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

Derivation and Initial Validation of the Utility Function for the Hearing Utility Measure (HUM)

OBJECTIVE

The Hearing Utility Measure (HUM) is a replacement hearing attribute for the Health Utilities Index, Mark 3 (HUI-3) designed to improve the responsiveness of utility estimates to changes in hearing-related quality of life. The final development step is to derive the instrument's utility scoring function.

METHODS

Residents of Ontario, Canada, aged ≥18 years participated in standard gamble and visual analogue scale exercises. Valuations for levels (response options) within each domain, and for each domain relative to the other domains were elicited and used to generate a hearing utility function. The function outputs hearing utility ranging from 0 = 'unable to hear at all' to 1 = 'perfect hearing' for each of the 25,920 hearing states classifiable by the HUM. Performance was assessed relative to the criterion standard: directly elicited standard gamble utility. Distributions of HUM-derived hearing utility were compared with legacy HUI-3 derived estimates.

RESULTS

A total of 126 respondents participated (mean age 39.2, range 18-85 years, 53% female [67/126]). The utility function performed well in the estimation of directly elicited utilities (mean difference 0.03, RMSE 0.06). Using the legacy HUI-3, estimated hearing utility was 1.0 for 118/126 respondents (93.6%) compared with just 66/126 (52.4%) using the HUM.

CONCLUSION

The new hearing attribute is capable of measuring variations in hearing utility not captured by the legacy HUI-3, especially near the ceiling of hearing function. These findings justify its application and further work to study its measurement properties in hearing loss populations.

LEVEL OF EVIDENCE

3 Laryngoscope, 134:4754-4762, 2024.

Valuing quality of life for economic evaluations in cancer: navigating multiple methods

INTRODUCTION

Utility values offer a quantitative means to evaluate the impact of novel cancer treatments on patients' quality of life (QoL). However, the multiple methods available for valuing QoL present challenges in selecting the most appropriate method across different contexts.

AREAS COVERED

This review provides cancer clinicians and researchers with an overview of methods to value QoL for economic evaluations, including standalone and derived preference-based measures (PBMs) and direct preference elicitation methods. Recent developments are described, including the comparative performance of cancer-specific PBMs versus generic PBMs, measurement of outcomes beyond health-related QoL, and increased use of discrete choice experiments to elicit preferences. Recommendations and considerations are provided to guide the choice of method for cancer research.

EXPERT OPINION

We foresee continued adoption of the QLU-C10D and FACT-8D in cancer clinical trials given the extensive use of the EORTC QLQ-C30 and FACT-G in cancer research. While these cancer-specific PBMs offer the convenience of eliciting utility values without needing a standalone PBM, researchers should consider potential limitations if they intend to substitute them for generic PBMs. As the field advances, there is a greater need for consensus on the approach to selection and integration of various methods in cancer clinical trials.

Comparison of the EQ-5D-5L and the patient-reported outcomes measurement information system preference score (PROPr) in the United States

BACKGROUND

In contrast to prior research, our study presents longitudinal comparisons of the EQ-5D-5L and Patient-Reported Outcomes Measurement Information System (PROMIS) preference (PROPr) scores. This fills a gap in the literature, providing a much-needed understanding of these preference-based measures and their applications in healthcare research. Furthermore, our study provides equations to estimate one measure from the other, a tool that can significantly facilitate comparisons across studies.

METHODS

We administered a health survey to 4,098 KnowledgePanel® members living in the United States. A subset of 1,256 (82% response rate) with back pain also completed the six-month follow-up survey. We then conducted thorough cross-sectional and longitudinal analyses of the two measures, including product-moment correlations between scores, associations with demographic variables, and health conditions. To estimate one measure from the other, we used ordinary least squares (OLS) regression with the baseline data from the general population.

RESULTS

The correlation between the EQ-5D-5L and PROPr scores was 0.69, but the intraclass correlation was only 0.34 because the PROPr had lower (less positive) mean scores on the 0 (dead) to 1 (perfect health) continuum than the EQ-5D-5L. The associations between the two preference measures and demographic variables were similar at baseline. The product-moment correlation between unstandardized beta coefficients for each preference measure regressed on 22 health conditions was 0.86, reflecting similar patterns of unique associations. Correlations of change from baseline to 6 months in the two measures with retrospective perceptions of change were similar. Adjusted variance explained in OLS regressions predicting one measure from the other was 48%. On average, the predicted values were within a half-standard deviation of the observed EQ-5D-5L and PROPr scores. The beta-binomial regression model slightly improved over the OLS model in predicting the EQ-5D-5L from the PROPr but was equivalent to the OLS model in predicting the PROPr.

CONCLUSION

Despite substantial mean differences, the EQ-5D-5L and PROPr have similar cross-sectional and longitudinal associations with other variables. We provide the OLS regression equations for use in cost-effectiveness research and meta-analyses. Future studies are needed to compare these measures with different conditions and interventions to provide more information on their relative validity.

Development of algorithms for estimating the Child Health Utility 9D from Caregiver Priorities and Child Health Index of Life with Disability

PURPOSE

The primary aim was to determine Child Health Utility 9D (CHU9D) utilities from the Caregiver Priorities and Child Health Index of Life with Disabilities (CPCHILD) for non-ambulatory children with cerebral palsy (CP).

METHODS

One hundred and eight surveys completed by Australian parents/caregivers of children with CP were analysed. Spearman's coefficients were used to investigate the correlations between the two instruments. Ordinary least square, robust MM-estimator, and generalised linear models (GLM) with four combinations of families and links were developed to estimate CHU9D utilities from either the CPCHILD total score or CPCHILD domains scores. Internal validation was performed using 5-fold cross-validation and random sampling validation. The best performing algorithms were identified based on mean absolute error (MAE), concordance correlation coefficient (CCC), and the difference between predicted and observed means of CHU9D.

RESULTS

Moderate correlations (ρ 0.4-0.6) were observed between domains of the CHU9D and CPCHILD instruments. The best performing algorithm when considering the CPCHILD total score was a generalised linear regression (GLM) Gamma family and logit link (MAE = 0.156, CCC = 0.508). Additionally, the GLM Gamma family logit link using CPCHILD comfort and emotion, quality of life, and health domain scores also performed well (MAE = 0.152, CCC = 0.552).

CONCLUSION

This study established algorithms for estimating CHU9D utilities from CPCHILD scores for non-ambulatory children with CP. The determined algorithms can be valuable for estimating quality-adjusted life years for cost-utility analysis when only the CPCHILD instrument is available. However, further studies with larger sample sizes and external validation are recommended to validate these findings.

Mapping from SIBDQ to EQ-5D-5L for patients with inflammatory bowel disease

OBJECTIVE

Clinical studies commonly use disease-specific measures to assess patients' health-related quality of life. However, economic evaluation often requires preference-based utility index scores to calculate cost per quality-adjusted life-year (QALY). When utility index scores are not directly available, mappings are useful. To our knowledge, no mapping exists for the Short Inflammatory Bowel Disease Questionnaire (SIBDQ). Our aim was to develop a mapping from SIBDQ to the EQ-5D-5L index score with German weights for inflammatory bowel disease (IBD) patients.

METHODS

We used 3856 observations of 1055 IBD patients who participated in a randomised controlled trial in Germany on the effect of introducing regular appointments with an IBD nurse specialist in addition to standard care with biologics. We considered five data availability scenarios. For each scenario, we estimated different regression and machine learning models: linear mixed-effects regression, mixed-effects Tobit regression, an adjusted limited dependent variable mixture model and a mixed-effects regression forest. We selected the final models with tenfold cross-validation based on a model subset and validated these with observations in a validation subset.

RESULTS

For the first four data availability scenarios, we selected mixed-effects Tobit regressions as final models. For the fifth scenario, mixed-effects regression forest performed best. Our findings suggest that the demographic variables age and gender do not improve the mapping, while including SIBDQ subscales, IBD disease type, BMI and smoking status leads to better predictions.

