Mapping the EQ-5D index from the cystic fibrosis questionnaire-revised using multiple modelling approaches

Measuring the burden of cystic fibrosis: A scoping review

BACKGROUND

Cystic fibrosis (CF) contributes a significant economic burden on individuals, healthcare systems, and society. Understanding the economic impact of CF is crucial for planning resource allocation.

METHODS

We conducted a scoping review of literature published between 1990 and 2022 that reported the cost of illness, and/or economic burden of CF. Costs were adjusted for inflation and reported as United States dollars.

RESULTS

A total of 39 studies were included. Direct healthcare costs (e.g., medications, inpatient and outpatient care) were the most frequently reported. Most studies estimated the cost of CF using a prevalence-based (n = 18, 46.2 %), bottom-up approach (n = 23, 59 %). Direct non-healthcare costs and indirect costs were seldom included. The most frequently reported direct cost components were medications (n = 34, 87.2 %), inpatient care (n = 33, 84.6 %), and outpatient care (n = 31, 79.5 %). Twenty-eight percent (n = 11) of studies reported the burden of CF from all three perspectives (healthcare system (payer), individual, and society). Indirect costs of CF were reported in approximately 20 % of studies (n = 8). The reported total cost of CF varied widely, ranging from $451 to $160,000 per person per year (2022 US$). The total cost depended on the number of domains and perspectives included in each study.

CONCLUSIONS

Most studies only reported costs to the healthcare system (i.e., hospitalizations and healthcare encounters) which likely underestimates the total costs of CF. The wide range of costs reported highlights the importance of standardizing perspectives, domains and costs when estimating the economic burden of CF.

Evaluating the correspondence between the EQ-5D-5L and disease severity and quality of life in adults and adolescents with cystic fibrosis

BACKGROUND

The EQ-5D is the recommended measure to capture health-related quality of life (HRQoL), recognised for use in health technology appraisal bodies. In order to assess whether it is appropriate to use the EQ-5D for making decisions about the cost-utility of treatments in cystic fibrosis (CF), this study assesses the performance of the EQ-5D-5L in adults and adolescents with CF.

METHOD

This was a cross-sectional observational survey study of patients with CF attending a single large CF centre. Participants were asked to complete a survey that included two HRQoL measures; the EQ-5D-5L and CF Quality of Life (CFQoL) questionnaires.

RESULTS

Among 213 participants, the median EQ-5D-5L index score was 0.76 (IQR 0.66 - 0.84) and the visual analogue (EQ-VAS) was 70 (60 - 80). Both the EQ-5D index and EQ-VAS discriminated between disease severity based on lung function (p = 0.01 and p < 0.01, respectively) and pulmonary exacerbation (p = 0.02 and p < 0.01, respectively); however, EQ-VAS differentiated between more lung function severity groups compared to EQ-5D index. The EQ-5D-5L demonstrated convergent validity as its dimensions, index score, and EQ-VAS had significant correlations with most CFQoL domains. Though, EQ-VAS significantly predicted more domains of CFQoL (4 domains) compared to EQ-5D index (only 1 domain).

CONCLUSION

The generic EQ-5D-5L performed adequately in discriminating between CF disease severity, and its index score and EQ-VAS had moderate correlations with CFQoL. However, using a complementary condition-specific measure alongside the EQ-5D-5L can provide better insight of HRQoL in CF and benefit the process of cost-utility analysis.

Socioeconomic burden of cystic fibrosis in Canada

BACKGROUND

Cost of illness studies are important tools to summarise the burden of disease for individuals, the healthcare system and society. The lack of standardised methods for reporting costs for cystic fibrosis (CF) makes it difficult to quantify the total socioeconomic burden. In this study, we aimed to comprehensively report the socioeconomic burden of CF in Canada.

METHODS

The total cost of CF in Canada was calculated by triangulating information from three sources (Canadian CF Registry, customised Burden of Disease survey and publicly available information). A prevalence-based, bottom-up, human capital approach was applied, and costs were categorised into four perspectives (ie, healthcare system, individual/caregiver, variable (ie, medicines) and society) and three domains (ie, direct, indirect and intangible). All costs were converted into 2021 Canadian dollars (CAD) and adjusted for inflation. The cost of cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapies was excluded.

