Valuations of epilepsy-specific health states: a comparison of patients with epilepsy and the general population

doi:10.1016/j.yebeh.2014.04.011

Epilepsy & Behavior

Volume 36, July 2014, Pages 12-17

https://doi.org/10.1016/j.yebeh.2014.04.011 Get rights and content

Highlights

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First study to compare general population and epilepsy patient health state values
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Values are comparable across the populations.
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NEWQOL-6D general population values may represent the views of people with epilepsy.

Abstract

Aims

Utility values that can be used in the economic evaluation of treatments for epilepsy can be elicited from the general population and the patient population, but it is unclear how the health state values differ. The aim of this study is to compare the preferences of the general population and a sample of people with epilepsy for health states described by the NEWQOL-6D QALY measure.

Methods

The Time Trade Off preference elicitation technique was used to value eight NEWQOL-6D health states. The general population sample was recruited and interviewed in their homes, and the sample with epilepsy was recruited and interviewed in an epilepsy service in North West England. Descriptive analysis and regression modeling were used to compare health state values across the populations.

Results

A sample of 70 people with epilepsy and a sample of 60 members of the general population were included. The populations differed across a range of background characteristics, but there were limited differences between the health state values. Patients provided significantly higher (better) values for the most severe health state described by the NEWQOL-6D (p < 0.01) and nonsignificant higher values for states with intermediate severity. The general population health state value was only higher for the best health state described by the NEWQOL-6D.

Conclusions

The similarities in the patient and general population values for NEWQOL-6D health states suggest that the use of the general population utility weights for the estimation of QALYs in the economic evaluation of epilepsy interventions is appropriate and largely representative of patient preferences.

Introduction

Cost utility analysis (CUA) can be used to assess the cost effectiveness of treatments for epilepsy, with the quality adjusted life year (QALY) as the outcome measure. The QALY combines the health-related quality of life (HRQL) and time spent in a health state as a single figure to allow for comparisons across interventions and conditions. The quality aspect of the QALY is a figure anchored on a 0 (dead) to 1 (full health) scale described as the utility score. Utility values can be generated using many different measures, although the National Institute of Health and Care Excellence (NICE) recommends the use of EQ-5D [1] which has five dimensions of health (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) scored according to one of three levels of severity (no problems, some or moderate problems, extreme problems). Utility scores for each of the 243 health states are derived from a tariff of values based on direct valuations of the general population using the Time Trade Off (TTO) method [2].

The generic nature of EQ-5D means that it is used across a wide range of patient groups, but the validity of the instrument has been questioned in epilepsy [3], [4], [5], [6]. In response to these concerns, the authors developed an epilepsy-specific QALY measure from the NEWQOL instrument, the NEWQOL-6D [7]. The NEWQOL-6D (Fig. 1) assesses health across six dimensions (worry about attacks, depression, memory, concentration, control, stigma), each with four response levels, therefore describing 4096 (4⁶) possible health states. To produce the utility values for use in the estimation of QALYs, a selection of health states was valued by a representative sample of the UK general population using the TTO preference elicitation technique. This produced a utility value set with a range from 0.341 (for the worst state) to 0.954 (for the best state).

Preferences for health states described by QALY measures that are used in the generation of utility values can be gained from both general population and patient samples. General population values are preferred by agencies such as NICE as it is argued that, where health care is publically funded, general public values should inform decision-making [8]. Evidence regarding differences in preferences for health states elicited from general population and patient samples is mixed, with evidence both for [9] and against [10] differences. This means that the choice of population may affect the values obtained and the subsequent economic evaluations carried out, but potential differences must be considered across different conditions. Values may differ across samples due to differences in interpretation and experience of living in and/or adapting to a particular health state or aspect of the state. Respondents are asked to imagine living in the health state presented, and the subsequent valuation is influenced by the individual's experience of their own or other people's health [11]. Values may differ based on whether the health state described relates to a physical or mental health condition, and this may be an important feature in epilepsy. However, no evidence regarding the valuation of epilepsy-specific health states across different populations is available.

The aim of this study was, therefore, to compare health state preferences from general population and patient samples using NEWQOL-6D health states. The aim was to understand how different populations perceive epilepsy-specific health states, and whether this impacts on the equivalence of health state values across the samples that could be used in the economic evaluation of epilepsy-specific interventions.

