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

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.

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.

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.

Improving Interpretation of Evidence Relating to Quality of Life in Health Technology Assessments of Rare Disease Treatments

Rare diseases are often severe, debilitating, life-limiting conditions, many of which occur in childhood. These complex conditions have a wide range of clinical manifestations that have a substantial impact on the lives of patients, carers and families and often produce heterogeneous clinical outcomes. Therefore, the evaluation of quality-of-life (QoL) impacts is important. In health technology assessment (HTA), patient-reported outcome measures (PROMs) and/or health state utility values (HSUVs) are used to determine QoL impacts of new treatments, but their use in rare diseases is challenging due to small and heterogeneous populations and limited disease knowledge. This paper describes challenges associated with the use of patient-reported outcomes (PROs)/HSUVs to evaluate QoL in HTA of rare disease treatments (RDTs) and identifies five recommendations to ensure appropriate interpretation of QoL impacts. These were derived from mixed methods research (literature reviews, appraisal document analyses, appraisal committee observations and interviews) examining the use of PROs/HSUVs in HTA of RDTs. They highlight that HTAs of RDTs must (1) understand the QoL impacts of the disease and of treatments; (2) critically assess PRO data, recognising the nuances in development and administration of PROMs/HSUVs, considering what is feasible and what matters most to the patient population; (3) recognise that lack of significant effect on a PRO does not imply no QoL benefit; (4) use different forms of evidence to understand QoL impacts, such as patient input; and (5) provide methodological guidance to capture QoL impacts on patients/carers.

Family Spillover Effects: Are Economic Evaluations Misrepresenting the Value of Healthcare Interventions to Society?

The societal impacts of health interventions are seldom incorporated into health economic evaluations, including the impact that illness can have on informal or unpaid caregivers and other family members (i.e., "family spillover effects"). Previous research has demonstrated that by excluding family spillover effects, the value of health interventions may be underestimated on average. In this commentary, we discuss how the inclusion of spillover effects influences how we value interventions and, given the extent to which caregiver/family effects are largely not captured or known, propose ways in which these data could be more systematically collected or estimated and used by researchers. These recommendations include prioritizing data collection alongside clinical trials and patient registries, engaging expert opinion panels, and developing mapping algorithms for estimating caregiver/family utility values from non-preference-based caregiver health-related quality-of-life measures and/or from patient preference-based measures.

[Establishment of Mono-scaled Benefit/Risk Analysis of HPV Vaccine]

Decisions concerning approval of human papillomavirus (HPV) vaccines and their use are based on expert evaluation of the vaccines. However, the quantitative differences between vaccine benefits and risks are difficult for non-experts to understand. In this study, we developed a new method to calculate the benefits and risks of the HPV vaccines using disability-adjusted life year (DALY) as the mono-scaled weight for various benefits and risks relevant to the vaccines. We evaluated benefits as a gain of DALY values for cervical cancer and risks as the loss of DALY values for various adverse events by the vaccination. To calculate the loss of DALY values, we integrated all adverse events in the International Classification of Diseases chapters. The novel method reflected the men-women ratio of this epidemiological disease to a certain extent. Among the vaccinated women, 111,372 and 477,190 received a bivalent and quadrivalent vaccine, respectively. The DALY rate of cervical cancer was 148.7. The calculated benefit for the bivalent and quadrivalent vaccines was 149.1 and 638.8, respectively, and set as the theoretical maximum. The risk was calculated as 129.3 and 49.6 in the bivalent and quadrivalent vaccines, respectively. Since HPV vaccines prevent several other cancers, the benefit of the vaccination extends beyond the risk according to this new method.

Feasibility of Deriving Health State Utilities in Mycosis Fungoides Cutaneous T-Cell Lymphoma Using Mapping Algorithms

BACKGROUND

A prospective, observational, US-based study (PROVe) used three questionnaires (Pruritus-VAS, Skindex-29, MF/SS-CTCL QoL) to assess quality of life in patients diagnosed with mycosis fungoides cutaneous T-cell lymphoma (MF-CTCL); however, none of these studies was provided with a preference-based algorithm yielding health state utility values (HSUVs).

OBJECTIVE

This study aimed to assess the feasibility of deriving HSUVs from published mapping algorithms by comparing mapped utilities with the HSUVs reported in the MF-CTCL literature.

METHODS

We searched 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) to identify any studies mapping Pruritus-VAS, Skindex-29, or MF/SS-CTCL QoL to a preference-based instrument (ideally, EQ-5D), and any studies assessing HSUVs in MF-CTCL. Two algorithms from a recent study that mapped Pruritus-VAS onto EQ-5D-3L were applied to the PROVe patient-level data. We performed multiple imputation to handle missing VAS data, calculated average mapped utilities in the whole sample, and compared them with relevant factors using the t-test and one-way analysis of variance (ANOVA).