RESULTS

The total socioeconomic burden of CF in Canada in 2021 across the four perspectives was $C414 million. Direct costs accounted for two-thirds of the total costs, with medications comprising half of all direct costs. Out-of-pocket costs to individuals and caregivers represented 18.7% of all direct costs. Indirect costs representing absenteeism accounted for one-third of the total cost.

CONCLUSION

This comprehensive cost of illness study for CF represents a community-oriented approach describing the socioeconomic burden of living with CF and serves as a benchmark for future studies.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

The estimation of health state utility values in rare diseases: do the approaches in submissions for NICE technology appraisals reflect the existing literature? A scoping review

BACKGROUND

Rare diseases negatively impact patients' quality of life, but the estimation of health state utility values (HSUVs) in research studies and cost-utility models for health technology assessment is challenging.

OBJECTIVES

This study compared the methods for estimating the HSUVs included in manufacturers' submissions of orphan drugs to the National Institute for Health and Care Excellence (NICE) with those of published studies addressing the same rare diseases to understand whether manufacturers fully exploited the existing literature in developing their economic models.

METHODS

All NICE Technology Appraisal (TA) and Highly Specialized Technologies (HST) guidance documents of non-cancer European Medicines Agency (EMA) orphan medicinal products were reviewed and compared with any published primary studies, retrieved via PubMed until November 2020, and estimating HSUVs for the same conditions addressed in manufacturers' submissions.

RESULTS

We identified 22 NICE TA/HST appraisal reports addressing 19 different rare diseases. Sixteen reports presented original HSUVs estimated using EQ-5D or Health Utility Index (n = 12), direct methods (n = 2) or mapping (n = 2), while the other six included values obtained from the literature only. In parallel, we identified 111 published studies: 86.6% used preference-based measures (mainly EQ-5D, 60.7%), 12.5% direct techniques, and 2.7% mapping. The collection of values from non-patient populations (using 'vignettes') was more frequent in manufacturers' submissions than in the literature (22.7% vs. 8.0%).

CONCLUSIONS

The agreement on methodological choices between manufacturers' submissions and published literature was only partial. More efforts should be made by manufacturers to accurately reflect the academic literature and its methodological recommendations in orphan drugs submissions.

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.

Development of the Cystic Fibrosis Questionnaire-Revised-8 Dimensions: Estimating Utilities From the Cystic Fibrosis Questionnaire-Revised

OBJECTIVES

Cystic fibrosis (CF) limits survival and negatively affects health-related quality of life (HRQOL). Cost-effectiveness analysis (CEA) may be used to make reimbursement decisions for new CF treatments; nevertheless, generic utility measures used in CEA, such as EQ-5D, are insensitive to meaningful changes in lung function and HRQOL in CF. Here we develop a new, CF disease-specific, preference-based utility measure based on the adolescent/adult version of the Cystic Fibrosis Questionnaire-Revised (CFQ-R), a widely used, CF-specific, patient-reported measure of HRQOL.

METHODS

Blinded CFQ-R data from 4 clinical trials (NCT02347657, NCT02392234, NCT01807923, and NCT01807949) were used to identify discriminating items for a classification system using psychometric (eg, factor and Rasch) analyses. Thirty-two health states were selected for a time trade-off (TTO) exercise with a representative sample of the UK general population. TTO utilities were used to estimate a preference-based scoring algorithm by regression analysis (tobit models with robust standard errors clustered on participants with censoring at -1).

RESULTS

A classification system with 8 dimensions (CFQ-R-8 dimensions; physical functioning, vitality, emotion, role functioning, breathing difficulty, cough, abdominal pain, and body image) was generated. TTO was completed by 400 participants (mean age, 47.3 years; 49.8% female). Among the regression models evaluated, the tobit heteroscedastic-ordered model was preferred, with a predicted utility range from 0.236 to 1, no logical inconsistencies, and a mean absolute error of 0.032.