CONCLUSION

We developed an algorithm mapping SIBDQ values to EQ-5D-5L index scores for different sets of covariates in IBD patients. It is implemented in the following web application: https://www.bwl.uni-hamburg.de/hcm/forschung/mapping.html .

A Comparison of Items and Constructs of Standardized Health-Related Quality of Life and Mental Well-Being Measures

OBJECTIVES

This study aimed to explore the internal constructs of the concepts being measured by EQ-5D-5L (a health-related quality of life measure that can produce preference-based utility values) and the 12-item General Health Questionnaire (GHQ-12, a mental well-being measure) and to understand to what extent the items of EQ-5D-5L and GHQ-12 associate with each other.

METHODS

We used data from 12 701 respondents participating in a Belgian survey in 2022. Correlation coefficients between GHQ-12 and EQ-5D-5L were calculated at both the aggregate and item levels. Multidimensional scaling, exploratory factor analysis, and regression models were performed to investigate the underlying constructs that are associated with the items.

RESULTS

Despite a moderate correlation (0.39) between the EQ-5D-5L and GHQ-12 total scores, only a trivial or weak correlation (<0.3) was observed between the first 4 EQ-5D-5L items and any GHQ-12 item. Multidimensional scaling and exploratory factor analysis showed the first 4 EQ-5D-5L dimensions were clustered together with EuroQol visual analog scale and positively phrased GHQ-12 items were close to each other, whereas EQ-anxiety/depression and negatively phrased GHQ-12 items were grouped with overall life satisfaction. In the regression models, not all GHQ-12 items had a significant coefficient to predict EQ-5D-5L responses.

CONCLUSIONS

To the best of our knowledge, we present the first comparison of items and underlying constructs of GHQ-12 and EQ-5D-5L. The results showed that GHQ-12 can only partially predict the responses of EQ-5D-5L and the 2 instruments measure different constructs. Researchers should carefully consider conceptual legitimacy while applying the mapping technique and consider sensitivity analyses for the mapping estimates.

Generating EQ-5D-3L health utility scores from the Edinburgh Postnatal Depression Scale: a perinatal mapping study

BACKGROUND

Perinatal depression (PND) describes depression experienced by parents during pregnancy or in the first year after a baby is born. The EQ-5D instrument (a generic measure of health status) is not often collected in perinatal research, however disease-specific measures, such as the Edinburgh Postnatal Depression Scale (EPDS) are widely used. Mapping can be used to estimate generic health utility index values from disease-specific measures like the EPDS.

OBJECTIVE

To develop a mapping algorithm to estimate EQ-5D utility index values from the EPDS.

METHODS

Patient-level data from the BaBY PaNDA study (English observational cohort study) provided 1068 observations with paired EPDS and EQ-5D (3-level version; EQ-5D-3L) responses. We compared the performance of six alternative regression model types, each with four specifications of covariates (EPDS score and age: base, squared, and cubed). Model performance (ability to predict utility values) was assessed by ranking mean error, mean absolute error, and root mean square error. Algorithm performance in 3 external datasets was also evaluated.

RESULTS

There was moderate correlation between EPDS score and utility values (coefficient:  - 0.42). The best performing model type was a two-part model, followed by ordinary least squared. Inclusion of squared and cubed covariates improved model performance. Based on graphs of observed and predicted utility values, the algorithm performed better when utility was above 0.6.

CONCLUSIONS

This direct mapping algorithm allows the estimation of health utility values from EPDS scores. The algorithm has good external validity but is likely to perform better in samples with higher health status.

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.

Mapping of the PROMIS global health measure to the PROPr in the United States

BACKGROUND

The Patient-Reported Outcomes Measurement and Information System (PROMIS®) global health items (global-10) yield physical and mental health scale scores and the PROMIS-Preference (PROPr) scoring system estimated from PROMIS domain scores (e.g., PROMIS-29 + 2) produces a single score anchored by 0 (dead or as bad as being dead) to 1 (full health). A link between the PROMIS global-10 and the PROPr is needed.

METHODS

The PROMIS-29 + 2 and the PROMIS global-10 were administered to 4102 adults in the Ipsos KnowledgePanel in 2022. The median age was 52 (range 18-94), 50% were female, 70% were non-Hispanic White, and 64% were married or living with a partner. The highest level of education completed for 26% of the sample was a high school degree or general education diploma and 44% worked full-time. We estimated correlations of the PROPr with the PROMIS global health items and the global physical and mental health scales. We examined the adjusted R2 and estimated correlations between predicted and observed PROPr scores.

RESULTS

Product-moment correlations between the PROMIS global health items and the PROPr ranged from 0.50 to 0.63. The PROMIS global physical health and mental health scale scores correlated 0.74 and 0.60, respectively, with the PROPr. The adjusted R2 in the regression of the PROPr on the PROMIS global health items was 64%. The equated PROPr preference scores correlated (product-moment) 0.80 (n = 4043; p < 0.0001) with the observed PROPr preference scores, and the intra-class correlation (two-way random effects model) was 0.80. The normalized mean absolute error (NMAE) was 0.45 (SD = 0.43). The adjusted R2 in the OLS regression of the PROPr on the PROMIS global health scales was 59%. The equated PROPr preference scores correlated (product-moment) was 0.77 (n = 4046; p < 0.0001) with the observed PROPr preference scores, and the intra-class correlation was 0.77. The NMAE was 0.49 (SD = 0.45).

CONCLUSIONS

Regression equations provide a reasonably accurate estimate of the PROPr preference-based score from the PROMIS global health items or scales for group-level comparisons. These estimates facilitate cost-effectiveness research and meta-analyses. The estimated PROPr scores are not accurate enough for individual-level applications. Future evaluations of the prediction equations are needed.

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.

Mapping the World Health Organization Disability Assessment Schedule (WHODAS 2.0) onto SF-6D Using Swedish General Population Data

BACKGROUND AND OBJECTIVE

Mapping algorithms can be used for estimating quality-adjusted life years (QALYs) when studies apply non-preference-based instruments. In this study, we estimate a regression-based algorithm for mapping between the World Health Organization Disability Assessment Schedule (WHODAS 2.0) and the preference-based instrument SF-6D to obtain preference estimates usable in health economic evaluations. This was done separately for the working and non-working populations, as WHODAS 2.0 discriminates between these groups when estimating scores.

METHODS

Using a dataset including 2258 participants from the general Swedish population, we estimated the statistical relationship between SF-6D and WHODAS 2.0. We applied three regression methods, i.e., ordinary least squares (OLS), generalized linear models (GLM), and Tobit, in mapping onto SF-6D from WHODAS 2.0 at the overall-score and domain levels. Root mean squared error (RMSE) and mean absolute error (MAE) were used for validation of the models; R2 was used to assess model fit.

RESULTS

The best-performing models for both the working and non-working populations were GLM models with RMSE ranging from 0.084 to 0.088, MAE ranging from 0.068 to 0.071, and R2 ranging from 0.503 to 0.608. When mapping from the WHODAS 2.0 overall score, the preferred model also included sex for both the working and non-working populations. When mapping from the WHODAS 2.0 domain level, the preferred model for the working population included the domains mobility, household activities, work/study activities, and sex. For the non-working population, the domain-level model included the domains mobility, household activities, participation, and education.

CONCLUSIONS

It is possible to apply the derived mapping algorithms for health economic evaluations in studies using WHODAS 2.0. As conceptual overlap is incomplete, we recommend using the domain-based algorithms over the overall score. Different algorithms must be applied depending on whether the population is working or non-working, due to the characteristics of WHODAS 2.0.

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.

More smoke and mirrors: Fifteen further reasons to doubt the effectiveness of headspace

OBJECTIVE

Commentary on the debate concerning the effectiveness of headspace, including the most recent independent evaluation of its services.

CONCLUSIONS

The available evaluations indicate that headspace does not deliver therapy of adequate duration that results in clinically significant improvement. Most evaluations have used either short-term process measures or uncontrolled satisfaction surveys, and where there have been data on outcomes using standardised instruments, findings have been disappointing. Costs are poorly quantified and probably underestimated. Even so, headspace as a primary care intervention costs twice as much as a mental health consultation by a general practitioner and, depending on the assumptions, may not be cost effective.

