Matthijs M. Versteegh

Dutch Tariff for the Five-Level Version of EQ-5D

BACKGROUND In 2009, a new version of the EuroQol five-dimensional questionnaire (EQ-5D) was introduced with five rather than three answer levels per dimension. This instrument is known as the EQ-5D-5L. To make the EQ-5D-5L suitable for use in economic evaluations, societal values need to be attached to all 3125 health states. OBJECTIVES To derive a Dutch tariff for the EQ-5D-5L. METHODS Health state values were elicited during face-to-face interviews in a general population sample stratified for age, sex, and education, using composite time trade-off (cTTO) and a discrete choice experiment (DCE). Data were modeled using ordinary least squares and tobit regression (for cTTO) and a multinomial conditional logit model (for DCE). Model performance was evaluated on the basis of internal consistency, parsimony, goodness of fit, handling of left-censored values, and theoretical considerations. RESULTS A representative sample (N = 1003) of the Dutch population participated in the valuation study. Data of 979 and 992 respondents were included in the analysis of the cTTO and the DCE, respectively. The cTTO data were left-censored at -1. The tobit model was considered the preferred model for the tariff on the basis of its handling of the censored nature of the data, which was confirmed through comparison with the DCE data. The predicted values for the EQ-5D-5L ranged from -0.446 to 1. CONCLUSIONS This study established a Dutch tariff for the EQ-5D-5L on the basis of cTTO. The values represent the preferences of the Dutch population. The tariff can be used to estimate the impact of health care interventions on quality of life, for example, in context of economic evaluations.

Condition-Specific Preference-Based Measures: Benefit or Burden?

OBJECTIVES Some argue that generic preference-based measures (PBMs) are not sensitive to certain disease-specific improvements. To overcome this problem, new condition-specific PBMs (CS-PBMs) are being developed, but it is not yet clear how such measures compare with existing generic PBMs. METHOD We generated CS-PBMs from three condition-specific questionnaires (Health Assessment Questionnaire for arthritis, Quality of Life Questionnaire for Cancer 30 for cancer, and Multiple Sclerosis Impact Scale 29 for multiple sclerosis). First, the questionnaires were reduced in content, and then, a time trade-off study was conducted in the general public (N = 402) to obtain weights associated with the dimensions and levels of the new questionnaire. Finally, we compared utilities obtained by using the CS-PBMs with utilities obtained by using the EuroQol five-dimensional (EQ-5D) questionnaire in four data sets. RESULTS Utility values generated by the CS-PBMs were higher than those of the EQ-5D questionnaire. The Health Assessment Questionnaire-based measure for arthritis proved to be insensitive to comorbidities. Measures based on the Multiple Sclerosis Impact Scale 29 and the Quality of Life Questionnaire for Cancer 30 discriminated comorbidities and side effect equally well as the EQ-5D questionnaire and were more sensitive than the EQ-5D questionnaire for mild impairments. CONCLUSIONS The introduction of PBMs that are specific to a certain disease may have the merit of sensitivity to disease-specific effects of interventions. That gain, however, is traded off to the loss of comparability of utility values and, in some cases, insensitivity to side effects and comorbidity. The use of a CS-PBM for cost-utility analysis is warranted only under strict conditions.

Time trade-off: one methodology, different methods.

There is no scientific consensus on the optimal specification of the time trade-off (TTO) task. As a consequence, studies using TTO to value health states may share the core element of trading length of life for quality of life, but can differ considerably on many other elements. While this pluriformity in specifications advances the understanding of TTO from a methodological point of view, it also results in incomparable health state values. Health state values are applied in health technology assessments, and in that context comparability of information is desired. In this article, we discuss several alternative specifications of TTO presented in the literature. The defining elements of these specifications are identified as being either methodological, procedural or analytical in nature. Where possible, it is indicated how these elements affect health state values (i.e., upward or downward). Finally, a checklist for TTO studies is presented, which incorporates a list of choices to be made by researchers who wish to perform a TTO task. Such a checklist enables other researchers to align methodologies in order to enhance the comparability of health state values.

Mapping QLQ-C30, HAQ, and MSIS-29 on EQ-5D.

