms. We validated the selected algorithm using EQ-5D-5L utilities converted from EORTC QLQ-C30 data collected in the PEGASUS phase III, randomized controlled trial of pegcetacoplan versus eculizumab in adults with PNH. Results: Selected through the genetic algorithm, the ordinary least squares model without interactions provided highly stable results across study visits (mean [±SD] utilities 0.58 [±0.42] to 0.89 [±0.10]), and showed the best predictive validity. Conclusion: The new PNH EQ-5D-5L direct mapping developed using a genetic algorithm enabled calculation of reliable health-state utility data required for cost-utility analysis in health technology assessments supporting treatments of PNH.

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 the Oxford Shoulder Score onto the EQ-5D utility index

PURPOSE

In order to enable cost-utility analysis of shoulder pain conditions and treatments, this study aimed to develop and evaluate mapping algorithms to estimate the EQ-5D health index from the Oxford Shoulder Score (OSS) when health outcomes are only assessed with the OSS.

METHODS

5437 paired OSS and EQ-5D questionnaire responses from four national multicentre randomised controlled trials investigating different shoulder pathologies and treatments were split into training and testing samples. Separate EQ-5D-3L and EQ-5D-5L analyses were undertaken. Transfer to utility (TTU) regression (univariate linear, polynomial, spline, multivariable linear, two-part logistic-linear, tobit and adjusted limited dependent variable mixture models) and response mapping (ordered logistic regression and seemingly unrelated regression (SUR)) models were developed on the training sample. These were internally validated, and their performance evaluated on the testing sample. Model performance was evaluated over 100-fold repeated training-testing sample splits.

RESULTS

For the EQ-5D-3L analysis, the multivariable linear and splines models had the lowest mean square error (MSE) of 0.0415. The SUR model had the lowest mean absolute error (MAE) of 0.136. Model performance was greatest in the mid-range and best health states, and lowest in poor health states. For the EQ-5D-5L analyses, the multivariable linear and splines models had the lowest MSE (0.0241-0.0278) while the SUR models had the lowest MAE (0.105-0.113).

CONCLUSION

The developed models now allow accurate estimation of the EQ-5D health index when only the OSS responses are available as a measure of patient-reported health outcome.

Mapping health assessment questionnaire disability index onto EQ-5D-5L in China

Objective

This research aimed to develop the more accurate mapping algorithms from health assessment questionnaire disability index (HAQ-DI) onto EQ-5D-5L based on Chinese Rheumatoid Arthritis patients.

Methods

The cross-sectional data of Chinese RA patients from 8 tertiary hospitals across four provincial capitals was used for constructing the mapping algorithms. Direct mapping using Ordinary least squares regression (OLS), the general linear regression model (GLM), MM-estimator model (MM), Tobit regression model (Tobit), Beta regression model (Beta) and the adjusted limited dependent variable mixture model (ALDVMM) and response mapping using Multivariate Ordered Probit regression model (MV-Probit) were carried out. HAQ-DI score, age, gender, BMI, DAS28-ESR and PtAAP were included as the explanatory variables. The bootstrap was used for validation of mapping algorithms. The average ranking of mean absolute error (MAE), root mean square error (RMSE), adjusted R ² (adjR ²) and concordance correlation coefficient (CCC) were used to assess the predictive ability of the mapping algorithms.

Results

According to the average ranking of MAE, RMSE, adjR ², and CCC, the mapping algorithm based on Beta performed the best. The mapping algorithm would perform better as the number of variables increasing.

Conclusion

The mapping algorithms provided in this research can help researchers to obtain the health utility values more accurately. Researchers can choose the mapping algorithms under different combinations of variables based on the actual data.

Patients' and Caregivers' Experiences With Atopic Dermatitis-Related Burden, Medical Care, and Treatments in 8 Countries

BACKGROUND

Previous studies have documented the high patient and caregiver burden associated with atopic dermatitis (AD). Less is known about the factors-especially those related to treatment options and the delivery of medical care-that may relate to burden and unmet needs among patients and their caregivers.

OBJECTIVE

Our primary aim was to characterize and compare health-related quality of life, long-term control of symptoms, satisfaction with treatments, the financial burden, and the prevalence of patient-centered care among adult and pediatric patients with AD in 8 developed nations.

METHODS

We developed a 53-item anonymous online survey for adult patients and caregivers of children with AD (N = 3171; self-reported disease severity: 8.2% clear, 33.2% mild, 41.1% moderate, 17.6% severe). The survey included questions across 7 domains selected by a steering committee of 11 patient organizations that advocate for patients with AD in the 8 countries. We used validated instruments when available including the 5-level EuroQol five-dimensional questionnaire and the Atopic Dermatitis Control Tool. The survey was offered in 5 languages and promoted through social media and other communication channels of the patient organizations.

RESULTS

The health-related quality-of-life scores for adult patients with AD (driven by 2 domains: pain/discomfort and anxiety/depression) were worse than those reported for asthma and type 2 diabetes in previous studies (0.72; 95% CI, 0.65-0.78). Patients and caregivers reported substantial financial impacts even in countries with government-funded health care systems, though the greatest impact was in the United States. In all countries, adults reported better control of symptoms than children, but neither group nor any nationality reported adequate control on average (rescaled mean, 57.5; 95% CI, 56.1-58.9), and control correlated negatively with disease severity. Similarly, satisfaction with treatments, which was moderate across countries on average, was much lower for respondents with more severe disease symptoms (F(3,3165) = 5.5; P < .001). Patients who saw a specialist (a dermatologist or an allergist) instead of a general practitioner for AD care indicated better long-term control of symptoms (by 4 points on average on the 100-point scale; 95% CI, 2.6-5.4; P < .001). Finally, self-management training and shared decision making were uncommonly reported by patients in all countries except by respondents from the United States, but both were associated with better long-term control of symptoms and higher satisfaction.