Section snippets

The Time Trade Off technique

Time Trade Off is used widely to value health states and was used to value NEWQOL-6D to promote comparability with EQ-5D, which was valued using a similar protocol [2]. This TTO protocol requires respondents to trade off a variable amount of years (x) in full health to avoid a fixed amount of ten years in a hypothetical health state described by the classification system. The trade-off follows an iterative process, until respondents are indifferent between the choices, where the value for the

Respondents

Sixty members of the general population valued the eight NEWQOL-6D health states. The description of the recruitment and response rates of the overall general population sample is available in Mulhern et al. [9]. In total, one hundred and three (n = 103) patients with epilepsy agreed to speak with a member of the Liverpool research team (DS) to discuss the project in greater detail. Thirty-three (n = 33) declined subsequently to take part in the study. The final patient sample, therefore, included

Discussion

We have reported the results of the first comparison of valuations by the general population and patients with epilepsy of epilepsy-specific health states and found limited differences between the values provided. This means that utility values derived from the general population for use in the estimation of QALYs may also generally represent the views of people with epilepsy. However, there may be differences at the more severe end of the scale, where general population respondents

Conflict of interest

The authors do not have any conflicts of interest.

Acknowledgments

This project was funded by Epilepsy Research UK — Grant number: P0903.

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EuroQOL-5D-3L does not adequately map quality-of-life deterioration in severely affected patients with epilepsy
2022, Epilepsy and Behavior
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A shorter form of the QOLIE-31, the QOLIE-10, is available since 1996 and has been used as a screening questionnaire to assess HRQOL in patients with epilepsy based on 10 out of the initial 31 items [11]. Other detailed HRQOL metrics, such as the NEWQOL-6D, have been created and validated but are only occasionally used in clinical practice [12–14]. As the QOLIE-31 is time-consuming, several other more generic scores are used to assess HROQL, such as the Short Form 36 (SF-36) (36 items), the reduced SF-12 (12 items), and the EuroQOL 5-dimension (EQ-5D) [7].
The steadily increasing impact of health-related quality of life (HRQOL) on reasonable diagnostic and therapeutic decisions makes the correct mapping of HRQOL indispensable in modern epileptology. The aim of this study was to address the reliability of the often-used generic HRQOL screening questionnaire EuroQOL 5-dimension, 3-level (EQ-5D-3L) by comparing its normalized index value (calculated via the time trade-off method) and visual analog scale (VAS) to the gold standard of the extensive Quality of Life in Epilepsy Inventory (QOLIE-31). QOLIE-10 scores were compared with the extensive QOLIE-31 and EQ-5D-3L TTO.
We conducted a retrospective analysis of a monocentric study of 184 patients with epilepsy. Bivariate Spearman correlation analysis and Fisher’s r-to-z transformation were used to compare the strengths of correlations of EQ-5D-3L, QOLIE-10 and QOLIE-31 with different epilepsy-specific domains (disease severity, drug interactions, emotional well-being, stigmatization, seizure-related anxiety, cognitive impairment).
The different metrics of EQ-5D-3L, QOLIE-10 and QOLIE-31 showed moderate to very strong intra- and inter-metric correlations for overall HRQOL. Quality of Life in Epilepsy Inventory-31 VAS and EQ-5D-3L VAS did not show any significantly different strengths of correlations with respect to the domains studied. In contrast, the correlation strength of the normalized EQ-5D-3L index value differed significantly from the QOLIE-31 T-score for several domains, for example, for drug-related adverse events, neuropsychological deficits, symptoms of depression and seizure worry. In seizure-free patients, EQ-5D-3L VAS and EQ-5D-3L index values correlated significantly less with the domain of “cognitive impairment” than the QOLIE-31 T-score. In patients without relevant neuropsychological deficits, the strengths of correlations with the assessed domains did not differ significantly between EQ-5D-3L metrics and the QOLIE-31 T-score. The HRQOL mapping probability of QOLIE-10 was inferior to QOLIE-31 and comparable to EQ-5D-3L regarding the analyzed domains.
In contrast to the EQ-5D-3L VAS, EQ-5D-3L index values do not adequately map health-related quality of life in severely affected patients with epilepsy and therefore should not be used as screening tools. The QOLIE-31 T-score remains the gold standard for HRQOL assessment in patients with epilepsy.
What Difference Does It Make? A Comparison of Health State Preferences Elicited From the General Population and From People With Multiple Sclerosis
2020, Value in Health
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Studies focusing on mental health18-21 or dementia22 health states, however, have found that patients provided lower HSVs compared with the general population, and some research indicates that the relative importance of particular dimensions of HRQL may differ.12,18,23 Furthermore, differences between patient and public values can vary according to the severity of the health state, with patients providing lower values for the mildest health states and higher values for the most severe states,6,19-22,24 resulting in “valuation compression” (ie, a narrower range of HSVs).25 Taken together, these differences can have a sufficient impact on the results of cost-effectiveness studies to influence resource allocation decisions, and the direction and nature of their effects can vary.3
A major debate in the quality-adjusted life-year (QALY) literature concerns whose preferences should be used to estimate health state values (HSVs) and to calculate QALYs.