Mapping Oswestry Disability Index Responses to EQ-5D-3L Utility Values: Are Cost-Utility Results Valid?

OBJECTIVES

To develop and validate approaches for mapping Oswestry Disability Index responses to 3-level version of EQ-5D utility values and to evaluate the impact of using mapped utility values on cost-utility results compared with published regression models.

METHODS

Three response mapping approaches were developed in a random sample of 70% of 18 692 patients with low back pain: nonparametric approach (Non-p), nonparametric approach excluding logical inconsistencies (Non-peLI), and ordinal logistic regression (OLR). Performance was assessed in the remaining 30% using R-square (R²), root mean square error (RMSE), and mean absolute error (MAE). To evaluate whether MAEs and their 95% limits of agreement (LA) were clinically relevant, a minimally clinically important difference of 0.074 was used. Probabilities of cost-effectiveness estimated using observed and mapped utility values were compared in 2 economic evaluations.

RESULTS

The Non-p performed the best (R² = 0.43; RMSE = 0.22; MAE = 0.03; 95% LA = -0.40 to 0.47) compared with the Non-peLI (R² = 0.07; RMSE = 0.29; MAE = -0.15; 95% LA = -0.63 to 0.34) and OLR (R² = 0.22; RMSE = 0.26; MAE = 0.02; 95% LA = -0.49 to 0.53). MAEs were lower than the minimally clinically important difference for the Non-p and OLR but not for the Non-peLI. Differences in probabilities of cost-effectiveness ranged from 1% to 4% (Non-p), 0.1% to 9% (Non-peLI), and 0.1% to 20% (OLR).

CONCLUSIONS

Results suggest that the developed response mapping approaches are not valid for estimating individual patients' 3-level version of EQ-5D utility values, and-depending on the approach-may considerably affect cost-utility results. The developed approaches did not perform better than previously published regression-based models and are therefore not recommended for use in economic evaluations.

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.

The Cost-Effectiveness of a Dance and Yoga Intervention for Girls with Functional Abdominal Pain Disorders

BACKGROUND

Functional abdominal pain disorders (FAPDs) affect children worldwide, being more prevalent among girls. The individual and societal burdens of the disease are substantial, and evidence-based interventions are needed. Non-pharmacological treatments have generally produced promising results, with dance and yoga specifically having potential as an effective treatment option. Beside efficacy, the cost-effectiveness of interventions is important when prioritizing and allocating public resources.

OBJECTIVE

This study evaluated the cost-effectiveness of an 8-month dance and yoga intervention for girls with functional abdominal pain or irritable bowel syndrome, based on a randomized control trial called 'Just in TIME'.

METHODS

The intervention, performed in Sweden, was studied using a decision analysis tool, i.e., a decision tree within the trial followed by a Markov model with a time horizon of 10 years. The base case considered healthcare costs as well as productivity losses, measuring the effects in gained quality-adjusted life-years (QALYs) and presenting an incremental cost-effectiveness ratio (ICER).

RESULTS

The base case results show that the intervention, compared with current practice, was the dominant strategy from both the 12-month and long-term perspectives. The sensitivity analyses indicated that the long-term, but not the short-term, findings were robust for different assumptions and changes in parameter estimates, resulting in ICERs similar to those of the base case scenario.

CONCLUSIONS

Offering dance and yoga to young girls with FAPDs generates small QALY gains and monetary savings compared with standard healthcare and is likely cost-effective. These findings make a valuable contribution to an area where evidence-based and cost-effective treatment interventions are needed.

CLINICAL TRIALS REGISTRATION NUMBER

ClinicalTrials.gov identifier: NCT02920268; Name: Just in TIME-Intervention With Dance and Yoga for Girls With Recurrent Abdominal Pain.

Mapping the obesity problems scale to the SF-6D: results based on the Scandinavian Obesity Surgery Registry (SOReg)

BACKGROUND

Obesity Problem Scale (OP) is a widely applied instrument for obesity, however currently calculation of health utility based on OP is not feasible as it is not a preference-based measure. Using data from the Scandinavian Obesity Surgery Registry (SOReg), we sought to develop a mapping algorithm to estimate SF-6D utility from OP. Furthermore, to test whether the mapping algorithm is robust to the effect of surgery.

METHOD

The source data SOReg (n = 36 706) contains both OP and SF-36, collected at pre-surgery and at 1, 2 and 5 years post-surgery. The Ordinary Least Square (OLS), beta-regression and Tobit regression were used to predict the SF-6D utility for different time points respectively. Besides the main effect model, different combinations of patient characteristics (age, sex, Body Mass Index, obesity-related comorbidities) were tested. Both internal validation (split-sample validation) and validation with testing the mapping algorithm on a dataset from other time points were carried out. A multi-stage model selection process was used, accessing model consistency, parsimony, goodness-of-fit and predictive accuracy. Models with the best performance were selected as the final mapping algorithms.

RESULTS

The final mapping algorithms were based on OP summary score using OLS models, for pre- and post-surgery respectively. Mapping algorithms with different combinations of patients' characteristics were presented, to satisfy the user with a different need.

CONCLUSION

This study makes available algorithms enabling crosswalk from the Obesity Problem Scale to the SF-6D utility. Different mapping algorithms are recommended for the mapping of pre- and post-operative data.

Mapping study of papillary thyroid carcinoma in China: Predicting EQ-5D-5L utility values from FACT-H&N

Objective

To develop a mapping algorithm that can be used to predict EQ-5D-5L health utility scores from FACT-H&N and obtain health utility parameters for Chinese patients with papillary thyroid carcinoma (PTC), which can be used for cost-utility analysis in health economic.

Methods

A total of 1,050 patients with PTC from a tertiary hospital in China were included, and they completed FACT-H&N and EQ-5D-5L. Four mapping algorithms of direct mapping functions were used to derive the models: Ordinary least squares (OLS), Tobit model (Tobit), Two-part model (TPM), and Beta mixture regression model (Beta). The goodness-of-fit of models was assessed by the mean absolute error (MAE), root mean square error (RMSE), Akaike information criteria (AIC), Bayesian information criteria (BIC), and absolute error (AE). A fivefold cross-validation method was used to test the stability of the models.

Results

The mean utility value of the EQ-5D-5L was 0.870 ± 0.094. The mean EQ-VAS score was 76.5 ± 13.0. The Beta mixture regression model mapping FACT-H&N to EQ-5D-5L achieved the best performance [fivefold cross-validation MAE = 0.04612, RMSE = 0.06829, AIC = -2480.538, BIC = -2381.137, AE > 0.05 (%) = 32.48, AE > 0.1 (%) = 8.95]. The independent variables in this model were Physical Well-Being (PWB), Emotional Well-Being (EWB), Head & Neck Cancer Subscale (HNCS) scores and its square term and interaction term scores.

Conclusions

This study calculated the health utility score of Chinese patients with PTC. The reported algorithms can be used to map the FACT-H&N into the EQ-5D-5L, which can be applied in the cost-utility related study of patients with PTC.

Mapping PedsQL™ scores to CHU9D utility weights for children with chronic conditions in a multi-ethnic and deprived metropolitan population

PURPOSE

The Child Health Utility-9 Dimensions (CHU9D) is a patient-reported outcome measure to generate Quality-Adjusted Life Years (QALYs), recommended for economic evaluations of interventions to inform funding decisions. When the CHU9D is not available, mapping algorithms offer an opportunity to convert other paediatric instruments, such as the Paediatric Quality of Life Inventory™ (PedsQL), onto the CHU9D scores. This study aims to validate current PedsQL to CHU9D mappings in a sample of children and young people of a wide age range (0 to 16 years of age) and with chronic conditions. New algorithms with improved predictive accuracy are also developed.

METHODS

Data from the Children and Young People's Health Partnership (CYPHP) were used (N = 1735). Four regression models were estimated: ordinal least squared, generalized linear model, beta-binomial and censored least absolute deviations. Standard goodness of fit measures were used for validation and to assess new algorithms.