CONCLUSIONS

The burden of AD, evaluated as health-related quality-of-life detriments, financial impacts, and uncontrolled symptoms, is significant and highest for patients with more severe atopic dermatitis who report greater challenges in achieving symptom resolution with existing treatments and approaches to care. The better outcomes associated with respondents who saw specialists suggest that patients, especially those with more severe AD, might benefit from medical care that is guided by providers with more in-depth knowledge of this complex condition. Finally, wider use of patient-centered care practices (specifically, self-management training and shared decision making) could improve outcomes and boost satisfaction with treatments for AD, though more research on this topic is warranted.

Health-related quality of life in adult patients with asthma according to asthma control and severity: A systematic review and meta-analysis

Background: The utility values are increasingly being used in economic evaluations and health policy decision making. This study aims to conduct a systematic literature review and meta-analysis of the utility values for asthma, particularly with respect to severity and asthma control.

Materials and methods: A literature search was conducted using the MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases for studies published until July, 2020, reporting the utilities of adult asthma. We extracted utility values derived by nine indirect and four direct utility instruments. Meta-analyses were performed for each utility instrument according to health states based on the level of asthma control and severity.

Results: Fifty-two eligible studies were included in our systematic review, of which forty studies were used in the meta-analyses. Among the 13 utility instruments, the most used was EQ-5D-3L, whereas EQ-5D-5L showed the narrowest 95% confidence interval (95% CI, 0.83–0.86) of pooled utility. The pooled utility of asthma declined with worsening control levels and severity. The pooled utility value of EQ-5D-3L was 0.72 (95% CI, 0.63–0.80) for uncontrolled, 0.82 (95% CI, 0.75–0.88) for partly controlled, and 0.87 (95% CI, 0.84–0.90) for well-controlled asthma.

Conclusion: Our study shows that EQ-5D-3L and EQ-5D-5L are appropriate for economic evaluations in terms of availability and variability of information, respectively. Asthma patients had poorer utility values with worsened severity and level of asthma control. This study will be useful for health economists conducting economic evaluations of asthma treatments.

Estimating the impact of changes in weight and BMI on EQ-5D-3L: a longitudinal analysis of a behavioural group-based weight loss intervention

PURPOSE

To estimate the association between changes in BMI and changes in Health-Related Quality of Life (EQ-5D-3L).

METHODS

The WRAP trial was a multicentre, randomised controlled trial with parallel design and recruited 1267 adults (BMI ≥ 28 kg/m2). Participants were allocated to Brief Intervention, a Commercial weight management Programme (WW, formerly Weight Watchers) for 12 weeks, or the same Programme for 52 weeks. Participants were assessed at 0, 3, 12, 24, and 60 months. We analysed the relationship between BMI and EQ-5D-3L, adjusting for age and comorbidities, using a fixed effects model. Test for attrition, model specification and missing data were conducted. Secondary analyses investigated a non-symmetric gradient for weight loss vs. regain.

RESULTS

A unit increase in BMI was associated with a - 0.011 (95% CI - 0.01546, - 0.00877) change in EQ-5D-3L. A unit change in BMI between periods of observation was associated with - 0.016 017 (95% CI - 0.0077009, - 0.025086) change in EQ-5D-3L. The negative association was reduced during weight loss, as opposed to weight gain, but the difference was not statistically significant.

CONCLUSIONS

We have identified a strong and statistically significant negative relationship between BMI changes and HRQoL. These estimates could be used in economic evaluations of weight loss interventions to inform policymaking.

CLINICAL TRIAL REGISTRATION

This trial was registered with Current Controlled Trials, number ISRCTN82857232.

Generating EQ-5D-5L health utility scores from BASDAI and BASFI: a mapping study in patients with axial spondyloarthritis using longitudinal UK registry data

BACKGROUND

Preference-based health-state utility values (HSUVs), such as the EuroQol five-dimensional questionnaire (EQ-5D-5L), are needed to calculate quality-adjusted life-years (QALYs) for cost-effectiveness analyses. However, these are rarely used in clinical trials of interventions in axial spondyloarthritis (axSpA). In these cases, mapping can be used to predict HSUVs.

OBJECTIVE

To develop mapping algorithms to estimate EQ-5D-5L HSUVs from the Bath Ankylosing Disease Activity Index (BASDAI) and the Bath Ankylosing Spondylitis Functional Index (BASFI).

METHODS

Data from the British Society for Rheumatology Biologics Register in Ankylosing Spondylitis (BSRBR-AS) provided 5122 observations with complete BASDAI, BASFI, and EQ-5D-5L responses covering the full range of disease severity. We compared direct mapping using adjusted limited dependent variable mixture models (ALDVMMs) and optional inclusion of the gap between full health and the next feasible value with indirect response mapping using ordered probit (OPROBIT) and generalised ordered probit (GOPROBIT) models. Explanatory variables included BASDAI, BASFI, and age. Metrics to assess model goodness-of-fit and performance/accuracy included Akaike and Bayesian information criteria (AIC/BIC), mean absolute error (MAE) and root mean square error (RMSE), plotting predictive vs. observed estimates across the range of BASDAI/BASFI and comparing simulated data with the original data set for the preferred/best model.

RESULTS

Overall, the ALDVMM models that did not formally include the gap between full health and the next feasible value outperformed those that did. The four-component mixture models (with squared terms included) performed better than the three-component models. Response mapping using GOPROBIT (no squared terms included) or OPROBIT (with squared terms included) offered the next best performing models after the three-component ALDVMM (with squared terms). Simulated data of the preferred model (ALDVMM with four-components) did not significantly underestimate uncertainty across most of the range of EQ-5D-5L values, however the proportion of data at full health was underrepresented, likely due in part to model fitting on a small number of observations at this point in the actual data (4%).

CONCLUSIONS

The mapping algorithms developed in this study enabled the generation of EQ-5D-5L utilities from BASDAI/BASFI. The indirect mapping equations reported for the EQ-5D-5L facilitate the calculation of the EQ-5D-5L utility scores using other UK and country-specific value sets.

Economic Evaluation: A Randomized Pragmatic Trial of a Primary Care-based Cognitive Behavioral Intervention for Adults Receiving Long-term Opioids for Chronic Pain

BACKGROUND

Chronic pain is prevalent and costly; cost-effective nonpharmacological approaches that reduce pain and improve patient functioning are needed.