RESULTS

Overall, 298 patients provided 1441 Pruritus-VAS scores over a 2-year follow-up (1-21 visits per patient). The average mapped HSUVs ranged between 0.950 and 0.999 depending on the algorithm applied and imputation of missing data. In subgroup analysis, significant differences (p < 0.05) were observed according to age, race, and cancer stage. A few previous studies that collected HSUVs from MF-CTCL patients reported mean values of between 0.82 and 0.87 using time trade-off, 0.63 and 0.83 using EQ-5D, and 0.51 and 0.69 using the HUI3.

CONCLUSIONS

The HSUVs derived by applying published mapping algorithms to PROVe Pruritus-VAS data appeared largely overestimated if compared with the existing literature. More research is required to understand the applicability of existing mapping algorithms and to develop new mapping algorithms in MF-CTCL.

Assessing the value of orphan drugs using conventional cost-effectiveness analysis: Is it fit for purpose?

Conventional cost-effectiveness analysis—i.e., assessing pharmaceuticals through a cost per quality-adjusted life year (QALY) framework—originated from a societal commitment to maximize population health given limited resources. This "extra-welfarist" approach has produced pricing and reimbursement systems that are not well- aligned with the unique considerations of orphan drugs. This framework has been slow to evolve along with our increased understanding of the impact of rare diseases, which in turn has complicated the assessment of orphan drugs meant to treat rare diseases. Herein, we (i) discuss the limitations of conventional cost-effectiveness analysis as applied to assessing access to, as well as the pricing and reimbursement of, orphan drugs, (ii) critically appraise alternative and supplemental approaches, and (iii) offer insights on plausible steps forward.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Mapping the Haem-A-QoL to the EQ-5D-5L in patients with hemophilia

OBJECTIVE

This study's objective was to develop an algorithm that mapping the Haem-A-QoL scores to EQ-5D-5L utility scores in patients with hemophilia in China.

METHODS

A national sample of 862 patients with hemophilia completed both the EQ-5D-5L and Haem-A-QoL instruments. Eight regression models were selected to develop the mapping algorithm, they were: the ordinary least squares, general linear regression, Tobit regression, censored least absolute deviation, mixture beta regression, adjusted limited dependent variable mixture, the two-part, and robust MM-estimator model. Root mean squared error (RMSE), mean absolute error (MAE), and R-square (R²) calculated using the tenfold cross-validation and random sample validation methods were used to assess the predictive ability of the models.

RESULTS

Based on RMSE, MAE, and R², the mixture beta regression model with selected Haem-A-QoL subscale scores as the predicted variables showed the best performance.

CONCLUSIONS

Our mapping algorithm bolsters the calculation of QALYs while conducting an economic evaluation of hemophilia-related interventions when only Haem-A-QoL data are available. The external validity of the algorithm should be further assessed in the other populations.

Implementing Outcomes-Based Managed Entry Agreements for Rare Disease Treatments: Nusinersen and Tisagenlecleucel

BACKGROUND AND OBJECTIVE

Enthusiasm for the use of outcomes-based managed entry agreements (OBMEAs) to manage uncertainties apparent at the time of appraisal/pricing and reimbursement of new medicines has waned over the past decade, as challenges in establishment, implementation and re-appraisal have been identified. With the recent advent of innovative treatments for rare diseases that have uncertainties in the clinical evidence base, but which could meet a high unmet need, there has been renewed interest in the potential of OBMEAs. The objective of this research was to review the implementation of OBMEAs for two case studies across countries in the European Union, Australia and Canada, to identify good practices that could inform development of tools to support implementation of OBMEAs.

METHODS

To investigate how OBMEAs are being implemented with rare disease treatments, we collected information from health technology assessment/payer experts in countries that had implemented OBMEAs for either nusinersen in spinal muscular atrophy or tisagenlecleucel in two cancer indications. Operational characteristics of the OBMEAs that were publicly available were documented. Then, the experts discussed issues in implementing these OBMEAs and specific approaches taken to overcome challenges.

RESULTS

The OBMEAs identified were based on individual outcomes to ensure appropriate use, manage continuation of treatment and in two cases linked to payment schedules, or they were population based, coverage with evidence development. For nusinersen, population-based OBMEAs are documented in Belgium, England and the Netherlands and individual-based schemes in Bulgaria, Ireland, Italy and Lithuania. For tisagenlecleucel, there were population-based schemes in Australia, Belgium, England and France and individual-based schemes in Italy and Spain. Comparison of the OBMEA constructs showed some clear published frameworks and clarity of the uncertainties to be addressed that were similar across countries. Agreements were generally made between the marketing authorisation holder and the payer with involvement of expert physicians. Only England and the Netherlands involved patients. Italy used its long-established, national, web-based, treatment-specific data collection system linked to reimbursement and Spain has just developed such a national treatment registry system. Other countries relied on a variety of data collection systems (including clinical registries) and administrative data. Durations of agreements varied for these treatments as did processes for interim reporting. The processes to ensure data quality, completeness and sufficiency for re-analysis after coverage with evidence development were not always clear, neither were analysis plans.