CONCLUSION

The CFQ-R-8 dimensions is the first disease-specific, preference-based scoring algorithm for CF, enabling estimation of disease-specific utilities for CEA based on the well-validated and widely used CFQ-R.

Treatment Preference Among People With Cystic Fibrosis: The Importance of Reducing Treatment Burden

BACKGROUND

There is a growing consensus that the perspective of the patient should be considered in the evaluation of novel interventions.

RESEARCH QUESTION

What treatment outcomes matter to people with cystic fibrosis (CF), and what trade-offs would they make to realize these outcomes?

STUDY DESIGN AND METHODS

Adults attending a specialist CF center were invited to complete an online discrete choice experiment (DCE). The DCE required participants to evaluate hypothetical CF treatment profiles, defined by impact on lung function, pulmonary exacerbations, abdominal symptoms, life expectancy, quality of life, inhaled medicine usage, and physiotherapy requirement. Choice data were analyzed, using multinomial logit and latent class models.

RESULTS

One hundred and three people with CF completed the survey (median age, 35 years; range, 18-76 years); 52% were female; mean FEV1 % predicted, 69% [SD, 22%]). On average, an improvement in life expectancy by 10 years or more had the greatest impact on treatment preference, followed by a 15% increase in lung function. However, it was shown that people would trade substantial reductions in these key outcomes to reduce treatment time or burden. Preference profiles were not uniform across the sample: three distinct subgroups were identified, each placing markedly different importance on the relative importance of both life expectancy and lung function compared with other attributes.

INTERPRETATION

The relative importance of treatment burden to people with CF, compared with life expectancy and lung function, suggests it should be routinely captured in clinical trials as an important secondary outcome measure. When considering the patient perspective, it is important that decision-makers recognize that the values of people with CF are not homogeneous.

Mapping the FACT-G to EQ-5D-3L utility index in cancer with the Chinese values set

OBJECTIVE

The purpose of this research was to create a function for mapping the cancer-specific instrument (FACT-G) to a preference-based measure (EQ-5D-3L) utility index for health-related quality of life, with utility scores generated using the Chinese value set.

METHOD

A cross-sectional study among 243 Chinese patients with cancer was conducted through EQ-5D-3L and FACT-G questionnaires survey. The EQ-5D-3L utility index values wad predicted based on OLS, GLM, CLAD, and Tobit model regression approaches. The performance and predictive power of each model were also evaluated using r² and adj- r², MAE, RMSE, ICC, and MID. Linear equating was used to avoid regression of the OLS model to mean. The model was validated using a 10-fold cross-validation method.

RESULTS

Among all regression models for the FACT-G, the OLS 5 model predicted mean EQ-5D-3L values the best, in terms of model goodness of fit (r²= 0.6230, r²= 58.93%, MAE = 0.0448, RMSE = 0.0624). The OLS model proved to be the most accurate for the mean, and the linear equating scores were much closer to observed scores.

CONCLUSION

Our results suggest that the best algorithm for FACT-G mapping to EQ-5D-3L utility index is OLS model, based on the survey of Chinese patients with cancer.

Mapping of head and neck cancer patient concerns inventory scores on to Euroqol-Five Dimensions-Five Levels (EQ-5D-5L) health utility scores

BACKGROUND

The purpose of this paper is to map the number of concerns on the dimensions in Head and Neck Patient Concerns Inventory (PCI) on to the health utility (HU) index scores on Euroqol-Five Dimensions-Five levels {EQ-5D-5L) .

METHODS

This is a cross-sectional survey conducted in patients who have completed their treatment. Four candidate models were considered, three based on ordinary least squares regression (OLS) and one two-parts model.

RESULTS

A reduced OLS model based on 'Physical and functional', 'Treatment-related', and 'Psychological, emotional and spiritual well-being' domains was found best on the estimation sample. This was validated externally on a separate sample.

CONCLUSIONS

This is the first study that mapped a non-QOL tool to generate HU scores on EQ-5D-5L. The proposed mapping algorithm can estimate the cost-utility in economic evaluation studies when HU scores are not directly available. The algorithm will be best suited for studies in low-middle income countries.