OBJECTIVE

Report the incremental cost-effectiveness ratio (ICER), compared with usual care, of cognitive behavioral therapy aimed at improving functioning and pain among patients with chronic pain on long-term opioid treatment.

DESIGN

Economic evaluation conducted alongside a pragmatic cluster randomized trial.

SUBJECTS

Adults with chronic pain on long-term opioid treatment (N=814).

INTERVENTION

A cognitive behavioral therapy intervention teaching pain self-management skills in 12 weekly, 90-minute groups delivered by an interdisciplinary team (behaviorists, nurses) with additional support from physical therapists, and pharmacists.

OUTCOME MEASURES

Cost per quality adjusted life year (QALY) gained, and cost per additional responder (≥30% improvement on standard scale assessment of Pain, Enjoyment, General Activity, and Sleep). Costs were estimated as-delivered, and replication.

RESULTS

Per patient intervention replication costs were $2145 ($2574 as-delivered). Those costs were completely offset by lower medical care costs; inclusive of the intervention, total medical care over follow-up was $1841 lower for intervention patients. Intervention group patients also had greater QALY and responder gains than did controls. Supplemental analyses using pain-related medical care costs revealed ICERs of $35,000, and $53,000 per QALY (for replication, and as-delivered intervention costs, respectively); the ICER when excluding patients with outlier follow-up costs was $106,000.

LIMITATIONS

Limited to 1-year follow-up; identification of pain-related utilization potentially incomplete.

CONCLUSION

The intervention was the optimal choice at commonly accepted levels of willingness-to-pay for QALY gains; this finding was robust to sensitivity analyses.

HIT-6 and EQ-5D-5L in patients with migraine: assessment of common latent constructs and development of a mapping algorithm

OBJECTIVE

The aims of this study were to assess whether there is a conceptual overlap between the questionnaires HIT-6 and EQ-5D and to develop a mapping algorithm allowing the conversion of HIT-6 to EQ-5D utility scores for Germany.

METHODS

This study used data from an ongoing randomised controlled trial for patients suffering from migraine. We assessed the conceptual overlap between the two instruments with correlation matrices and exploratory factor analysis. Linear regression, tobit, mixture, and two-part models were used for mapping, accounting for repeated measurements, tenfold cross-validation was conducted to validate the models.

RESULTS

We included 1010 observations from 410 patients. The EQ-5D showed a substantial ceiling effect (47.3% had the highest score) but no floor effect, while the HIT-6 showed a very small ceiling effect (0.5%). The correlation between the instruments' total scores was moderate (- 0.30), and low to moderate among each domain (0.021-0.227). The exploratory factor analysis showed insufficient conceptual overlap between the instruments, as they load on different factors. Thus, there is reason to believe that the instruments' domains do not capture the same latent constructs. To facilitate future mapping, we provide coefficients and a variance-covariance matrix for the preferred model, a two-part model with the total HIT-6 score as the explanatory variable.

CONCLUSION

This study showed that the German EQ-5D and the HIT-6 lack the conceptual overlap needed for appropriate mapping. Thus, the estimated mapping algorithms should only be used as a last resort for estimating utilities to be employed in economic evaluations.

Mapping of the acromegaly quality of life questionnaire to ED-5D-5L index score among patients with acromegaly

OBJECTIVE

This study aimed to develop a mapping function that links the acromegaly quality of life (AcroQoL) questionnaire to EQ-5D-5L to obtain a preference-based utility value to inform economic evaluation.

METHODS

A nationwide cross-sectional questionnaire survey among patients with acromegaly was conducted online in China during 17 December 2019 to 6 January 2020. The study sample was randomly divided into a training set and a validation set. Ordinary least squares (OLS), Tobit, beta-based mixture, and adjusted limited dependent variable mixture models were tested for development of the function in the training set. Total and subscale scores and individual items of AcroQoL were included as predictors in the models along with their squared terms and demographic and clinical characteristics, and selected by backward stepwise selection. The root mean square error, mean absolute error, Akaike's information criterion, Bayesian information criterion and adjusted R-square were used to assess goodness of fit and predictive ability of the models.

RESULTS

There were 424 adult patients with acromegaly eligible for this analysis. Average EQ-5D-5L index score and AcroQoL score for them was 0.82 (SD = 0.15) and 44.3 (SD = 22.9), respectively. A total of 60 candidate models were tested. Considering model simplicity and predictive ability in both training and validation set, the best model was the OLS model using scores of physical dimension and its square term as predictors.

CONCLUSION

A validated mapping function was developed in this study for estimating EQ-5D scores using AcroQoL outcomes. Its external validity can be further tested in other population with Acromegaly.

Mapping the EORTC QLQ-C30 to EQ-5D-3L in patients with breast cancer

Background

The types of outcomes measured collected in clinical studies and those required for cost-effectiveness analysis often differ. Decision makers routinely use quality adjusted life years (QALYs) to compare the benefits and costs of treatments across different diseases and treatments using a common metric. QALYs can be calculated using preference-based measures (PBMs) such as EQ-5D-3L, but clinical studies often focus on objective clinician or laboratory measured outcomes and non-preference-based patient outcomes, such as QLQ-C30. We model the relationship between the generic, preference-based EQ-5D-3L and the cancer specific quality of life questionnaire, QLQ-C30 in patients with breast cancer. This will result in a mapping that allows users to convert QLQ-C30 scores into EQ-5D-3L scores for the purposes of cost-effectiveness analysis or economic evaluation.

Methods

We use data from a randomized trial of 602 patients with HER2-positive advanced breast cancer provided 3766 EQ-5D-3L observations. Direct mapping using adjusted, limited dependent variable mixture models (ALDVMM) is compared to a random effects linear regression and indirect mapping using seemingly unrelated ordered probit models. EQ-5D-3L was estimated as a function of the summary scales of the QLQ-C30 and other patient characteristics.