CONCLUSIONS

These case studies have shown that important information about the constructs of OBMEAs for rare disease treatments are publicly available, and for some jurisdictions, interim reports of progress. Outcomes-based managed entry agreements can play an important role not only in reimbursement, but also in treatment optimisation. However, they are complex to implement and should be the exception and not the rule. More recent OBMEAs have developed document covenants among stakeholders or electronic systems to provide assurances about data sufficiency. For coverage with evidence development, there is an opportunity for greater collaboration among jurisdictions to share processes, develop common data collection agreements, and share interim and final reports. The establishment of an international public portal to host such reports would be particularly valuable for rare disease treatments.

Implications of response shift for micro-, meso-, and macro-level healthcare decision-making using results of patient-reported outcome measures

PURPOSE

Results of patient-reported outcome measures (PROMs) are increasingly used to inform healthcare decision-making. Research has shown that response shift can impact PROM results. As part of an international collaboration, our goal is to provide a framework regarding the implications of response shift at the level of patient care (micro), healthcare institute (meso), and healthcare policy (macro).

METHODS

Empirical evidence of response shift that can influence patients' self-reported health and preferences provided the foundation for development of the framework. Measurement validity theory, hermeneutic philosophy, and micro-, meso-, and macro-level healthcare decision-making informed our theoretical analysis.

RESULTS

At the micro-level, patients' self-reported health needs to be interpreted via dialogue with the clinician to avoid misinterpretation of PROM data due to response shift. It is also important to consider the potential impact of response shift on study results, when these are used to support decisions. At the meso-level, individual-level data should be examined for response shift before aggregating PROM data for decision-making related to quality improvement, performance monitoring, and accreditation. At the macro-level, critical reflection on the conceptualization of health is required to know whether response shift needs to be controlled for when PROM data are used to inform healthcare coverage.

CONCLUSION

Given empirical evidence of response shift, there is a critical need for guidelines and knowledge translation to avoid potential misinterpretations of PROM results and consequential biases in decision-making. Our framework with guiding questions provides a structure for developing strategies to address potential impacts of response shift at micro-, meso-, and macro-levels.

The Use of Patient-Reported Outcome Measures in Rare Diseases and Implications for Health Technology Assessment

Background

Patient-reported outcome measures (PROMs) are used in health technology assessment (HTA) to measure patient experiences with disease and treatment, allowing a deeper understanding of treatment impact beyond clinical endpoints. Developing and administering PROMs for rare diseases poses unique challenges because of small patient populations, disease heterogeneity, lack of natural history knowledge, and short-term studies.

Objective

This research aims to identify key factors to consider when using different types of PROMs in HTA for rare disease treatments (RDTs).

Methods

A scoping review of scientific and grey literature was conducted, with no date or publication type restrictions. Information on the advantages of and the challenges and potential solutions when using different types of PROMs for RDTs, including psychometric properties, was extracted and synthesized.

Results

Of 79 records from PubMed, 32 were included, plus 12 records from the grey literature. PROMs for rare diseases face potential data collection and psychometric challenges resulting from small patient populations and disease heterogeneity. Generic PROMs are comparable across diseases but not sensitive to disease specificities. Disease-specific instruments are sensitive but do not exist for many rare diseases and rarely provide the utility values required by some HTA bodies. Creating new PROMs is time and resource intensive. Potential solutions include pooling data (multi-site/international data collection), using computer-assisted technology, or using generic and disease-specific PROMs in a complementary way.

Conclusions

PROMs are relevant in HTA for RDTs but pose a number of difficulties. A deeper understanding of the potential advantages of and the challenges and potential solutions for each can help manage these difficulties.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40271-020-00493-w.

The estimation of health state utility values in rare diseases: overview of existing techniques

There are several techniques for estimating health state utility values, each of which presents pros and cons in the context of rare diseases (RDs). Direct approaches (e.g. standard gamble and time trade-off) may be too demanding for patients with RDs, since most of them affect young children or cause cognitive impairment. The alternatives are using "vignettes" that describe hypothetical health states for the general public, which may not reflect the heterogeneous manifestations of RDs, or multi-attribute utility instruments (i.e. indirect techniques), such as EQ-5D, which may be less sensitive in capturing the specificities of RDs. The "rule of rescue" approach is a promising alternative in RDs, since it prioritizes identifiable patients with life-threatening or disabling conditions. However, it raises measurement challenges and ethical issues. Furthermore, the literature reports on relevant implications of choosing a technique over others for health technology assessment, which should be considered in relation to individual RDs.