Background Responses on condition-specific instruments can be mapped on the EQ-5D to estimate utility values for economic evaluation. Mapping functions differ in predictive quality, and not all condition-specific measures are suitable for estimating EQ-5D utilities. We mapped QLQ-C30, HAQ, and MSIS-29 on the EQ-5D and compared the quality of the mapping functions with statistical and clinical indicators. Methods We used 4 data sets that included both the EQ-5D and a condition-specific measure to develop ordinary least squares regression equations. For the QLQ-C30, we used a multiple myeloma data set and a non-Hodgkin lymphoma one. An early arthritis cohort was used for the HAQ, and a cohort of patients with relapsing remitting or secondary progressive multiple sclerosis was used for the MSIS-29. We assessed the predictive quality of the mapping functions with the root mean square error (RMSE) and mean absolute error (MAE) and the ability to discriminate among relevant clinical subgroups. Pearson correlations between the condition-specific measures and items of the EQ-5D were used to determine if there is a relationship between the quality of the mapping functions and the amount of correlated content between the used measures. Results The QLQ-C30 had the highest correlation with EQ-5D items. Average %RMSE was best for the QLQ-C30 with 10.9%, 12.2% for the HAQ, and 13.6% for the MSIS-29. The mappings predicted mean EQ-5D utilities without significant differences with observed utilities and discriminated between relevant clinical groups, except for the HAQ model. Conclusions The preferred mapping functions in this study seem suitable for estimating EQ-5D utilities for economic evaluation. However, this research shows that lower correlations between instruments lead to less predictive quality. Using additional validation tests besides reporting statistical measures of error improves the assessment of predictive quality.

Patient and general public preferences for health states: A call to reconsider current guidelines

In economic evaluations of health care interventions, benefits are often expressed in terms of Quality-Adjusted Life-Years (QALYs). The QALY comprises length and quality of life into one measure which allows cross-disease comparability. The quality adjustment of the QALY is based on preferences for health states. An important normative choice is the question whose preferences for states of health we wish to capture. The answer to this question is directly related to the normative question regarding the appropriate maximand in health care decisions. Currently, preferences are commonly derived from the general public, rather than from actual patients. This choice, which can have large consequences on final outcomes of economic evaluations, has always been a topic of debate. This paper clarifies and furthers the discussion regarding the appropriate source of preferences for health state valuations, acknowledges the plurality of different perspectives, and argues that health economic guidelines could require analysis of benefit in terms of QALYs based on both patient and general public preferences.

An assessment of the external validity of mapping QLQ-C30 to EQ-5D preferences

BackgroundAlthough cancer-specific Health-related Quality-of-Life measures are commonly included in randomized clinical trials or other prospective non-randomized clinical studies, it is rare that preference-based instruments are used, which allow the calculation of a Utility weight suitable for estimating Quality-adjusted Life-Years gained.ObjectiveTo test the external validity of a previously published mapping algorithm to transform the EORTC QLQ-C30 questionnaire responses into EQ-5D-derived utilities by predicting EQ-5D utilities from QLQ-C30 scores.Study design and methodsComparative retrospective data analysis of four multicentre, prospective clinical trials in Breast, Multiple Myeloma, Non-Hodgkin Lymphoma and Non-Small-Cell Lung cancer patients with, respectively, 219, 172, 132 and 172 patients. Regression analysis of individual pairs of EQ-5D and QLQ-C30 scores.ResultsAlthough the internal predictive power of a previously published mapping equation was high, its external validity when tested on a set of unrelated external data sets in other cancers proved to underestimate both the mean and variance of the mapped EQ-5D utilities. Furthermore, it appears that the relationship between QLQ-C30 scores and EQ-5D values is not stable across the different data sets.ConclusionsValidation of the proposed algorithm in other external clinical data sets should be encouraged as well as the application of other more complex mapping methods to enhance accuracy of mapping. In the meanwhile, direct mapping from QLQ-C30 profiles to EQ-5D utilities using published algorithms should be performed with reservations.

Testing mapping algorithms of the cancer-specific EORTC QLQ-C30 onto EQ-5D in malignant mesothelioma

BackgroundIn order to estimate utilities for cancer studies where the EQ-5D was not used, the EORTC QLQ-C30 can be used to estimate EQ-5D using existing mapping algorithms. Several mapping algorithms exist for this transformation, however, algorithms tend to lose accuracy in patients in poor health states. The aim of this study was to test all existing mapping algorithms of QLQ-C30 onto EQ-5D, in a dataset of patients with malignant pleural mesothelioma, an invariably fatal malignancy where no previous mapping estimation has been published.MethodsHealth related quality of life (HRQoL) data where both the EQ-5D and QLQ-C30 were used simultaneously was obtained from the UK-based prospective observational SWAMP (South West Area Mesothelioma and Pemetrexed) trial. In the original trial 73 patients with pleural mesothelioma were offered palliative chemotherapy and their HRQoL was assessed across five time points. This data was used to test the nine available mapping algorithms found in the literature, comparing predicted against observed EQ-5D values. The ability of algorithms to predict the mean, minimise error and detect clinically significant differences was assessed.ResultsThe dataset had a total of 250 observations across 5 timepoints. The linear regression mapping algorithms tested generally performed poorly, over-estimating the predicted compared to observed EQ-5D values, especially when observed EQ-5D was below 0.5. The best performing algorithm used a response mapping method and predicted the mean EQ-5D with accuracy with an average root mean squared error of 0.17 (Standard Deviation; 0.22). This algorithm reliably discriminated between clinically distinct subgroups seen in the primary dataset.ConclusionsThis study tested mapping algorithms in a population with poor health states, where they have been previously shown to perform poorly. Further research into EQ-5D estimation should be directed at response mapping methods given its superior performance in this study.