Results

A four component mixture model outperformed other models in terms of summary fit statistics. A close fit to the observed data was observed across the range of disease severity. Simulated data from the model closely aligned to the original data and showed that mapping did not significantly underestimate uncertainty. In the simulated data, 22.15% were equal to 1 compared to 21.93% in the original data. Variance was 0.0628 in the simulated data versus 0.0693 in the original data. The preferred mapping is provided in Excel and Stata files for the ease of users.

Conclusion

A four component adjusted mixture model provides reliable, non-biased estimates of EQ-5D-3L from the QLQ-C30, to link clinical studies to economic evaluation of health technologies for breast cancer. This work adds to a growing body of literature demonstrating the appropriateness of mixture model based approaches in mapping.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08964-5.

Mapping the PHQ-8 to EQ-5D, HUI3 and SF6D in patients with depression

BACKGROUND

There is limited evidence of mapping clinical instruments to a generic preference-based instrument in Asian patient populations. The current study aims to map the eight-item Patient Health Questionnaire depression scale (PHQ-8) onto the EuroQol Five-Dimension (EQ-5D), the Health Utilities Index Mark 3 (HUI3) and the Short Form Six-Dimension (SF-6D) which helps to inform future cost-utility analyses of treatments for depression.

METHODS

A total of 249 participants who had completed PHQ-8, EQ-5D, SF-6D and HUI3 questionnaires were included in the analyses. A beta regression mixture model was used to map the utility scores as a function of PHQ-8 total scores, PHQ-squared, age and gender. The predictive accuracy of the models was examined using mean absolute error and root mean square error.

RESULTS

The results were compared against two common regression methods including Ordinary Least Square (OLS) and Tobit regression models. The mean age of the sample was 36.2 years (SD = 11.1). The mean EQ-5D-3L, EQ-5D-5L, HUI3 and SF-6D utility scores were 0.615, 0.709, 0.461 and 0.607, respectively. The EQ-5D-3L, EQ-5D-5L and SF-6D utility scores were best predicted by the beta mixture regression model consisting of PHQ-8 total sores, PHQ-squared, and covariates including age and gender. The HUI3 was best predicted by the OLS regression model.

CONCLUSIONS

The current study provides important evidence to clinicians and researchers about the mapping algorithms that can be used in economic evaluation among patients with depression.

Health-Related Quality of Life in Patients With Different Diseases Measured With the EQ-5D-5L: A Systematic Review

Background: The EQ-5D-5L is a generic preference-based questionnaire developed by the EuroQol Group to measure health-related quality of life (HRQoL) in 2005. Since its development, it has been increasingly applied in populations with various diseases and has been found to have good reliability and sensitivity. This study aimed to summarize the health utility elicited from EQ-5D-5L for patients with different diseases in cross-sectional studies worldwide.

Methods: Web of Science, MEDLINE, EMBASE, and the Cochrane Library were searched from January 1, 2012, to October 31, 2019. Cross-sectional studies reporting utility values measured with the EQ-5D-5L in patients with any specific disease were eligible. The language was limited to English. Reference lists of the retrieved studies were manually searched to identify more studies that met the inclusion criteria. Methodological quality was assessed with the Agency for Health Research and Quality (AHRQ) checklist. In addition, meta-analyses were performed for utility values of any specific disease reported in three or more studies.

Results: In total, 9,400 records were identified, and 98 studies met the inclusion criteria. In the included studies, 50 different diseases and 98,085 patients were analyzed. Thirty-five studies involving seven different diseases were included in meta-analyses. The health utility ranged from 0.31 to 0.99 for diabetes mellitus [meta-analysis random-effect model (REM): 0.83, (95% CI = 0.77–0.90); fixed-effect model (FEM): 0.93 (95% CI = 0.93–0.93)]; from 0.62 to 0.90 for neoplasms [REM: 0.75 (95% CI = 0.68–0.82); FEM: 0.80 (95% CI = 0.78–0.81)]; from 0.56 to 0.85 for cardiovascular disease [REM: 0.77 (95% CI = 0.75–0.79); FEM: 0.76 (95% CI = 0.75–0.76)]; from 0.31 to 0.78 for multiple sclerosis [REM: 0.56 (95% CI = 0.47–0.66); FEM: 0.67 (95% CI = 0.66–0.68)]; from 0.68 to 0.79 for chronic obstructive pulmonary disease [REM: 0.75 (95% CI = 0.71–0.80); FEM: 0.76 (95% CI = 0.75–0.77)] from 0.65 to 0.90 for HIV infection [REM: 0.84 (95% CI = 0.80–0.88); FEM: 0.81 (95% CI = 0.80–0.82)]; from 0.37 to 0.89 for chronic kidney disease [REM: 0.70 (95% CI = 0.48–0.92; FEM: 0.76 (95% CI = 0.74–0.78)].

Conclusions: EQ-5D-5L is one of the most widely used preference-based measures of HRQoL in patients with different diseases worldwide. The variation of utility values for the same disease was influenced by the characteristics of patients, the living environment, and the EQ-5D-5L value set.

Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42020158694.

Mapping the Memorial Anxiety Scale for Prostate Cancer to the SF-6D

PURPOSE

To create a crosswalk that predicts Short Form 6D (SF-6D) utilities from Memorial Anxiety Scale for Prostate Cancer (MAX-PC) scores.

METHODS

The data come from prostate cancer patients enrolled in the North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS, N = 1016). Cross-sectional data from 12- to 24-month follow-up were used as estimation and validation datasets, respectively. Participants' SF-12 scores were used to generate SF-6D utilities in both datasets. Beta regression mixture models were used to evaluate SF-6D utilities as a function of MAX-PC scores, race, education, marital status, income, employment status, having health insurance, year of cancer diagnosis and clinically significant prostate cancer-related anxiety (PCRA) status in the estimation dataset. Models' predictive accuracies (using mean absolute error [MAE], root mean squared error [RMSE], Akaike information criterion [AIC] and Bayesian information criterion [BIC]) were examined in both datasets. The model with the highest prediction accuracy and the lowest prediction errors was selected as the crosswalk.

