Do country-specific preference weights matter in the choice of mapping algorithms? The case of mapping the Diabetes-39 onto eight country-specific EQ-5D-5L value sets

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 12-item World Health Organization disability assessment schedule 2.0 (WHODAS 2.0) onto the assessment of quality of life (AQoL)-4D utilities

PURPOSE

The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a widely used disability-specific outcome measure. This study develops mapping algorithms to estimate Assessment of Quality of Life (AQoL)-4D utilities based on the WHODAS 2.0 responses to facilitate economic evaluation.

METHODS

The study sample comprises people with disability or long-term conditions (n = 3376) from the 2007 Australian National Survey of Mental Health and Wellbeing. Traditional regression techniques (i.e., Ordinary Least Square regression, Robust MM regression, Generalised Linear Model and Betamix Regression) and machine learning techniques (i.e., Lasso regression, Boosted regression, Supported vector regression) were used. Five-fold internal cross-validation was performed. Model performance was assessed using a series of goodness-of-fit measures.

RESULTS

The robust MM estimator produced the preferred mapping algorithm for the overall sample with the smallest mean absolute error in cross-validation (MAE = 0.1325). Different methods performed differently for different disability subgroups, with the subgroup with profound or severe restrictions having the highest MAE across all methods and models.

CONCLUSION

The developed mapping algorithm enables cost-utility analyses of interventions for people with disability where the WHODAS 2.0 has been collected. Mapping algorithms developed from different methods should be considered in sensitivity analyses in economic evaluations.

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.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Mapping the Patient-Reported Outcomes Measurement Information System (PROMIS-29) to EQ-5D-5L

BACKGROUND AND OBJECTIVE

The Patient-Reported Outcomes Measurement Information System (PROMIS-29) is gaining popularity as healthcare system funders increasingly seek value-based care. However, it is limited in its ability to estimate utilities and thus inform economic evaluations. This study develops the first mapping algorithm for estimating EuroQol 5-Dimension 5-Level (EQ-5D-5L) utilities from PROMIS-29 responses using a large dataset and through extensive comparisons between econometric models.

METHODS

An online survey was conducted to collect responses to PROMIS-29 and EQ-5D-5L from the general Australian population (N = 3013). Direct and indirect mapping methods were explored, including linear regression, Tobit, generalised linear model, censored regression model, beta regression (Betamix), the adjusted limited dependent variable mixture model (ALDVMM) and generalised ordered logit. The most robust model was selected by assessing the performance based on average ten-fold cross-validation geometric mean absolute error and geometric mean squared error, the predicted mean, maximum and minimum utilities, as well as the fitting across the entire distribution.

RESULTS

The direct approach using ALDVMM was considered the preferred model based on lowest geometric mean absolute error and geometric mean squared error in cross-validation (0.0882, 0.0299) and its superiority in predicting the actual observed mean, full health states and lower utility extremes. The robustness and precision in prediction across the entire distribution of utilities with ALDVMM suggest it is an accurate and valid mapping algorithm. Moreover, the suggested mapping algorithm outperformed previously published algorithms using Australian data, indicating the validity of this model for economic evaluations.

CONCLUSIONS

This study developed a robust algorithm to estimate EQ-5D-5L utilities from PROMIS-29. Consistent with the recent literature, the ALDVMM outperformed all other econometric models considered in this study, suggesting that the mixture models have relatively better performance and are an ideal candidate model for mapping.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Validação do instrumento reduzido Diabetes-21 para avaliação da qualidade de vida relacionada à saúde em pessoas com diabetes

Resumo Objetivo Analisar a validade, confiabilidade e interpretabilidade de instrumento reduzido para avaliação da qualidade de vida relacionada à saúde entre pessoas com diabetes mellitus. Métodos Estudo de validação, composto pelas fases de adaptação do instrumento Diabetes-39 (constituído por 5 dimensões e 39 itens), pré-teste, análises de validade estrutural (exploratória e confirmatória), confiabilidade, validade concorrente e interpretabilidade. Resultados A estrutura fatorial da versão final reduzida diferiu do instrumento original. Foram reduzidos os itens, de 39 para 21, e as dimensões, de 5 para 4. As cargas fatoriais, nas análises exploratória e confirmatória, variaram entre 0,41 e 0,90 e entre 0,51 e 0,89, respectivamente. A confiabilidade apresentou-se adequada (alfa de Cronbach=0,91; Kappa≥0,60 em todos os itens; coeficiente de correlação intraclasse=0,91). Conclusão O instrumento reduzido Diabetes-21 foi considerado válido, confiável e interpretável para avaliação da qualidade de vida relacionada à saúde entre pessoas com diabetes mellitus.