RESULTS

While previous algorithms perform well, performance can be enhanced. OLS was the best estimation method for the final equations at the total, dimension and item PedsQL scores levels. The CYPHP mapping algorithms include age as an important predictor and more non-linear terms compared with previous work.

CONCLUSION

The new CYPHP mappings are particularly relevant for samples with children and young people with chronic conditions living in deprived and urban settings. Further validation in an external sample is required. Trial registration number NCT03461848; pre-results.

Mapping the EQ-5D-5L from the Spanish national health survey functional disability scale through Bayesian networks

PURPOSE

Preference-based measures are valuable tools for evaluating therapeutic interventions and for cost-effectiveness studies. Mapping procedures are useful when it is not possible to collect these kind of measures. The objective of this study was to evaluate which mapping method is the most appropriate to estimate the EQ-5D-5L index from the Spanish National Health Survey functional disability scale.

METHODS

The sample, formed by 5708 older adults (aged 65 years or older), was drawn from the Spanish National Health Survey ("Encuesta Nacional de Salud en España," ENSE in Spanish 2011-2012). The predictions of EQ-5D-5L index were performed with response mapping using Bayesian network (BN), ordered logit (Ologit), and multinomial logistic (ML). The following direct methods were used: ordinary least squares (OLS) and Tobit regression. The intraclass correlation coefficient (ICC), absolute error (MAE), mean squared error (MSE), and root-mean squared error (RMSE) were calculated to compare all models. The predictions of response models were obtained through the expected value method.

RESULTS

BN model showed the highest ICC (0.756, 95% confidence interval, CI 0.733-0.777) and lowest MAE (0.110, 95% CI 0.104-0.115). OLS was the model with worse accuracy results with lowest ICC (0.621, 95% CI 0.553-0.681) and highest MAE (0.159, 95%CI: 0.145-0.173).

CONCLUSION

Indirect mapping methods (BN, Ologit, and ML) had a better accuracy than the direct methods. The response mapping approach provides a robust method to estimate EQ-5D-5L scores from the functional disability scale.

Obtaining EQ-5D-3L utility index from the health status scale of traditional Chinese medicine (TCM-HSS) based on a mapping study

BACKGROUND

Almost all traditional Chinese medicine (TCM) quality of life measures are non-preference-based measures (non-PBMs), which do not provide utilities for cost-utility analysis in pharmacoeconomic evaluation. Whereas the mapping has become a new instrument to obtain utilities, which builds a bridge between non-PBMs and PBMs.

PURPOSE

To develop mapping algorithms from the health status scale of traditional Chinese medicine (TCM-HSS) onto the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L).

METHODS

The cross-sectional data were collected by questionnaire survey from a tertiary hospital visit population and community residents in China, and randomly divided into training and validation set by 2:1. Based on the training set, direct and indirect mapping methods (7 regression methods and 4 model specifications) were conducted to establish alternative models, which were comprehensively evaluated based on the validation set by mean absolute error, root mean square error, and Spearman correlation coefficient between predicted and observed values. Based on the whole sample, the preferred mapping algorithm was developed.

RESULTS

A total of 639 samples were included, with an average age of 45.24 years and 61.66% of respondents were female. The mean EQ-5D-3L index was 0.9225 [SD = 0.1458], and the mean TCM-HSS index was 3.4144 [SD = 3.1154]. The final mapping algorithm was a two-part regression model including the TCM-HSS subscales, interaction terms, and demographic covariates (age and gender). The prediction performance was good. The mean error was 0.0003, the mean absolute error was 0.0566, the root mean square error was 0.1039, and 83.10% of the prediction errors were within 0.1; the Spearman correlation coefficient between predicted and observed EQ-5D-3L values was 0.6479.

CONCLUSION

It is the first study to develop a mapping algorithm between the TCM-HSS and EQ-5D-3L, which demonstrates excellent prediction accuracy and estimates utility value for economic evaluation from TCM quality of life measures.

Development of a mapping function ("crosswalk") for the conversion of scores between the Oswestry Disability Index (ODI) and the Core Outcome Measures Index (COMI)

INTRODUCTION

The Oswestry Disability Index (ODI) and the Core Outcome Measures Index (COMI) are two commonly used self-rating outcome instruments in patients with lumbar spinal disorders. No formal crosswalk between them exists that would otherwise allow the scores of one to be interpreted in terms of the other. We aimed to create such a mapping function.

METHODS

We performed a secondary analysis of ODI and COMI data previously collected from 3324 patients (57 ± 17y; 60.3% female) at baseline and 1y after surgical or conservative treatment. Correlations between scores and Cohen's kappa for agreement (κ) regarding achievement of the minimal clinically important change (MCIC) score on each instrument (ODI, 12.8 points; COMI, 2.2 points) were calculated, and regression models were built. The latter were tested for accuracy in an independent set of registry data from 634 patients (60 ± 15y; 56.8% female).

RESULTS

All pairs of measures were significantly positively correlated (baseline, 0.73; 1y follow-up (FU), 0.84; change-scores, 0.73). MCIC for COMI was achieved in 53.9% patients and for ODI, in 52.4%, with 78% agreement on an individual basis (κ = 0.56). Standard errors for the regression slopes and intercepts were low, indicating excellent prediction at the group level, but root mean square residuals (reflecting individual error) were relatively high. ODI was predicted as COMI × 7.13-4.20 (at baseline), COMI × 6.34 + 2.67 (at FU) and COMI × 5.18 + 1.92 (for change-score); COMI was predicted as ODI × 0.075 + 3.64 (baseline), ODI × 0.113 + 0.96 (FU), and ODI × 0.102 + 1.10 (change-score). ICCs were 0.63-0.87 for derived versus actual scores.

CONCLUSION

Predictions at the group level were very good and met standards justifying the pooling of data. However, we caution against using individual values for treatment decisions, e.g. attempting to monitor patients over time, first with one instrument and then with the other, due to the lower statistical precision at the individual level. The ability to convert scores via the developed mapping function should open up more centres/registries for collaboration and facilitate the combining of data in meta-analyses.

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.

Estimating Cost-Effectiveness Using Alternative Preference-Based Scores and Within-Trial Methods: Exploring the Dynamics of the Quality-Adjusted Life-Year Using the EQ-5D 5-Level Version and Recovering Quality of Life Utility Index

OBJECTIVES

This study aimed to explore quality-adjusted life-year (QALY) and subsequent cost-effectiveness estimates based on the more physical health-focused EQ-5D 5-level version (EQ-5D-5L) value set for England or cross-walked EQ-5D 3-level version UK value set scores or more mental health recovery-focused Recovering Quality of Life Utility Index (ReQoL-UI), when using alternative within-trial statistical methods. We describe possible reasons for the different QALY estimates based on the interaction between item scores, health state profiles, preference-based scores, and mathematical and statistical methods chosen.

METHODS

QALYs are calculated over 8 weeks from a case study 2:1 (intervention:control) randomized controlled trial in patients with anxiety or depression. Complete case and with missing cases imputed using multiple-imputation analyses are conducted, using unadjusted and regression baseline-adjusted QALYs. Cost-effectiveness is judged using incremental cost-effectiveness ratios and acceptability curves. We use previously established psychometric results to reflect on estimated QALYs.

RESULTS

A total of 361 people (241:120) were randomized. EQ-5D-5L crosswalk produced higher incremental QALYs than the value set for England or ReQoL-UI, which produced similar unadjusted QALYs, but contrasting baseline-adjusted QALYs. Probability of cost-effectiveness <£30 000 per QALY ranged from 6% (complete case ReQoL-UI baseline-adjusted QALYs) to 64.3% (multiple-imputation EQ-5D-5L crosswalk unadjusted QALYs). The control arm improved more on average than the intervention arm on the ReQoL-UI, a result not mirrored on the EQ-5D-5L nor condition-specific (Patient-Health Questionnaire-9, depression; Generalized Anxiety Disorder-7, anxiety) measures.