RESULTS

The crosswalk had modest prediction accuracy (MAE = 0.092, RMSE = 0.114, AIC = - 2708 and BIC = - 2595.6), which are comparable to prediction accuracies of other SF-6D crosswalks in the literature. About 24% and 52% of predictions fell within ± 5% and ± 10% of observed SF-6D, respectively. The observed mean disutility associated with acquiring clinically significant PCRA is 0.168 (standard deviation = 0.179).

CONCLUSION

This study provides a crosswalk that converts MAX-PC scores to SF-6D utilities for economic evaluation of clinically significant PCRA treatment options for prostate cancer survivors.

An International Comparison of EQ-5D-5L and EQ-5D-3L for Use in Cost-Effectiveness Analysis

OBJECTIVES

To estimate the impact of using EQ5D-5L (5L) compared with EQ5D-3L (3L) in cost-effectiveness analyses in 6 countries with 3L and 5L values: Germany, Japan, Korea, The Netherlands, China, and Spain.

METHODS

Eight cost-effectiveness analyses based on clinical studies with 3L provided 11 pairwise comparisons. We estimated cost-effectiveness by applying the appropriate country values for 3L to observed responses. We re-estimated cost-effectiveness for each country by predicting the 5L tariff score for each respondent, for each country, using a previously published mapping method. We compared results in terms of impact on estimated incremental quality-adjusted life-year (QALY) gain and cost-effectiveness ratios.

RESULTS

For most countries the impact of moving from 3L to 5L is to lower the incremental QALY gain in the majority of comparisons. The only exception to this was Japan, where 4 out of 11 cases (37%) saw lower QALYs gained when using 5L. The mean and median reductions in health gain, in those case studies where 5L does lead to lower health gain, are largest in The Netherlands (84% mean reduction, 41% median reduction), Germany (68% and 27%), and Spain (30% and 31%). For most countries, those studies where 5L leads to lower health gain see larger reductions than the gains in studies showing the opposite tendency.

CONCLUSIONS

Overall, 3L and 5L are not interchangeable in these countries. Differences between results are large, but the direction of change can be unpredictable. These findings should prompt further investigation into the reasons for differences.

Cost-utility analysis of stereotactic body radiotherapy plus cetuximab in previously irradiated recurrent squamous cell carcinoma of the head and neck

BACKGROUND

This study aimed to estimate the cost-utility of stereotactic body radiotherapy (SBRT) plus cetuximab for patients with previously irradiated recurrent squamous cell carcinoma of the head and neck.

METHODS

We constructed a Markov health-state transition model to simulate costs and clinical outcomes of recurrent squamous cell carcinoma of the head and neck. Model parameters were derived from the published literature and the National Health Insurance Administration reimbursement price list. Incremental cost-effectiveness ratio and the net monetary benefit were calculated from a health payer perspective. The impact of uncertainty was modeled with one-way and probabilistic sensitivity analyses.

RESULTS

In the base-case, SBRT plus cetuximab compared to SBRT alone resulted in an ICER of NT$ 840,455 per QALY gained. In the one-way sensitivity analysis, the utility of progression-free state for patients treated with SBRT plus cetuximab or SBRT alone and the cost of progression-free survival for SBRT+Cet were the most sensitive parameters in the model. Probabilistic sensitivity analysis showed that the probability of cost-effectiveness at a willingness-to-pay threshold of NT$ 2,252,340 per QALY was 100% for SBRT plus cetuximab but 0% for SBRT alone.

CONCLUSIONS

This study showed that SBRT+Cet was cost-effective and benefited patients with previously irradiated rSCCHN.

Mapping MacNew Heart Disease Quality of Life Questionnaire onto country-specific EQ-5D-5L utility scores: a comparison of traditional regression models with a machine learning technique

BACKGROUND

This study aims to derive country-specific EQ-5D-5L health status utility (HSU) from the MacNew Heart Disease Health-related Quality of Life questionnaire (MacNew) using both traditional regression analyses, as well as a machine learning technique.

METHODS

Data were drawn from the Multi-Instrument Comparison (MIC) survey. The EQ-5D-5L was scored using 4 country-specific tariffs (United States, United Kingdom, Germany, and Canada). The traditional regression techniques, as well as a machine learning technique, deep neural network (DNN), were adopted to directly predict country-specific EQ-5D-5L HSUs (i.e. a direct mapping approach). An indirect response mapping was undertaken additionally. The optimal algorithm was identified based on three goodness-of-fit tests, namely, the mean absolute error (MAE), mean error (ME) and root mean square error (RMSE), with the first being the primary criteria. Internal validation was undertaken.

RESULTS

Indirect response mapping and direct mapping (via betamix with MacNew items as the key predictors) were found to produce the optimal mapping algorithms with the lowest MAE when EQ-5D-5L were scored using three country-specific tariffs (United Kingdom, Canada, and Germany for the former and United Kingdom, United States, Canada and Germany for the latter approach). DNN approach generated the lowest MAE and RMSE when using the Germany-specific tariff.

CONCLUSIONS

Among different approaches been explored, there is not a conclusive conclusion regarding the optimal method for developing mapping algorithms. A machine learning approach represents an alternative mapping approach that should be explored further. The reported algorithms from response mapping have the potential to be more widely used; however, the performance needs to be externally validated.

Application of a Mapping Function to Estimate Utilities for Ragweed Allergy Immunotherapy Trials

BACKGROUND

Ragweed pollen sensitivity is a common cause of allergic rhinitis (AR) worldwide. AR symptoms include itchy and runny eyes, sneezing, blocked nose, impaired sleep and social and emotional problems, which can have a significant impact on quality of life.

OBJECTIVE

The objective of this analysis was to estimate utilities for two pooled standardised quality (SQ) ragweed sublingual immunotherapy (SLIT) tablet trials by applying a previously developed mapping algorithm. This study validated the algorithm and extended its application to ragweed seasonal allergy trials. The mapping algorithm relates disease-specific quality-of-life scores to preference-based utilities that may be used to calculate quality-adjusted life-years (QALYs) in cost-effectiveness studies.