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.

Mapping the Edmonton Symptom Assessment System-Revised: Renal to the EQ-5D-5L in patients with chronic kidney disease

PURPOSE

The Edmonton Symptom Assessment System-Revised: Renal (ESAS-r: Renal) is a disease-specific patient-reported outcome measure (PROM) that assesses symptoms common in chronic kidney disease (CKD). There is no preference-based scoring system for the ESAS-r: Renal or a mapping algorithm to predict health utility values. We aimed to develop a mapping algorithm from the ESAS-r: Renal to the Canadian EQ-5D-5L index scores.

METHODS

We used data from a multi-centre cluster randomized-controlled trial of the routine measurement and reporting of PROMs in hemodialysis units in Northern Alberta, Canada. In two arms of the trial, both the ESAS-r: Renal and the EQ-5D-5L were administered to CKD patients undergoing hemodialysis. We used data from one arm for model estimation, and data from the other for validation. We explored direct and indirect mapping models; model selection was based on statistical fit and predictive power.

RESULTS

Complete data were available for 506 patient records in the estimation sample and 242 in the validation sample. All models tended to perform better in patients with good health, and worse in those with poor health. Generalized estimating equations (GEE) and generalized linear model (GLM) on selected ESAS-r: Renal items were selected as final models as they fitted the best in estimation and validation sample.

CONCLUSION

When only ESAS-r: Renal data are available, one could use GEE and GLM to predict EQ-5D-5L index scores for use in economic evaluation. External validation on populations with different characteristics is warranted, especially where renal-specific symptoms are more prevalent.

A systematic review of patient-reported outcome measures (PROMs) in cystic fibrosis

BACKGROUND

To determine patient-reported outcome measures (PROMs) which may be suitable for incorporation into the Australian Cystic Fibrosis Data Registry (ACFDR) by identifying PROMs administered in adult and paediatric cystic fibrosis (CF) populations in the last decade.

METHODS

We searched MEDLINE, EMBASE, Scopus, CINAHL, PsycINFO and Cochrane Library databases for studies published between January 2009 and February 2019 describing the use of PROMs to measure health-related quality of life (HRQoL) in adult and paediatric patients with CF. Validation studies, observational studies and qualitative studies were included. The search was conducted on 13 February 2019. The COnsensus-based Standards for the selection of health Measurement INstruments Risk of Bias Checklist was used to assess the methodological quality of included studies.

RESULTS

Twenty-seven different PROMs were identified. The most commonly used PROMs were designed specifically for CF. Equal numbers of studies were conducted on adult (32%, n=31), paediatric (35%, n=34) and both (27%, n=26) populations. No PROMs were used within a clinical registry setting previously. The two most widely used PROMs, the Cystic Fibrosis Questionnaire-Revised (CFQ-R) and the Cystic Fibrosis Quality of Life Questionnaire (CFQoL), demonstrated good psychometric properties and acceptability in English-speaking populations.

DISCUSSION

We found that although PROMs are widely used in CF, there is a lack of reporting on the efficacy of methods and timepoints of administration. We identified the CFQ-R and CFQoL as the most suitable for incorporation in the ACFDR as they captured significant effects of CF on HRQoL and were reliable and valid in CF populations. These PROMs will be used in a further qualitative study assessing patients' with CF and clinicians' perspectives toward the acceptability and feasibility of incorporating a PROM in the ACFDR.

PROSPERO REGISTRATION NUMBER

CRD42019126931.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

'Mapping' Health State Utility Values from Non-preference-Based Measures: A Systematic Literature Review in Rare Diseases

BACKGROUND

The use of patient-reported outcome measures (PROMs) to monitor the effects of disease and treatment on patient symptomatology and daily life is increasing in rare diseases (RDs) (i.e. those affecting less than one in 2000 people); however, these instruments seldom yield health state utility values (HSUVs) for cost-utility analyses. In such a context, 'mapping' allows HSUVs to be obtained by establishing a statistical relationship between a 'source' (e.g. a disease-specific PROM) and a 'target' preference-based measure [e.g. the EuroQol-5 Dimension (EQ-5D) tool].