CONCLUSIONS

ReQoL-UI produced contradictory cost-effectiveness results relative to the EQ-5D-5L. The EQ-5D-5L's better responsiveness and "anxiety/depression" and "usual activities" items drove the incremental QALY results. The ReQoL-UI's single physical health item and "personal recovery" construct may have influenced its lower 8-week incremental QALY estimates in this patient sample.

Comparison of the PROMIS Preference Score (PROPr) and EQ-5D-5L Index Value in General Population Samples in the United Kingdom, France, and Germany

OBJECTIVES

The Patient-Reported Outcome Measurement Information System (PROMIS) Preference score (PROPr) can be used to assess health state utility (HSU) and estimate quality-adjusted life-years in cost-effectiveness analyses. It is based on item response theory and promises to overcome limitations of existing HSU scores such as ceiling effects. The PROPr contains 7 PROMIS domains: cognitive abilities, depression, fatigue, pain, physical function, sleep disturbance, and ability to participate in social roles and activities. We aimed to compare the PROPr with the 5-level EQ-5D (EQ-5D-5L) in terms of psychometric properties using data from 3 countries.

METHODS

We collected PROMIS-29 profile and EQ-5D-5L data from 3 general population samples (United Kingdom = 1509, France = 1501, Germany = 1502). Given that cognition is not assessed by the PROMIS-29, it was predicted by the recommended linear regression model. We compared the convergent validity, known-groups construct validity, and ceiling and floor effects of the PROPr and EQ-5D-5L.

RESULTS

The mean PROPr (0.48, 0.53, 0.48; P<.01) and EQ-5D-5L scores (0.82, 0.85, 0.83; P<.01) showed significant differences of similar magnitudes (d = 0.34; d = 0.32; d = 0.35; P<.01) across all samples. The differences were invariant to sex, income, occupation, education, and most conditions but not for age. The Pearson correlation coefficients between both scores were r = 0.74, r = 0.69, and r = 0.72. PROPr's ceiling and floor effects both were minor to moderate. The EQ-5D-5L's ceiling (floor) effects were major (negligible).

CONCLUSIONS

Both the EQ-5D-5L and the PROPr assessed by the PROMIS-29 show high validity. The PROPr yields considerably lower HSU values than the EQ-5D-5L. Consequences for quality-adjusted life-year measurements should be investigated in future research.

Mapping naso-ocular symptom scores to EQ-5D-5L utility values in Japanese cedar pollinosis

BACKGROUND

The total naso-ocular symptom score (TSS) is widely used as an endpoint to evaluate the severity of seasonal allergic rhinitis. However, it is not a generic preference-based measure. We sought to develop an algorithm for mapping between the TSS and health utility in Japanese cedar pollinosis (JCP). We also performed a cost-utility analysis of sublingual immunotherapy (SLIT) for JCP by using this algorithm.

METHODS

Patients with JCP filled out the TSS questionnaire and EQ-5D-5L simultaneously during the pollen season in 2019 and in 2020. We estimated a direct utility mapping model by regressing responses to individual TSS questions directly onto utility. The incremental cost-effectiveness ratio (ICER) of active SLIT to a placebo was determined by examining the drug expense and the estimated quality-adjusted life year (QALY) using a dataset from a double-blind placebo-controlled clinical trial.

RESULTS

A total of 238 records were included for analysis. The estimated utility decreased with increasing severity of rhinitis. Patients with comorbid asthma showed lower utility. A negative and significant correlation was seen between the TSS and utility in both 2019 and 2020. The estimated equations were: Y(utility) = -0.0161∗X(TSS) + 1.005 in non-asthmatic JCP patients. The ICER of active SLIT to the placebo was estimated to be 4,049,720 and 6,011,218 JPY/QALY in the first and second year, respectively.

CONCLUSIONS

It is possible to reasonably predict utility from the total naso-ocular symptom score by using regression models. In the estimated algorithm, pre-seasonal SLIT for JCP is cost-effective.

Health Economic Aspects of Childhood Excess Weight: A Structured Review

An economic perspective is crucial to understand the broad consequences of childhood excess weight (CEW). These can manifest in the form of elevated health care and societal costs, impaired health status, or inefficiencies in the allocation of resources targeted at its prevention, management, or treatment. Although existing systematic reviews provide summaries of distinct economic research strands covering CEW, they have a restricted focus that overlooks relevant evidence. The overarching aim of this structured review was to update and enhance recent key reviews of four strands of economic evidence in this area, namely, (1) economic costs associated with CEW, (2) health utilities associated with CEW, (3) economic evaluations of interventions targeting CEW, and (4) economic determinants and broader consequences of CEW. Our de novo searches identified six additional studies for the first research strand, five studies for the second, thirty-one for the third, and two for the fourth. Most studies were conducted in a small number of high-income countries. Our review highlights knowledge gaps across all the research strands. Evidence from this structured review can act as data input into future economic evaluations in this area and highlights areas where future economic research should be targeted.

Indirect and Direct Mapping of the Cancer-Specific EORTC QLQ-C30 onto EQ-5D-5L Utility Scores

OBJECTIVE

The aim of this study was to develop a response mapping algorithm to predict EQ-5D-5L utilities from European Organisation for Research and Treatment Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) scores and compare performance with direct mapping approaches to identify the best performing algorithm.

METHODS

The Multi-Instrument Comparison dataset contains responses to both the EQ-5D-5L and QLQ-C30 questionnaires from 692 individuals with a broad range of cancers. Response mapping was conducted, fitting ordered logistic regressions to predict response levels for each of the five EQ-5D dimensions and utilities were predicted using the US and Japanese EQ-5D-5L value sets to test the algorithm performance. Various direct mapping models were fitted: ordinary least squares, tobit, two-part (TPM), adjusted limited dependent variable mixture and beta mixture models. Model assessment and recommendations regarding the best mapping algorithm was based on goodness-of-fit statistics, predictive ability (measures of error, distribution of predicted utilities) and in sample cross-validation.

RESULTS

The response mapping model performed well in terms of predictive ability and measurement error using the US or Japanese value set, with mean absolute error ranging from 0.0708 to 0.0988, and comparably to the TPM, which was the best performing direct algorithm.

CONCLUSION

The developed mapping algorithms enable the prediction of EQ-5D-5L utilities from QLQ-C30 scores when EQ-5D-5L data have not been directly collected in clinical trials. The response mapping model offers the possibility of predicting EQ-5D-5L utility values using any national value set and can be generalised to multiple countries and oncology settings.

Improving health-related quality of life instrument translation into South African languages

Background

Most health-related quality of life (HRQoL) instruments have been created in English, which can influence their reliability and validity in non-English speaking populations. This study assessed the translation methodology of HRQoL instruments that have been used and translated into South African languages and which could be applied in cost-utility analyses (CUAs).

Methods

A 2019 systematic review was updated with searches conducted in Medline, the Web of Science^TM (WoS^TM) Core Collection and the South African SciELO collection via the WoS^TM Platform. Additional searches in Sabinet’s African Journals database and on instrument developers’ webpages were performed. Only HRQoL instruments suitable for CUAs were included. Articles reporting at least one element of the translation methods were included. Established good practice principles were used to evaluate the translation methodology.

Results

Within the 39 publications identified, a dozen translated instruments have been used in South Africa. All instruments used were translated from English and none had originally been created in South Africa. Instrument developers’ translations were used more than study investigators’ translations. Almost all instrument developer versions met the full translation criteria. No investigator translated instrument met the full translation criteria primarily because recommendations on forward and back translations were not followed. However, this analysis was hampered by a lack of methodological reporting details. The most used instruments, which also had the most translated versions available, were the EQ-5D-3L, SF-36 version 2 and EORTC QLQ-C30.

Conclusion

Instrument developers’ translations more often met recommended translation methodology compared with investigators’ versions. The EQ-5D-3L may be best suited for South African economic evaluations and for use in clinical practice, but further work may be needed.