METHODS

A mapping algorithm based on a grass pollen allergy immunotherapy trial, GT-08 (EudraCT no. 2004-000083-27) was applied to pooled data from two ragweed pollen immunotherapy trials, P05233 (EudraCT 2008-003863-38) and P05234 (EudraCT 2008-003864-20) to generate EuroQoL 5-Dimensions, 3-Levels (EQ-5D-3L) utilities from Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) data.

RESULTS

The mean utility difference between the SQ ragweed SLIT tablet and placebo was 0.025 [95% confidence interval (CI) 0.011-0.038]. The SQ ragweed SLIT tablet showed an incremental quality-adjusted life-days (QALDs) benefit of 1.900 (95% CI 0.835-2.916) over 75 days.

CONCLUSIONS

Application of a previously developed mapping function allowed for the calculation of QALDs associated with the SQ ragweed SLIT tablet. The results showed a QALD benefit of the SQ ragweed SLIT tablet in P05233 and P05234 trials in the treatment of ragweed pollen-induced AR.

Mapping of the EORTC QLQ-C30 to EQ-5D-5L index in patients with lymphomas

OBJECTIVE

The objective of this study was to develop algorithms to map the EORTC QLQ-C30 (QLQ-C30) onto EQ-5D-5L in a sample of patients with lymphomas.

METHODS

An online nationwide survey of patients with lymphoma was carried out in China. Ordinary least squares (OLS), beta-based mixture, adjusted limited dependent variable mixture regression, and a Tobit regression model were used to develop the mapping algorithms. The QLQ-C30 subscales/items, their squared and interaction terms, and respondents' demographic variables were used as independent variables. The root mean square error (RMSE), mean absolute error (MAE), and R-squared (R²) were estimated based on tenfold cross-validation to assess the predictive ability of the selected models.

RESULTS

Data of 2222/4068 respondents who self-completed the online survey were elicited for analyses. The mean EQ-5D-5L index score was 0.81 (SD 0.21, range - 0.81-1.0). 19.98% of respondents reported an index score at 1.0. In total, 72 models were generated based on four regression methods. According to the RMSE, MAE and R², the OLS model including QLQ-C30 subscales, squared terms, interaction terms, and demographic variables showed the best fit for overall and the Non-Hodgkin's lymphoma sample; for Hodgkin's lymphoma, the ALDVMM with 1-component model, including QLQ-C30 subscales, squared terms, interaction terms, and demographic variables, showed a better fit than the other models.

CONCLUSION

The mapping algorithms enable the EQ-5D-5L index scores to be predicted by QLQ-C30 subscale/item scores with good precision in patients living with lymphomas.

Health-related quality of life and its associated factors in patients with type 2 diabetes mellitus

Background:

Assessing the health-related quality of life in patients with type 2 diabetes mellitus is important for evaluation of treatment outcome. The purpose of this study was to evaluate the health-related quality of life in type 2 diabetes mellitus patients and its related factors in Yazd.

Methods:

Data were gathered by using the EuroQoL-five-dimension-5 level instrument as well as using medical records of 734 outpatients with type 2 diabetes mellitus who were referred to the largest governmental diabetes center in South of Iran, Yazd province. When appropriate, the Kruskal–Wallis test or the Wilcoxon test was used to test the difference in the health-related quality-of-life scores in each factor. Finally, the adjusted limited dependent variable mixture model was developed to investigate factors associated with health-related quality-of-life scores.

Results:

The mean and median of the EuroQoL-five-dimension-5 level index values of 717 patients who completed the questionnaires were 0.75 ± 0.006 and 0.72 ± 0.20, respectively, and those of the Visual Analogue Scale scores were 69.25 ± 0.63 and 75 ± 30, respectively. The mean scores for health-related quality of life were significantly higher for employed, educated, single, and male patients, as well as patients without comorbidities, diabetes-related complications, and hemoglobin A1c level >7%. Adjusted limited dependent variable mixture model showed that gender, age, marital status, and diabetes-related complications are significant independent predictors of EuroQoL-five-dimension-5 level index value.

Conclusion:

The mean scores for health-related quality of life in patients with type 2 diabetes mellitus were moderate in this study, and this finding is consistent with health-related quality-of-life scores reported in other studies conducted in the Middle East region. Therefore, health-related quality of life should be the most important consideration in the management of patients. In parallel, some factors, especially gender, should be considered to improve health-related quality of life.

Mapping clinical outcomes to generic preference-based outcome measures: development and comparison of methods

BACKGROUND

Cost-effectiveness analysis using quality-adjusted life-years as the measure of health benefit is commonly used to aid decision-makers. Clinical studies often do not include preference-based measures that allow the calculation of quality-adjusted life-years, or the data are insufficient. 'Mapping' can bridge this evidence gap; it entails estimating the relationship between outcomes measured in clinical studies and the required preference-based measures using a different data set. However, many methods for mapping yield biased results, distorting cost-effectiveness estimates.

OBJECTIVES

Develop existing and new methods for mapping; test their performance in case studies spanning different preference-based measures; and develop methods for mapping between preference-based measures.

DATA SOURCES

Fifteen data sets for mapping from non-preference-based measures to preference-based measures for patients with head injury, breast cancer, asthma, heart disease, knee surgery and varicose veins were used. Four preference-based measures were covered: the EuroQoL-5 Dimensions, three-level version (n = 11), EuroQoL-5 Dimensions, five-level version (n = 2), Short Form questionnaire-6 Dimensions (n = 1) and Health Utility Index Mark 3 (n = 1). Sample sizes ranged from 852 to 136,327. For mapping between generic preference-based measures, data from FORWARD, the National Databank for Rheumatic Diseases (which includes the EuroQoL-5 Dimensions, three-level version, and EuroQoL-5 Dimensions, five-level version, in its 2011 wave), were used.

MAIN METHODS DEVELOPED

Mixture-model-based approaches for direct mapping, in which the dependent variable is the health utility value, including adaptations of methods developed to model the EuroQoL-5 Dimensions, three-level version, and beta regression mixtures, were developed, as were indirect methods, in which responses to the descriptive systems are modelled, for consistent multidirectional mapping between preference-based measures. A highly flexible approach was designed, using copulas to specify the bivariate distribution of each pair of EuroQoL-5 Dimensions, three-level version, and EuroQoL-5 Dimensions, five-level version, responses.