OBJECTIVE

This study aimed to systematically review all published studies using 'mapping' to derive HSUVs from non-preference-based measures in RDs, and identify any critical issues related to the main features of RDs, which are characterised by small, heterogeneous, and geographically dispersed patient populations.

METHODS

The following databases were searched during the first half of 2019 without time, study design, or language restrictions: MEDLINE (via PubMed), the School of Health and Related Research Health Utility Database (ScHARRHUD), and the Health Economics Research Centre (HERC) database of mapping studies (version 7.0). The keywords combined terms related to 'mapping' with Orphanet's list of RD indications (e.g. 'acromegaly') in addition to 'rare' and 'orphan'. 'Very rare' diseases (i.e. those with fewer than 1000 cases or families documented in the medical literature) were excluded from the searches. A predefined, pilot-tested extraction template (in Excel^®) was used to collect structured information from the studies.

RESULTS

Two groups of studies were identified in the review. The first group (n = 19) developed novel mapping algorithms in 13 different RDs. As a target measure, the majority used EQ-5D, and the others used the Short-Form Six-Dimension (SF-6D) and 15D; most studies adopted ordinary least squares (OLS) regression. The second group of studies (n = 9) applied previously published algorithms in non-RDs to comparable RDs, mainly in the field of cancer. The critical issues relating to 'mapping' in RDs included the availability of very few studies, the relatively high number of cancer studies, and the absence of research in paediatric RDs. Moreover, the reviewed studies recruited small samples, showed a limited overlap between RD-specific and generic PROMs, and highlighted the presence of cultural and linguistic factors influencing results in multi-country studies. Lastly, the application of existing algorithms developed in non-RDs tended to produce inaccuracies at the bottom of the EQ-5D scale, due to the greater severity of RDs.

CONCLUSIONS

More research is encouraged to develop algorithms for a broader spectrum of RDs (including those affecting young children), improve mapping study quality, test the generalisability of algorithms developed in non-RDs (e.g. HIV) to rare variants or evolutions of the same condition (e.g. AIDS wasting syndrome), and verify the robustness of results when mapped HSUVs are used in cost-utility models.

Health State Utility Data in Cystic Fibrosis: A Systematic Review

INTRODUCTION

Cystic fibrosis (CF) is a life-limiting, hereditable condition, with the highest prevalence in Europe. CF treatments have led to improvements in clinical symptoms, disease management and decelerated disease progression. However, little is known about the health state utility (HSU) associated with CF disease states, adverse events, and changes in disease severity. Although HSU data have contributed to existing health economic modelling studies, a lack of such data have been highlighted. This systematic review aims to provide a summary of HSU-related research in CF and highlight related research gaps.

METHODS

Online searches were performed in six databases and studies in any of the following categories were included: (1) estimation of HSUs in CF; (2) mapping studies between patient-reported outcome measures (PROMs) and HSUs; (3) economic evaluations on the management of CF that report primary HSU data; and (4) any CF clinical trial that reported HSU as an outcome.

RESULTS

A total of 17 studies were reviewed, of which 12 provided HSU values for specific CF populations. The remaining five articles provided HSU data that were broken down by CF relevant health states, including lung transplantations, pulmonary exacerbation (PEx) events and forced expiratory volume in 1 s (FEV₁).

CONCLUSION

Current HSU data in CF are limited and there is considerable scope for further research, both in providing HSU values for CF and in investigating methods for HSU elicitation/evaluation in CF populations.

Mapping function from FACT-B to EQ-5D-5 L using multiple modelling approaches: data from breast cancer patients in China

BACKGROUND

The Functional Assessment of Cancer Therapy-Breast (FACT-B) is the most commonly used scale for assessing quality of life in patients with breast cancer. The lack of preference-based measures limits the cost-utility of breast cancer in China. The goal of this study was to explore whether a mapping function can be established from the FACT-B to the EQ-5D-5 L when the EQ-5D health-utility index is not available.