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

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

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

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

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

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

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.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Does linear equating improve prediction in mapping? Crosswalking MacNew onto EQ-5D-5L value sets

PURPOSE

Preference-based measures are essential for producing quality-adjusted life years (QALYs) that are widely used for economic evaluations. In the absence of such measures, mapping algorithms can be applied to estimate utilities from disease-specific measures. This paper aims to develop mapping algorithms between the MacNew Heart Disease Quality of Life Questionnaire (MacNew) instrument and the English and the US-based EQ-5D-5L value sets.

METHODS

Individuals with heart disease were recruited from six countries: Australia, Canada, Germany, Norway, UK and the US in 2011/12. Both parametric and non-parametric statistical techniques were applied to estimate mapping algorithms that predict utilities for MacNew scores from EQ-5D-5L value sets. The optimal algorithm for each country-specific value set was primarily selected based on root mean square error (RMSE), mean absolute error (MAE), concordance correlation coefficient (CCC), and r-squared. Leave-one-out cross-validation was conducted to test the generalizability of each model.

RESULTS

For both the English and the US value sets, the one-inflated beta regression model consistently performed best in terms of all criteria. Similar results were observed for the cross-validation results. The preferred model explained 59 and 60% for the English and the US value set, respectively. Linear equating provided predicted values that were equivalent to observed values.

CONCLUSIONS

The preferred mapping function enables to predict utilities for MacNew data from the EQ-5D-5L value sets recently developed in England and the US with better accuracy. This allows studies, which have included the MacNew to be used in cost-utility analyses and thus, the comparison of services with interventions across the health system.

Exploring health-related quality of life and frailty in older adults based on the Korean Frailty and Aging Cohort Study

PURPOSE

The study aimed to analyze the association between frailty and health-related quality of life (HRQOL) based on the Korean Frailty and Aging Cohort Study.

METHODS

In this cross-sectional study, 2905 adults aged 70 to 84 years were enrolled. Frailty was determined according to the Fried frailty index. HRQOL was measured using the 5-level EuroQol questionnaire (EQ-5D-5L) and the 12-item Short-Form Health Survey version 2 (SF-12). Hierarchical linear regressions were conducted to examine the relationship between frailty and HRQOL and a logistic regression analysis was performed to estimate odds ratios of frailty status in the scores of the lowest quartiles in each scale.

RESULTS

Of the total respondents, 7.8% were frail, 47.0% were pre-frail, and 45.2% were robust. Frail respondents had significantly lower HRQOL scores than robust respondents, especially for EQ-5D-5L utility weights (0.74 vs 0.93). Frailty was strongly associated with decreased HRQOL in both physical and mental component summary of SF-12 (p < 0.001). Both pre-frail and frail states were related to greater odds of scoring in the bottom 25% of HRQOL scales compared to the non-frail state (p < 0.0001).

CONCLUSION

Frailty was associated with declined HRQOL in Korean older adults. This result recommends raising awareness about identifying and preventing frailty for better quality of life in the Korean elderly population.

A mapping study in mainland China: predicting EQ-5D-5L utility scores from the psoriasis disability index

Aims: This study aims to develop a mapping algorithm that can be used to predict 5-level EQ-5D (EQ-5D-5L) utility scores from the Psoriasis Disability Index (PDI) for further use in cost-utility analysis among psoriasis patients.Materials and Methods: A total of 321 participants with psoriasis was recruited in a dermatology clinic from a tertiary hospital in China. The EQ-5D-5L utility scores were scored using the Chinese-specific value set. Three model specifications were used and each one was estimated using three different statistical techniques, including the ordinary least squares (OLS), the Tobit regression and the generalized linear model (GLM). The goodness-of-fit of mapping performance was estimated by using two common indicators: the mean absolute error (MAE) and the mean square error (MSE).Results: A final validated sample of 321 psoriasis patients was analyzed in the study. The patients had a mean ± standard deviation (SD) age of 39.7 ± 12.9 years, and the EQ-5D-5L state utility score is 0.899 ± 0.106. Among all the models considered, the OLS linear model based on the four PDI item scores was selected as the best model due to higher accuracy (MAE = 0.1334 and 0.1557 for the estimation and validation sample separately).Limitations: The main limitation of this study is that the survey site was limited to one hospital and not more broadly representing the whole of China. Additionally, there are some missing data in the full sample and an absence of an external dataset to validate the algorithms.Conclusions: The mapping algorithms reported in this paper can be used to predict the EQ-5D-5L utilities from the PDI; however, similar to other mapping studies in the literature it can only serve as the second-best approach to elicit utilities from disease-specific instruments.

Health-related quality of life and health utility score of patients with gastric cancer: A multi-centre cross-sectional survey in China

OBJECTIVE

To evaluate the health-related quality of life (HRQoL) and health state utility scores of gastric cancer patients in daily life at different clinical stages after treatment, and to explore influencing factors associated with HRQoL.

METHODS

Gastric cancer patients discharged from hospitals and healthy controls identified by screening were recruited. The three-level EQ-5D was employed to assess HRQoL and was scored using two Chinese-specific tariffs published in 2014 and 2018.