From Good to Better: New Dutch Guidelines for Economic Evaluations in Healthcare.

Many countries have national guidelines for performing economic evaluations in healthcare. These guidelines should ensure the comparability and quality of such evaluations, which should facilitate making well informed policy decisions regarding reimbursement of interventions. Given the developments in both the methodology and policy context of economic evaluation of healthcare interventions, these guidelines require periodical revision. Recently, the Dutch National Health Care Institute issued new guidance for economic evaluations in healthcare [1]. The new guidelines update and replace three separately published previous guidelines: those for pharmacoeconomic evaluation (latest version 2006), outcomes research (latest version 2008) as well as the Dutch costing manual (latest version 2010). In this editorial, we highlight the distinguishing features of the new Dutch guidelines. Moreover, we highlight which developments, in our opinion, are desirable in coming updates, but are still in development or controversial. 2 Unchanged Features

Cost Effectiveness of the Angiotensin Receptor Neprilysin Inhibitor Sacubitril/Valsartan for Patients with Chronic Heart Failure and Reduced Ejection Fraction in the Netherlands: A Country Adaptation Analysis Under the Former and Current Dutch Pharmacoeconomic Guidelines

OBJECTIVES To describe the adaptation of a global health economic model to determine whether treatment with the angiotensin receptor neprilysin inhibitor LCZ696 is cost effective compared with the angiotensin-converting enzyme inhibitor enalapril in adult patients with chronic heart failure with reduced left ventricular ejection fraction in the Netherlands; and to explore the effect of performing the cost-effectiveness analyses according to the new pharmacoeconomic Dutch guidelines (updated during the submission process of LCZ696), which require a value-of-information analysis and the inclusion of indirect medical costs of life-years gained. METHODS We adapted a UK model to reflect the societal perspective in the Netherlands by including travel expenses, productivity loss, informal care costs, and indirect medical costs during the life-years gained and performed a preliminary value-of-information analysis. RESULTS The incremental cost-effectiveness ratio obtained was €17,600 per quality-adjusted life-year (QALY) gained. This was robust to changes in most structural assumptions and across different subgroups of patients. Probability sensitivity analysis results showed that the probability that LCZ696 is cost-effective at a €50,000 per QALY threshold is 99.8%, with a population expected value of perfect information of €297,128. On including indirect medical costs of life-years gained, the incremental cost-effectiveness ratio was €26,491 per QALY gained, and LCZ696 was 99.46% cost effective at €50,000 per QALY, with a population expected value of perfect information of €2,849,647. CONCLUSIONS LCZ696 is cost effective compared with enalapril under the former and current Dutch guidelines. However, the (monetary) consequences of making a wrong decision were considerably different in both scenarios.

Which factors may determine the necessary and feasible type of effectiveness evidence? A mixed methods approach to develop an instrument to help coverage decision-makers

Objectives Reimbursement decisions require evidence of effectiveness and, in general, a blinded randomised controlled trial (RCT) is the preferred study design to provide it. However, there are situations where a cohort study, or even patient series, can be deemed acceptable. The aim of this study was to develop an instrument that first examines which study characteristics of a blinded RCT are necessary, and then, if particular characteristics are considered necessary, examines whether these characteristics are feasible. Design We retrospectively studied 22 interventions from 20 reimbursement reports concerning medical specialist care made by the Dutch National Health Care Institute (ZIN) to identify any factors that influenced the necessity and feasibility of blinded RCTs, and their constituent study characteristics, that is, blinding, randomisation and a control group. A literature review was performed to identify additional factors. Additional expertise was included by interviewing eight experts in epidemiology, medicine and ethics. The resulting instrument was called the FIT instrument (Feasible Information Trajectory), and was prospectively validated using three consecutive reimbursement reports. Results (Blinded) RCT evidence was lacking in 5 of 11 positive reimbursement decisions and 3 of 11 negative decisions. In the reimbursement reports, we found no empirical evidence supporting situations where a blinded RCT is unnecessary. The literature also revealed few arguments against the necessity of a blinded RCT. In contrast, many factors influencing the feasibility of randomisation, a control group and blinding, were found in the reimbursement reports and the literature; for example, when a patient population is too small or when an intervention is common practice, randomisation will be hindered. Conclusions Policy regarding the necessity and feasibility of different types of evidence of effectiveness would benefit from systematic guidance. The FIT instrument has the potential to support transparent, reproducible and well-founded decisions on appropriate evidence of effectiveness in medical specialist care.