A Review of Utility Measurement Methods Used in Pharmacoeconomic Submissions to HIRA in South Korea: Methodological Consistency and Areas for Improvement

Pharmacoeconomic (PE) guidelines, first published in 2006 and later updated in 2011, were developed to guide the preparation and submission of PE data to the Health Insurance Review and Assessment Service (HIRA) for drug reimbursement decision making in South Korea. This study, which was conducted as part of a project for revision of the PE guideline, reviewed utility values used in the PE submissions processed at HIRA during 2014-2018 to identify aspects of the current guidelines that may need to be revisited. A total of 50 PE submissions were processed at HIRA over the 5 years. Of these, 47 submissions that used quality-adjusted life-years as an outcome measure were included in this review. Data were extracted from full copies of the manufacturer's initial submissions and committee documents provided by HIRA. Of the 47 submissions, nearly half (n = 23, 48.9%) used published sources to obtain health state utility values, followed by direct methods using time trade-off (n = 7) or standard gamble (n = 2) and indirect methods with patient-level data using the EQ-5D-3L (n = 4) or the EQ-5D-5L (n = 2). Mapping, using the EQ-5D-3L as a target measure, was also adopted in six submissions, although it was somewhat unfavourably described in the guideline. Notably, 52.2% of the submissions with published sources took utility values from different sources for different health states defined in a single model. In addition, details of utility measurement methods or mapping functions taken from published sources were relatively poorly reported. Moreover, the preferences of the Korean general public, preferred by the guideline, were rarely reflected in the utility values used in submissions relying on published sources (95.7% for foreign values only/mixed) and mapping (66.7%). While most submissions with direct and indirect methods used domestic preference values, the former was occasionally criticised by assessment committees because of health state descriptions. This review highlights a considerable amount of inconsistency in the measurement of utility values used in the PE submissions during 2014-2018, indicating a strong need for methodological standardisation.

A framework for economic evaluation of therapeutic drug monitoring-guided dosing in oncology

The standard approach for dose individualization of chemotherapy in the oncology setting has long been based on body surface area (BSA) as a measure of body size. However, for many anticancer drugs, administration of dosages based on BSA may result in some patients receiving supratherapeutic or subtherapeutic concentrations due to substantial interindividual pharmacokinetic variability. Therapeutic drug monitoring (TDM)-guided dosing aims to ensure that the patient's serum drug concentration is in a target range which has been shown to produce optimal clinical outcomes. The management of several malignancies is now moving away from using traditional intravenous chemotherapy to longer-term treatment with targeted molecular therapies. These targeted anticancer drugs are currently dosed based on a fixed dose for all patients. The pharmacokinetic characteristics of most of these drugs (e.g., tyrosine-kinase inhibitors) support implementation of individualized dosing via TDM. However, prior to adopting TDM-guided dosing in oncology settings, the economic efficiency and value for money of introducing TDM interventions should be critically and systematically examined along with the impacts on patient care and outcomes. Yet, current evidence in this area is limited, and more generally, there is lack of methodological guidance on how to identify, estimate and value clinical and cost information necessary to conduct economic evaluations of TDM interventions. In this paper, we propose a coherent framework for conducting economic evaluation of TDM interventions in oncology settings and discuss some practical challenges of conducting economic evaluations of TDM.

The estimation of a preference-based single index for the IBS-QoL by mapping to the EQ-5D-5L in patients with irritable bowel syndrome

Purpose

The Irritable Bowel Syndrome Quality of Life (IBS-QoL) questionnaire is a commonly used and validated IBS-specific QoL instrument. However, this questionnaire is in contrast to the EQ-5D-5L, not preference-based and as such does not allow calculation of QALYs. The objective of this study was to describe the convergent- and known-group validity of both questionnaires and to develop a mapping algorithm from EQ-5D-5L which enable IBS-QoL scores to be transformed into utility scores for use in economic evaluations.

Methods

We used data from two multicenter randomized clinical trials, which represented the estimation and external validation dataset. The convergent validity was investigated by examining correlations between the EQ-5D-5L and IBS-QoL and the known-group validity by calculating effect sizes. Ordinary least squares (OLS), censored least absolute deviations (CLAD), and mixture models were used in this mapping approach.

Results

283 IBS patients were included (n = 189 vs. n = 84). Mean IBS-QoL score was 71.13 (SD 15.66) and mean EQ-5D-5L utility score was 0.73 (SD 0.19). The overall sensitivity of the IBS-QoL and EQ-5D-5L to discriminate between patient and disease characteristics was similar. CLAD model 4, containing the total IBS-QoL score and squared IBS-SSS (IBS severity scoring system), was chosen as the most appropriate model to transform IBS-QoL scores into EQ-5D-5L utility scores.

Conclusion

This study reports the development of an algorithm where the condition-specific questionnaire IBS-QoL can be used to calculate utility values for use in economic evaluations. Including a clinical measure, IBS-SSS, in the model improved the performance of the algorithm.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11136-021-02995-y.

Psychometric assessment of EQ-5D-5L and ReQoL measures in patients with anxiety and depression: construct validity and responsiveness

PURPOSE

Generic health measures have been questioned for quantifying mental-health-related outcomes. In patients with anxiety and/or depression, our aim is to assess the psychometric properties of the preference-based EQ-5D-5L (generic health) and ReQoL-UI (recovery-focussed quality of life) for economic evaluation against the PHQ-9 (depression) and GAD-7 (anxiety). EQ-5D-5L anxiety/depression item and ReQoL-10 are also assessed.

METHODS

A 2:1 (intervention: control) randomised controlled trial collected measures at baseline and 8 weeks post baseline; in the intervention arm, data were also collected 3, 6, 9, and 12-months post baseline. EQ-5D-5L preference-based scores were obtained from the value set for England (VSE) and 'cross-walked' EQ-5D-3L United Kingdom (UK) value set scores. ReQoL-UI preference-based scores were obtained from its UK value set as applied to seven ReQoL-10 items. EQ-5D-5L and ReQoL measures' construct validity and responsiveness were assessed compared against PHQ-9 and GAD-7 scores and group cut-offs.

RESULTS

361 people were randomised to intervention (241) or control (120). ReQoL-UI/-10 had better construct validity with depression severity than the EQ-5D-5L (VSE/cross-walk scores), which had relatively better construct validity with anxiety severity than the ReQoL-UI/-10. Across all intervention-arm time-points relative to baseline, responsiveness was generally better for EQ-5D-5L (VSE in particular) than ReQoL-UI, but worse than ReQoL-10.

CONCLUSION

There is insufficient evidence to recommend the ReQoL-UI over EQ-5D-5L for economic evaluations to capture anxiety severity. However, there may be rationale for recommending the ReQoL-UI over the EQ-5D-5L to capture depression severity given its better construct validity, albeit poorer responsiveness, and if recovery-focussed quality of life relative to condition-specific symptomology is the construct of interest.

Mapping of the World Health Organization's Disability Assessment Schedule 2.0 to disability weights using the Multi-Country Survey Study on Health and Responsiveness

OBJECTIVES

To develop and test an internationally applicable mapping function for converting WHODAS-2.0 scores to disability weights, thereby enabling WHODAS-2.0 to be used in cost-utility analyses and sectoral decision-making.

METHODS

Data from 14 countries were used from the WHO Multi-Country Survey Study on Health and Responsiveness, administered among nationally representative samples of respondents aged 18+ years who were non-institutionalized and living in private households. For the combined total of 92,006 respondents, available WHODAS-2.0 items (for both 36-item and 12-item versions) were mapped onto disability weight estimates using a machine learning approach, whereby data were split into separate training and test sets; cross-validation was used to compare the performance of different regression and penalized regression models. Sensitivity analyses considered different imputation strategies and compared overall model performance with that of country-specific models.

RESULTS

Mapping functions converted WHODAS-2.0 scores into disability weights; R-squared values of 0.700-0.754 were obtained for the test data set. Penalized regression models reached comparable performance to standard regression models but with fewer predictors. Imputation had little impact on model performance. Model performance of the generic model on country-specific test sets was comparable to model performance of country-specific models.