RESULTS

A total of 1,399 patients and 2,179 healthy controls were recruited. The likelihood of reporting problems in the five dimensions for patients was 4.0-23.8 times higher than controls. Based on the 2014/2018 tariff, the mean EQ-5D utility score was 0.321/0.163 lower than controls, and the mean utility scores of each patient subgroup were 0.077/0.039 (high-grade intraepithelial neoplasia/carcinoma in situ), 0.254/0.121 (Stage I), 0.249/0.123 (Stage II), 0.353/0.182 (Stage III) and 0.591/0.309 (Stage IV) lower than controls (all statistically significant). Age, occupation, duration of illness, other chronic disease status and therapeutic regimen had a significant impact upon different aspects of HRQoL in patients.

CONCLUSIONS

Gastric cancer significantly impaired patients' HRQoL in daily life after treatment. More advanced cancer stages were associated with larger decrements on health state utility.

Mapping the Minnesota living with heart failure questionnaire (MLHFQ) to EQ-5D-5L in patients with heart failure

BACKGROUND

Mapping algorithms can be used to convert scores from a non-preference based instrument to health state utilities. The objective of this study was to develop mapping algorithms which will enable the Minnesota Living with Heart Failure Questionnaire (MLHFQ) scores to be converted into EQ-5D-5L utility scores that can be used in heart failure related cost utility studies.

METHOD

Patients diagnosed with heart failure were recruited from Australia. Mapping algorithms were developed using both direct and indirect response mapping approach. Three model specifications were considered to predict the EQ-5D-5 L utility score using MLHFQ total score (Model 1), MLHFQ domain scores (Model 2), or MLHFQ item scores (Model 3). Six regression techniques, each of which has the capability to cope with either skewness, heteroscedasticity, ceiling effects and/or the potential presence of outliers in the data set were used to identify the optimal mapping functions for each of the three models. Goodness-of-fit of the models were assessed using six indicators. In the absence of an external validation dataset, predictive performance of was assessed using three-fold cross validation method. In the indirect response mapping, EQ. 5D 5 L responses were predicted separately using the MLHFQ item scores using ordered logit model.

RESULTS

A total of 141 patients participated in the study. The lowest mean absolute error (MAE) was recorded from the multivariable fractional polynomials (MFP) model in all three-model specifications. Regarding the indirect response mapping, results showed that the performance was comparable with the direct mapping approach based on root mean squared error (RMSE) but was worse based on MAE.

CONCLUSION

The MLHFQ can be mapped onto EQ-5D-5 L utilities with good predictive accuracy using both direct and indirect response mapping techniques. The reported mapping algorithms would facilitate calculation of health utility for economic evaluations related to heart failure.

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

BACKGROUND

Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values (HSUVs) from data obtained from another health-related quality of life (HRQoL) measure. There have been several methodological developments in this area since a previous review up to 2007.

OBJECTIVE

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

DATA SOURCES

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

STUDY SELECTION

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

DATA EXTRACTION

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

RESULTS

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

CONCLUSIONS

The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions.

Testing alternative regression models to predict utilities: mapping the QLQ-C30 onto the EQ-5D-5L and the SF-6D

PURPOSE

The purpose of the study was to compare alternative statistical techniques to find the best approach for converting QLQ-C30 scores onto EQ-5D-5L and SF-6D utilities, and to estimate the mapping algorithms that best predict these health state utilities.

METHODS

772 cancer patients described their health along the cancer-specific instrument (QLQ-C30) and two generic preference-based instruments (EQ-5D-5L and SF-6D). Seven alternative regression models were applied: ordinary least squares, generalized linear model, extended estimating equations (EEE), fractional regression model, beta binomial (BB) regression, logistic quantile regression and censored least absolute deviation. Normalized mean absolute error (NMAE), normalized root mean square error (NRMSE), r-squared (r²) and concordance correlation coefficient (CCC) were used as model performance criteria. Cross-validation was conducted by randomly splitting internal dataset into two equally sized groups to test the generalizability of each model.

RESULTS

In predicting EQ-5D-5L utilities, the BB regression performed best. It gave better predictive accuracy in terms of all criteria in the full sample, as well as in the validation sample. In predicting SF-6D, the EEE performed best. It outperformed in all criteria: NRMSE = 0.1004, NMAE = 0.0798, CCC = 0.842 and r² = 72.7% in the full sample, and NRMSE = 0.1037, NMAE = 0.0821, CCC = 0.8345 and r² = 71.4% in cross-validation.

CONCLUSIONS

When only QLQ-C30 data are available, mapping provides an alternative approach to obtain health state utility data for use in cost-effectiveness analyses. Among seven alternative regression models, the BB and the EEE gave the most accurate predictions for EQ-5D-5L and SF-6D, respectively.