This study explores differences between public and patient values for multiple sclerosis (MS) health states, described using an MS-specific classification system (Multiple Sclerosis Impact Scale–8 Dimensions [MSIS-8D]).
The MSIS-8D is an existing preference-based measure of health-related quality of life in MS, which has 2 tariffs of HSVs, based on the preferences of a representative sample of the UK general population (n = 1702) and of people with MS living in the United Kingdom (n = 1635), elicited using the time trade-off technique. Here, we explore differences between HSVs by sample type, using descriptive statistics and multivariate regression methods.
Overall, the survey of people with MS produced significantly higher HSVs; estimated values ranged from 0.079 to 0.883 for the general population survey and from 0.138 to 0.894 for the MS survey. Differences in HSVs were more pronounced for severe health states. The difference between patient and public values varied across the dimensions of the MSIS-8D. People with MS placed greater importance on cognition than the general population, leading to lower HSVs when impairment was at a worse level; the reverse was true for the daily activities, fatigue, and depression dimensions.
We identified significant differences in HSVs by sample type. Using patient rather than public values may influence the results of economic evaluations, depending on the dimensions of health-related quality of life affected by the intervention being assessed, and may therefore have important consequences for reimbursement decisions.
Comparing Generic and Condition-Specific Preference-Based Measures in Epilepsy: EQ-5D-3L and NEWQOL-6D
2017, Value in Health
There is debate about the psychometric characteristics of the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L) for use in epilepsy. In response to the concerns, an epilepsy-specific preference-based measure (NEWQOL-6D) was developed. The psychometric characteristics of the NEWQOL-6D, however, have not been assessed.
To investigate the validity and responsiveness of the EQ-5D-3L and the Quality of Life in Newly Diagnosed Epilepsy Instrument-six dimensions (NEWQOL-6D) for use in the assessment of treatments for newly diagnosed focal epilepsy.
The analysis used data from the Standard And New Antiepileptic Drugs trial including patients with focal epilepsy. We assessed convergent validity using correlations, and known-group validity across different epilepsy and general health severity indicators using analysis of variance and effect sizes. The responsiveness of the measures to change over time was assessed using standardized response means. We also assessed agreement between the measures.
There was some level of convergence and agreement between the measures in terms of utility score but divergence in the concepts measured by the descriptive systems. Both instruments displayed known-group validity, with significant differences between severity groups, and generally slightly larger effect sizes for the NEWQOL-6D across the epilepsy-specific indicators. Evidence for responsiveness was less clear, with small to moderate standardized response means demonstrating different levels of change across different indicators.
There was an overall tendency for the NEWQOL-6D to better reflect differences across groups, but this does not translate into large absolute utility differences. Both the EQ-5D-3L and the NEWQOL-6D show some evidence of validity for providing utility values for economic evaluations in newly diagnosed focal epilepsy.
PatientsLikeMe® Online Epilepsy Community: Patient characteristics and predictors of poor health-related quality of life
2016, Epilepsy and Behavior
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In part, this could be explained by the different recall periods of these two instruments and also illustrates the limitation of using generic measures in the context of epilepsy. Limitations of the EQ-5D-3L have been described elsewhere [42,43] and have led to the development of the first epilepsy-specific utility measure, the Quality of Life in Newly Diagnosed Epilepsy Instrument—6D (NEWQOL-6D) [44,45], which covers HRQoL dimensions more relevant to epilepsy, such as worry about seizures, depression and social functioning, memory problems, cognitive problems, control of condition, and perceived stigma. Indeed, the dimensions covered by NEWQOL-6D were each identified in this research as being relevant to patients with epilepsy.
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Data recorded (January 2010–November 2011) by Epilepsy Community members, with an epilepsy diagnosis and who reported > 1 seizure, included the following: sociodemographic and disease characteristics, treatments, symptoms, side effects perceived as medication-related, seizure occurrence, and standardized questionnaires (Quality of Life in Epilepsy Inventory [QOLIE-31/P], EuroQoL 5-Dimensions Scale, 3 Levels [EQ-5D-3L], and Hospital Anxiety and Depression Scale [HADS]). Univariate and multivariate logistic regressions were conducted to identify predictors of poor HRQoL.
During the study period, the Epilepsy Community comprised 3073 patients, of whom 71.5% were female, had a mean age of 37.8 years, and had a mean epilepsy duration of 17.7 years. The most frequently reported moderate/severe symptoms (n = 2135) included memory problems (60.2%), problems concentrating (53.8%), and fatigue (50.0%). Medication-related side effects (n = 639) included somnolence (23.2%), fatigue (17.2%), and memory impairment (13.8%). The QOLIE-31/P scores (n = 1121) were significantly worse in patients who experienced a recent seizure. For QOLIE-31/P, highly predictive factors for poor HRQoL included the following: mild/moderate problems concentrating, depression, memory problems, treatment side effects, occurrence of tonic–clonic seizures, and epilepsy duration ≤ 1 year. For EQ-5D-3L, highly predictive factors for poor HRQoL included the following: pain, depression, and comorbidities. Patients on newer AEDs were less likely to report poor HRQoL (QOLIE-31/P).
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