RESULTS

A range of criteria for assessing model performance is proposed. Theoretically, linear regression is inappropriate for mapping. Case studies confirm this. Flexible, direct mapping methods, based on different variants of mixture models with appropriate underlying distributions, perform very well for all preference-based measures. The precise form is important. Case studies show that a minimum of three components are required. Covariates representing disease severity are required as predictors of component membership. Beta-based mixtures perform similarly to the bespoke mixture approaches but necessitate detailed consideration of the number and location of probability masses. The flexible, bi-directional indirect approach performs well for testing differences between preference-based measures.

LIMITATIONS

Case studies drew heavily on EuroQoL-5 Dimensions. Indirect methods could not be undertaken for several case studies because of a lack of coverage. These methods will often be unfeasible for preference-based measures with complex descriptive systems.

CONCLUSIONS

Mapping requires appropriate methods to yield reliable results. Evidence shows that widely used methods such as linear regression are inappropriate. More flexible methods developed specifically for mapping show that close-fitting results can be achieved. Approaches based on mixture models are appropriate for all preference-based measures. Some features are universally required (such as the minimum number of components) but others must be assessed on a case-by-case basis (such as the location and number of probability mass points).

FUTURE RESEARCH PRIORITIES

Further research is recommended on (1) the use of the monotonicity concept, (2) the mismatch of trial and mapping distributions and measurement error and (3) the development of indirect methods drawing on methods developed for mapping between preference-based measures.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 34. See the NIHR Journals Library website for further project information. This project was also funded by a Medical Research Council grant (MR/L022575/1).

Mapping to Quality of Life and Capability Measures in Cataract Surgery Patients: From Cat-PROM5 to EQ-5D-3L, EQ-5D-5L, and ICECAP-O Using Mixture Modelling

Objectives. Cataract is a prevalent and potentially blinding eye condition. Cataract surgery, the only proven treatment for this condition, is a very frequently undertaken procedure. The objective of this analysis was to develop a mapping algorithm that could be used to predict quality of life and capability scores from the Cat-PROM5, a newly developed, validated patient-reported outcome measure for patients undergoing cataract surgery. Methods. We estimated linear models and adjusted limited dependent variable mixture models. Data were taken from the Predict-CAT cohort of up to 1181 patients undergoing cataract surgery at two sites in England. The Cat-PROM5 was mapped to two quality of life measures (EQ-5D-3L and EQ-5D-5L) and one capability measure (ICECAP-O). All patients reported ICECAP-O and one or other of the EQ-5D measures both before and after cataract surgery. Model performance was assessed using likelihood statistics, graphical inspections of model fit, and error measurements. Results. Adjusted limited dependent variable mixture models dominated linear models on all performance criteria. Mixture models offered very good fit. Three component models that allowed component membership to be a function of covariates (age, sex, and diabetic status depending on specification and outcome measure) and which conditioned on covariates offered the best performance in almost all cases. An exception was the EQ-5D-5L post-surgery for which a two-component model was selected. Conclusions. Mapping from Cat-PROM5 to quality of life and capability measures using adjusted limited dependent variable mixture models is feasible, and the estimates can be used to support cost-effectiveness analysis in relation to cataract care. Mixture models performed strongly for both quality of life outcomes and capability outcomes.

Mapping the kidney disease quality of life 36-item short form survey (KDQOL-36) to the EQ-5D-3L and the EQ-5D-5L in patients undergoing dialysis

OBJECTIVES

To develop algorithms mapping the Kidney Disease Quality of Life 36-Item Short Form Survey (KDQOL-36) onto the 3-level EQ-5D questionnaire (EQ-5D-3L) and the 5-level EQ-5D questionnaire (EQ-5D-5L) for patients with end-stage renal disease requiring dialysis.

METHODS

We used data from a cross-sectional study in Europe (France, n = 299; Germany, n = 413; Italy, n = 278; Spain, n = 225) to map onto EQ-5D-3L and data from a cross-sectional study in Singapore (n = 163) to map onto EQ-5D-5L. Direct mapping using linear regression, mixture beta regression and adjusted limited dependent variable mixture models (ALDVMMs) and response mapping using seemingly unrelated ordered probit models were performed. The KDQOL-36 subscale scores, i.e., physical component summary (PCS), mental component summary (MCS), three disease-specific subscales or their average, i.e., kidney disease component summary (KDCS), and age and sex were included as the explanatory variables. Predictive performance was assessed by mean absolute error (MAE) and root mean square error (RMSE) using 10-fold cross-validation.

RESULTS

Mixture models outperformed linear regression and response mapping. When mapping to EQ-5D-3L, the ALDVMM model was the best-performing one for France, Germany and Spain while beta regression was best for Italy. When mapping to EQ-5D-5L, the ALDVMM model also demonstrated the best predictive performance. Generally, models using KDQOL-36 subscale scores showed better fit than using the KDCS.

CONCLUSIONS

This study adds to the growing literature suggesting the better performance of the mixture models in modelling EQ-5D and produces algorithms to map the KDQOL-36 onto EQ-5D-3L (for France, Germany, Italy, and Spain) and EQ-5D-5L (for Singapore).

Mapping EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS)

Purpose

To develop a mapping model to estimate EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS).

Methods

The responses to EQ-5D-3L and KOOS questionnaires (n = 40,459 observations) were obtained from the Swedish National anterior cruciate ligament (ACL) Register for patients ≥ 18 years with the knee ACL injury. We used linear regression (LR) and beta-mixture (BM) for direct mapping and the generalized ordered probit model for response mapping (RM). We compared the distribution of the original data to the distributions of the data generated using the estimated models.

Results

Models with individual KOOS subscales performed better than those with the average of KOOS subscale scores (KOOS₅, KOOS₄). LR had the poorest performance overall and across the range of disease severity particularly at the extremes of the distribution of severity. Compared with the RM, the BM performed better across the entire range of disease severity except the most severe range (KOOS₅ < 25). Moving from the most to the least disease severity was associated with 0.785 gain in the observed EQ-5D-3L. The corresponding value was 0.743, 0.772 and 0.782 for LR, BM and RM, respectively. LR generated simulated EQ-5D-3L values outside the feasible range. The distribution of simulated data generated from the BM model was almost identical to the original data.