CONCLUSIONS

Disability weights can be generated with good accuracy using WHODAS 2.0 scores, including in national settings where health state valuations are not directly available, which signifies the utility of WHODAS as an outcome measure in evaluative studies that express intervention benefits in terms of QALYs gained.

Predicting presenteeism using measures of health status

Objectives

To identify whether it is feasible to develop a mapping algorithm to predict presenteeism using multiattribute measures of health status.

Methods

Data were collected using a bespoke online survey in a purposive sample (n = 472) of working individuals with a self-reported diagnosis of Rheumatoid arthritis (RA). Survey respondents were recruited using an online panel company (ResearchNow). This study used data captured using two multiattribute measures of health status (EQ5D-5 level; SF6D) and a measure of presenteeism (WPAI, Work Productivity Activity Index). Statistical correlation between the WPAI and the two measures of health status (EQ5D-5 level; SF6D) was assessed using Spearman’s rank correlation. Five regression models were estimated to quantify the relationship between WPAI and predict presenteeism using health status. The models were specified based in index and domain scores and included covariates (age; gender). Estimated and observed presenteeism were compared using tenfold cross-validation and evaluated using Root mean square error (RMSE).

Results

A strong and negative correlation was found between WPAI and: EQ5D-5 level and WPAI (r = − 0.64); SF6D (r =− 0.60). Two models, using ordinary least squares regression were identified as the best performing models specifying health status using: SF6D domains with age interacted with gender (RMSE = 1.7858); EQ5D-5 Level domains and age interacted with gender (RMSE = 1.7859).

Conclusions

This study provides indicative evidence that two existing measures of health status (SF6D and EQ5D-5L) have a quantifiable relationship with a measure of presenteeism (WPAI) for an exemplar application of working individuals with RA. A future study should assess the external validity of the proposed mapping algorithms.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11136-021-02936-9.

Mapping PedsQL™ Generic Core Scales to EQ-5D-3L utility scores in transfusion-dependent thalassemia patients

PURPOSE

To develop a mapping algorithm for generating EQ-5D-3L utility scores from the PedsQL Generic Core Scales (PedsQL GCS) in patients with transfusion-dependent thalassemia (TDT).

METHODS

The algorithm was developed using data from 345 TDT patients. Spearman's rank correlation was used to evaluate the conceptual overlap between the instruments. Model specifications were chosen using a stepwise regression. Both direct and response mapping methods were attempted. Six mapping estimation methods ordinary least squares (OLS), a log-transformed response using OLS, generalized linear model (GLM), two-part model (TPM), Tobit and multinomial logistic regression (MLOGIT) were tested to determine the root mean squared error (RMSE) and mean absolute error (MAE). Other criterion used were accuracy of the predicted utility score, proportions of absolute differences that was less than 0.03 and intraclass correlation coefficient. An in-sample, leave-one-out cross validation was conducted to test the generalizability of each model.

RESULTS

The best performing model was specified with three out of the four PedsQL GCS scales-the physical, emotional and social functioning score. The best performing estimation method for direct mapping was a GLM with a RMSE of 0.1273 and MAE of 0.1016, while the best estimation method for response mapping was the MLOGIT with a RMSE of 0.1597 and MAE of 0.0826.

CONCLUSION

The mapping algorithm developed using the GLM would facilitate the calculation of utility scores to inform economic evaluations for TDT patients when EQ-5D data is not available. However, caution should be exercised when using this algorithm in patients who have poor quality of life.

Response Mapping Methods to Estimate the EQ-5D-5L From the Western Ontario McMaster Universities Osteoarthritis in Patients With Hip or Knee Osteoarthritis

OBJECTIVES

The mapping technique can estimate generic preference-based measure scores through a specific measure that cannot be used in economic evaluations. This study compared 2 response mapping methods to estimate EQ-5D-5L scores using the Western Ontario McMaster Universities Osteoarthritis (WOMAC).

METHODS

The sample consisted of 758 patients with the hip or knee osteoarthritis recruited in baseline. Bayesian networks (BN) and multinomial logistic regression (ML) were used as response mapping models. Predictions were obtained using the 6-month follow-up as a validation sample. The mean absolute error, mean squared error, deviation from the root mean squared error and intraclass correlation coefficient were calculated as precision measures.

RESULTS

There was 5.5% of missing data, which was removed. The mean age was 69.6 years (standard deviation = 10.5), with 61.6% of women. The BN model presented lower mean absolute error, mean squared error, root mean squared error and higher intraclass correlation coefficient than the ML model. Only the WOMAC items pain and physical function items were related with the EQ-5D-5L dimensions.

CONCLUSION

BN response mapping models are more robust methods, with better prediction results, than ML models. The BN model also provided a graphic representation of the dependency relationships between the EQ-5D-5L dimensions and the different WOMAC items that could be useful in the clinical investigation of patients with hip or knee osteoarthritis.

A video-feedback parenting intervention to prevent enduring behaviour problems in at-risk children aged 12-36 months: the Healthy Start, Happy Start RCT

BACKGROUND

Behaviour problems emerge early in childhood and place children at risk for later psychopathology.

OBJECTIVES

To evaluate the clinical effectiveness and cost-effectiveness of a parenting intervention to prevent enduring behaviour problems in young children.

DESIGN

A pragmatic, assessor-blinded, multisite, two-arm, parallel-group randomised controlled trial.

SETTING

Health visiting services in six NHS trusts in England.

PARTICIPANTS

A total of 300 at-risk children aged 12-36 months and their parents/caregivers.

INTERVENTIONS

Families were allocated in a 1 : 1 ratio to six sessions of Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD) plus usual care or usual care alone.

MAIN OUTCOME MEASURES

The primary outcome was the Preschool Parental Account of Children's Symptoms, which is a structured interview of behaviour symptoms. Secondary outcomes included caregiver-reported total problems on the Child Behaviour Checklist and the Strengths and Difficulties Questionnaire. The intervention effect was estimated using linear regression. Health and social care service use was recorded using the Child and Adolescent Service Use Schedule and cost-effectiveness was explored using the Preschool Parental Account of Children's Symptoms.

RESULTS

In total, 300 families were randomised: 151 to VIPP-SD plus usual care and 149 to usual care alone. Follow-up data were available for 286 (VIPP-SD, n = 140; usual care, n = 146) participants and 282 (VIPP-SD, n = 140; usual care, n = 142) participants at 5 and 24 months, respectively. At the post-treatment (primary outcome) follow-up, a group difference of 2.03 on Preschool Parental Account of Children's Symptoms (95% confidence interval 0.06 to 4.01; p = 0.04) indicated a positive treatment effect on behaviour problems (Cohen's d = 0.20, 95% confidence interval 0.01 to 0.40). The effect was strongest for children's conduct [1.61, 95% confidence interval 0.44 to 2.78; p = 0.007 (d = 0.30, 95% confidence interval 0.08 to 0.51)] versus attention deficit hyperactivity disorder symptoms [0.29, 95% confidence interval -1.06 to 1.65; p = 0.67 (d = 0.05, 95% confidence interval -0.17 to 0.27)]. The Child Behaviour Checklist [3.24, 95% confidence interval -0.06 to 6.54; p = 0.05 (d = 0.15, 95% confidence interval 0.00 to 0.31)] and the Strengths and Difficulties Questionnaire [0.93, 95% confidence interval -0.03 to 1.9; p = 0.06 (d = 0.18, 95% confidence interval -0.01 to 0.36)] demonstrated similar positive treatment effects to those found for the Preschool Parental Account of Children's Symptoms. At 24 months, the group difference on the Preschool Parental Account of Children's Symptoms was 1.73 [95% confidence interval -0.24 to 3.71; p = 0.08 (d = 0.17, 95% confidence interval -0.02 to 0.37)]; the effect remained strongest for conduct [1.07, 95% confidence interval -0.06 to 2.20; p = 0.06 (d = 0.20, 95% confidence interval -0.01 to 0.42)] versus attention deficit hyperactivity disorder symptoms [0.62, 95% confidence interval -0.60 to 1.84; p = 0.32 (d = 0.10, 95% confidence interval -0.10 to 0.30)], with little evidence of an effect on the Child Behaviour Checklist and the Strengths and Difficulties Questionnaire. The primary economic analysis showed better outcomes in the VIPP-SD group at 24 months, but also higher costs than the usual-care group (adjusted mean difference £1450, 95% confidence interval £619 to £2281). No treatment- or trial-related adverse events were reported. The probability of VIPP-SD being cost-effective compared with usual care at the 24-month follow-up increased as willingness to pay for improvements on the Preschool Parental Account of Children's Symptoms increased, with VIPP-SD having the higher probability of being cost-effective at willingness-to-pay values above £800 per 1-point improvement on the Preschool Parental Account of Children's Symptoms.