METHODS

A cross-sectional survey of adults with breast cancer was conducted in China. All patients included in the study completed the EQ-5D-5 L and the disease-specific FACT-B questionnaire, and demographic and clinical data were also collected. The Chinese tariff value was used to calculate the EQ-5D-5 L utility scores. Five models were evaluated using three different modelling approaches: the ordinary least squares (OLS) model, the Tobit model and the two-part model (TPM). Total scores, domain scores, squared terms and interaction terms were introduced into models. The goodness of fit, signs of the estimated coefficients, and normality of prediction errors of the model were also assessed. The normality of the prediction error is determined by calculating the root mean squared error (RMSE), the mean absolute deviation (MAD), and the mean absolute error (MAE). Akaike information criteria (AIC) and Bayes information criteria (BIC) were also used to assess models and predictive performances. The OLS model was followed by simple linear equating to avoid regression to the mean.

RESULTS

The performance of the models was improved after the introduction of the squared terms and the interaction terms. The OLS model, including the squared terms and the interaction terms, performed best for mapping the EQ-5D-5 L. The explanatory power of the OLS model was 70.0%. The AIC and BIC of this model were the smallest (AIC = -705.106, BIC = -643.601). The RMSE, MAD and MAE of the OLS model, Tobit model and TPM were similar. The MAE values of the 5-fold cross-validation of the multiple models in this study were 0.07155~0.08509; meanwhile, the MAE of the TPM was the smallest, followed by that of the OLS model. The OLS regression proved to be the most accurate for the mean, and linearly equated scores were much closer to observed scores.

CONCLUSIONS

This study establishes a mapping algorithm based on the Chinese population to estimate the EQ-5D-5 L index of the FACT-B and confirms that OLS models have higher explanatory power and that TPMs have lower prediction error. Given the accuracy of the mean prediction and the simplicity of the model, we recommend using the OLS model. The algorithm can be used to calculate EQ-5D scores when EQ-5D data are not directly collected in a study.

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

Purpose

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

Methods

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

Results

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

Conclusions

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

Electronic supplementary material

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

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

BACKGROUND

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

OBJECTIVE

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

DATA SOURCES

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

STUDY SELECTION

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

DATA EXTRACTION

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

RESULTS

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

CONCLUSIONS

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

Correspondence between symptoms and preference-based health status measures in the STOP study

BACKGROUND

Pulmonary exacerbations (PEx) in cystic fibrosis (CF) patients decrease lung function, increase symptoms and reduce health-related quality of life (HRQoL). We evaluated associations between 8 symptom-based questions from the Cystic Fibrosis Respiratory Symptom Diary - Chronic Respiratory Infection Symptom Score (CFRSD-CRISS) and the 5-level EuroQOL-5 Dimensions (EQ-5D-5 L) summary score and hypothesized the CFRSD-CRISS would be well-correlated with quality-of-life measures among CF patients with PEx.

METHODS

CF patients who had CFRSD-CRISS and EQ-5D-5L measurements on the day of the initial PEx, 7 days later, and at the end of intravenous antibiotic treatment were included. We examined age-stratified (<18 versus ≥18 years old) characteristics, including the percent predicted of forced expiratory volume in 1 s (ppFEV1), CFRSD-CRISS measurements, and domains of the EQ-5D. We also calculated age-stratified Pearson correlation coefficients between the EQ-5D-5L and CFRSD-CRISS items at each of the 3 time points.

RESULTS

A total of 169 patients were analyzed. Patients reported having problems performing usual activities and with pain/discomfort on the first day of the PEx and these measures improved by the end of treatment. PpFEV1 improved in both age categories by the end of PEx treatment but was not associated with the change in summary EQ-5D-5 L over the time of PEx treatment (r-squared = 0.029). Correlations were weak (generally <0.4) between the elements of the EQ-5D-5 L versus the CFRSD-CRISS.

CONCLUSIONS

Value assessment of treatments for CF PEx will require the collection of preference-weighted measures rather than only the symptom-based questions of the CFRSD-CRISS.