Conclusions

We developed mapping models to estimate EQ-5D-3L from KOOS facilitating application of KOOS in cost-utility analyses. The BM showed superior performance for estimating EQ-5D-3L from KOOS. Further validation of the estimated models in different independent samples is warranted.

Electronic supplementary material

The online version of this article (10.1007/s11136-019-02303-9) contains supplementary material, which is available to authorized users.

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 Strengths and Difficulties Questionnaire onto the Child Health Utility 9D in a large study of children

PURPOSE

Non-preference-based measures cannot be used to directly obtain utilities but can be converted to preference-based measures through mapping. The only mapping algorithm for estimating Child Health Utility-9D (CHU9D) utilities from Strengths and Difficulties Questionnaire (SDQ) responses has limitations. This study aimed to develop a more accurate algorithm.

METHODS

We used a large sample of children (n = 6898), with negligible missing data, from the Longitudinal Study of Australian Children. Exploratory factor analysis (EFA) and Spearman's rank correlation coefficients were used to assess conceptual overlap between SDQ and CHU9D. Direct mapping (involving seven regression methods) and response mapping (involving one regression method) approaches were considered. The final model was selected by ranking the performance of each method by averaging the following across tenfold cross-validation iterations: mean absolute error (MAE), mean squared error (MSE), and MAE and MSE for two subsamples where predicted utility values were < 0.50 (poor health) or > 0.90 (healthy). External validation was conducted using data from the Child and Adolescent Mental Health Services study.

RESULTS

SDQ and CHU9D were moderately correlated (ρ = - 0.52, p < 0.001). EFA demonstrated that all CHU9D domains were associated with four SDQ subscales. The best-performing model was the Generalized Linear Model with SDQ items and gender as predictors (full sample MAE: 0.1149; MSE: 0.0227). The new algorithm performed well in the external validation.

CONCLUSIONS

The proposed mapping algorithm can produce robust estimates of CHU9D utilities from SDQ data for economic evaluations. Further research is warranted to assess the applicability of the algorithm among children with severe health problems.

Mapping the Functional Independence Measure to a multi-attribute utility instrument for economic evaluations in rehabilitation: a secondary analysis of randomized controlled trial data

Purpose: To test whether the Functional Independence Measure (FIM) could be mapped to the EQ-5D-3L to give researchers a viable but "second-best" option for calculating quality-adjusted life-years (QALYs) and conducting a cost-utility analysis when only clinical outcomes have been collected.Materials and methods: Secondary analysis of repeated measures data collected during a randomized controlled trial (n = 3506 observations) at two inpatient rehabilitation centres. Participants had a mean age of 74 (SD 13) years, 63% were women and 58% were admitted with an orthopaedic diagnosis. Ordinary least-squares regression and adjusted limited dependent variable mixture models were used to estimate regression-based mappings. Performance was evaluated based on mean absolute error and the proportion of errors in excess of the minimally important difference.Results: In orthopaedic and neurological patients, high mean absolute errors (0.2 on the quality-adjusted life years scale) and a high proportion of errors (60%) in excess of the minimally important difference suggest that predicted EQ-5D-3L values provided a poor substitute for observed EQ-5D-3L values.Conclusions: Regression-based mappings from the FIM to the EQ-5D-3L are error-prone and unsuitable for calculating QALYs in rehabilitation patients. Researchers and rehabilitation professionals should therefore include a multi-attribute utility instrument such as the EQ-5D as well as the FIM to evaluate the effect of rehabilitation interventions and in rehabilitation registries. This will provide additional information on health-related quality of life and support cost-utility analyses.Implications for rehabilitationThe Functional Independence Measure (FIM) cannot be used to calculate quality-adjusted life-years (QALYs) for cost-utility analyses.Predicting QALYs from FIM data is a poor substitute for direct measurement of QALYs in orthopaedic or neurological rehabilitation populations.Multi-attribute utility instruments (MAUIs) allow direct measurement of QALYs, as well as providing a patient-reported measure of clinical quality and outcomes in rehabilitation.A MAUI should be included routinely in clinical practice by rehabilitation professionals as well as in rehabilitation trials and registries to track patient outcomes and improve clinical practice.

Mapping the FACT-B Instrument to EQ-5D-3L in Patients with Breast Cancer Using Adjusted Limited Dependent Variable Mixture Models versus Response Mapping

BACKGROUND

Preference-based measures of health, such as the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L), are required to calculate quality-adjusted life-years for use in cost-effectiveness analysis, but are often not recorded in clinical studies. In these cases, mapping can be used to estimate preference-based measures.

OBJECTIVES

To model the relationship between the EQ-5D-3L and the Functional Assessment of Cancer Therapy-Breast Cancer (FACT-B) instrument, comparing indirect and direct mapping methods, and the use of FACT-B summary score versus FACT-B subscale scores.

METHODS

We used data from three clinical studies for advanced breast cancer providing 11,958 observations with full information on FACT-B and the EQ-5D-3L. We compared direct mapping using adjusted limited dependent variable mixture models (ALDVMMs) with indirect mapping using seemingly unrelated ordered probit models. The EQ-5D-3L was estimated as a function of FACT-B and other patient-related covariates.

RESULTS

The use of FACT-B subscale scores was better than using the total FACT-B score. A good fit to the observed data was observed across the entire range of disease severity in all models. ALDVMMs outperformed the indirect mapping. The breast cancer-specific scale had a strong influence in predicting the pain/discomfort and self-care dimensions of the EQ-5D-3L.

CONCLUSIONS

This article adds to the growing literature that demonstrates the performance of the ALDVMM method for mapping. Regardless of which model is used, the subscales of FACT-B should be included as independent variables wherever possible. The breast cancer-specific subscale of FACT-B is important in predicting the EQ-5D-3L. This suggests that generic cancer measures should not be used for utility mapping in patients with breast cancer.