LIMITATIONS

The proportion of participants with graduate-level qualifications was higher than among the general public.

CONCLUSIONS

VIPP-SD is effective in reducing behaviour problems in young children when delivered by health visiting teams. Most of the effect of VIPP-SD appears to be retained over 24 months. However, we can be less certain about its value for money.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN58327365.

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. 25, No. 29. See the NIHR Journals Library website for further project information.

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.

Psychometric properties of the SF-6Dv2 in an Iranian breast cancer population

INTRODUCTION

The Short-Form Six-Dimension version 2 (SF-6Dv2) is the newest preference-based instrument for estimation of quality adjusted life-years (QALYs). The aim of this study is to evaluate the validity and reliability of the SF-6Dv2 in an Iranian breast cancer population.

METHODS

The SF-6Dv2 and FACT-B instruments were completed for 416 patients who were recruited from the largest academic center for cancer patients in Iran. The ceiling effects are computed as the proportion of participants reporting no problems in SF-6Dv2 index. Construct validity was evaluated using convergent validity, discriminant validity, and known-groups validity. Reliability was assessed using intra-class correlation coefficient (ICC) and Cohen's kappa value.

RESULTS

The ceiling effects of the SF-6Dv2 was 2.16%. Higher scores of all subscales of the FACT-B were associated with patients who reported no problems in each of the SF-6Dv2 dimensions. The correlation between SF-6Dv2 dimensions and FACT-B subscales varied from 0.109 between the role limitation of the SF-6Dv2 and the SWB subscale of the FACT-B to 0.665 between the pain dimension of SF-6Dv2 and the PWB of FACT-B. The lower mean score of SF-6Dv2 was associated with patients with older age, higher education level, more severe current treatment status, and more severe cancer stage status. ICC for the SF-6Dv2 index scores was 0.66, and Kappa values varied from 0.33 for mobility to 0.66 for mental health dimensions.

CONCLUSIONS

The validity and reliability of the SF-6Dv2 were satisfaction in a breast cancer population and it can be employed in clinical practice or research.

Protocol for the development of a repository of individual participant data from randomised controlled trials conducted in adult care homes (the Virtual International Care Homes Trials Archive (VICHTA))

Background

Approximately 418,000 people live in care homes in the UK, yet accessible, robust data on care home populations and organisation are lacking. This hampers our ability to plan, allocate resources or prevent risk. Large randomised controlled trials (RCTs) conducted in care homes offer a potential solution. The value of detailed data on residents’ demographics, outcomes and contextual information captured in RCTs has yet to be fully realised. Irrespective of the intervention tested, much of the trial data collected overlaps in terms of structured assessments and descriptive information. Given the time and costs required to prospectively collect data in these populations, pooling anonymised RCT data into a structured repository offers benefit; secondary analyses of pooled RCT data can improve understanding of this under-researched population and enhance the future trial design. This protocol describes the creation of a project-specific repository of individual participant data (IPD) from trials conducted in care homes and subsequent expansion into a legacy dataset for wider use, to address the need for accurate, high-quality IPD on this vulnerable population.

Methods

Informed by scoping of relevant literature, the principal investigators of RCTs conducted in adult care homes in the UK since 2010 will be invited to contribute trial IPD. Contributing trialists will form a Steering Committee who will oversee data sharing and remain gatekeepers of their own trial’s data. IPD will be cleaned and standardised in consultation with the Steering Committee for accuracy. Planned analyses include a comparison of pooled IPD with point estimates from administrative sources, to assess generalisability of RCT data to the wider care home population. We will also identify key resident characteristics and outcomes from within the trial repository, which will inform the development of a national minimum dataset for care homes. Following project completion, management will migrate to the Virtual Trials Archives, forming a legacy dataset which will be expanded to include international RCTs, and will be accessible to the wider research community for analyses.

Discussion

Analysis of pooled IPD has the potential to inform and direct future practice, research and policy at low cost, enhancing the value of existing data and reducing research waste. We aim to create a permanent archive for care home trial data and welcome the contribution of emerging trial datasets.

Estimation of losses of quality-adjusted life expectancy attributed to the combination of cognitive impairment and multimorbidity among Chinese adults aged 45 years and older

OBJECTIVES

This study aims to estimate the losses of quality-adjusted life expectancy (QALE) due to the joint effects of cognitive impairment and multimorbidity, and to further confirm additional losses attributable to this interaction among middle-aged and elderly Chinese people.

METHODS

The National Cause of Death Monitoring Data were linked with the China Health and Retirement Longitudinal Study (CHARLS). A mapping and assignment method was used to estimate health utility values, which were further used to calculate QALE. Losses of QALE were measured by comparing the differences between subgroups. All the losses of QALE were displayed at two levels: the individual and population levels.

RESULTS

At age 45, the individual-level and population-level losses of QALE attributed to the combination of cognitive impairment and multimorbidity were 7.61 (95% CI: 5.68, 9.57) years and 4.30 (95% CI: 3.43, 5.20) years, respectively. The losses for cognitive impairment alone were 3.10 (95% CI: 2.29, 3.95) years and 1.71 (95% CI: 1.32, 2.13) years at the two levels. Similarly, the losses for multimorbidity alone were 3.53 (95% CI: 2.53, 4.56) years and 1.91 (95% CI: 1.24, 2.63) years at the two levels. Additional losses due to the interaction of cognitive impairment and multimorbidity were indicated by the 0.98 years of the individual-level gap and 0.67 years of the population-level gap.

CONCLUSION

Among middle-aged and elderly Chinese people, cognitive impairment and multimorbidity resulted in substantial losses of QALE, and additional QALE losses were seen due to their interaction at both individual and population levels.

Predicting EQ-5D-5L crosswalk from the PROMIS-29 profile for the United Kingdom, France, and Germany

Background

EQ-5D health state utilities (HSU) are commonly used in health economics to compute quality-adjusted life years (QALYs). The EQ-5D, which is country-specific, can be derived directly or by mapping from self-reported health-related quality of life (HRQoL) scales such as the PROMIS-29 profile. The PROMIS-29 from the Patient Reported Outcome Measures Information System is a comprehensive assessment of self-reported health with excellent psychometric properties. We sought to find optimal models predicting the EQ-5D-5L crosswalk from the PROMIS-29 in the United Kingdom, France, and Germany and compared the prediction performances with that of a US model.

Methods

We collected EQ-5D-5L and PROMIS-29 profiles and three samples representative of the general populations in the UK (n = 1509), France (n = 1501), and Germany (n = 1502). We used stepwise regression with backward selection to find the best models to predict the EQ-5D-5L crosswalk from all seven PROMIS-29 domains. We investigated the agreement between the observed and predicted EQ-5D-5L crosswalk in all three countries using various indices for the prediction performance, including Bland–Altman plots to examine the performance along the HSU continuum.

Results

The EQ-5D-5L crosswalk was best predicted in France (nRMSE_FRA = 0.075, nMAE_FRA = 0.052), followed by the UK (nRMSE_UK = 0.076, nMAE_UK = 0.053) and Germany (nRMSE_GER = 0.079, nMAE_GER = 0.051). The Bland–Altman plots show that the inclusion of higher-order effects reduced the overprediction of low HSU scores.

Conclusions

Our models provide a valid method to predict the EQ-5D-5L crosswalk from the PROMIS-29 for the UK, France, and Germany.