The Effects of Exercise and Relaxation on Health and Wellbeing

Better management by individuals of their long-term conditions is promoted to improve health and reduce healthcare expenditure. However, there is limited evidence on the determinants and consequences of self-management activity. We investigate the determinants of two forms of self-management, exercise and relaxation, and their impact on the health and wellbeing of 3472 individuals with long-term health conditions over a 1-year period. We use simultaneous recursive trivariate models to estimate the effects of these two inputs on three health and wellbeing outcomes: the EuroQol five-dimensional (EQ-5D) score, self-assessed health and happiness. We reflect the opportunity cost of time and knowledge with employment status and education and find that employment reduces relaxation and education increases exercise. We find that neither exercise nor relaxation affects the EuroQol five-dimensional score, but exercise increases self-assessed health and relaxation increases happiness. Our findings show that individuals tailor their self-management activities to their economic constraints, with effects on different aspects of their utility. Interventions to encourage self-management should take account of heterogeneous effects and constraints. © 2017 The Authors. Health Economics Published by John Wiley & Sons, Ltd.

Mapping MOS-HIV to HUI3 and EQ-5D-3L in Patients With HIV

Objectives: The Medical Outcomes Study HIV Health Survey (MOS-HIV) is frequently used in HIV clinical trials; however, scores generated from the MOS-HIV are not suited for cost-effectiveness analyses as they do not assign utility values to health states. Our objective was to estimate and externally validate several mapping algorithms to predict Health Utilities Index Mark 3 (HUI3) and EQ-5D-3L utility values from the MOS-HIV. Methods: We developed and validated mapping algorithms using data from two HIV clinical trials. Data from the first trial (n = 367) formed the estimation data set for the HUI3 (4,610 observations) and EQ-5D-3L (4,662 observations) mapping algorithms; data from the second trial (n = 168) formed the HUI3 (1,135 observations) and EQ-5D-3L (1,152 observations) external validation data set. We compared ordinary least squares (OLS) models of increasing complexity with the more flexible two-part, beta regression, and finite mixture models. We assessed model performance using mean absolute error (MAE) and mean squared error (MSE). Results: The OLS model that used MOS-HIV dimension scores along with squared terms gave the best HUI3 predictions (mean observed 0.84; mean predicted 0.80; MAE 0.0961); the finite mixture model gave the best EQ-5D-3L predictions (mean observed 0.90; mean predicted 0.88; MAE 0.0567). All models produced higher prediction errors at the lower end of the HUI3 and EQ-5D-3L score ranges (<0.40). Conclusions: The proposed mapping algorithms can be used to predict HUI3 and EQ-5D-3L utility values from the MOS-HIV, although greater error may pose a problem in samples where a substantial proportion of patients are in poor health. These algorithms may be useful for estimating utility values from the MOS-HIV for cost-effectiveness studies when HUI3 or EQ-5D-3L data are not available.

Mapping to Estimate Health-State Utility from Non-Preference-Based Outcome Measures: An ISPOR Good Practices for Outcomes Research Task Force Report

Economic evaluation conducted in terms of cost per quality-adjusted life-year (QALY) provides information that decision makers find useful in many parts of the world. Ideally, clinical studies designed to assess the effectiveness of health technologies would include outcome measures that are directly linked to health utility to calculate QALYs. Often this does not happen, and even when it does, clinical studies may be insufficient for a cost-utility assessment. Mapping can solve this problem. It uses an additional data set to estimate the relationship between outcomes measured in clinical studies and health utility. This bridges the evidence gap between available evidence on the effect of a health technology in one metric and the requirement for decision makers to express it in a different one (QALYs). In 2014, ISPOR established a Good Practices for Outcome Research Task Force for mapping studies. This task force report provides recommendations to analysts undertaking mapping studies, those that use the results in cost-utility analysis, and those that need to critically review such studies. The recommendations cover all areas of mapping practice: the selection of data sets for the mapping estimation, model selection and performance assessment, reporting standards, and the use of results including the appropriate reflection of variability and uncertainty. This report is unique because it takes an international perspective, is comprehensive in its coverage of the aspects of mapping practice, and reflects the current state of the art.