Comparing responsiveness of the EQ-5D-5L, EQ-5D-3L and EQ VAS in stroke patients

Aims: To date, evidence to support the construct validity of the EQ-5D-5L has primarily focused on cross-sectional data. The aims of this study were to examine the responsiveness of EQ-5D-5L in patients with stroke and to compare it with responsiveness of EQ-5D-3L and visual analogue scale (EQ VAS). Methods: We performed an observational longitudinal cohort study of patients with stroke. At 1 week and 4 months post-stroke, patients were assessed with modified Rankin Scale (mRS) and Barthel Index (BI) and were administered the EQ-5D-5L and EQ-5D-3L, including the EQ VAS. The EQ-5D-5L index scores were derived using the crosswalk methodology developed by the EuroQol Group. We classified patients according to two external criteria, based on mRS or BI, into 3 categories: ‘improvement,’ ‘stable’ or ‘deterioration’. We assessed the responsiveness of each measure in each patient subgroup using: effect size (ES), standardized response mean (SRM), F-statistic, relative efficiency and area under the receiver operating characteristic curve. Results: A total of 112 patients (52 % females; mean age 70.6 years; 93 % ischemic stroke) completed all the instruments at both occasions. In subjects with clinical improvement, EQ-5D-5L was consistently responsive, showing moderate ES (0.51–0.71) and moderate to large SRM (0.69–0.86). In general, EQ-5D-3L index appeared to be more responsive (ES 0.63–0.82; SRM 0.77–1.06) and EQ VAS less responsive (ES 0.51–0.65; SRM 0.59–0.69) than EQ-5D-5L index. Conclusions: The EQ-5D-5L index, based on the crosswalk value set, seems to be appropriately responsive in patients with stroke, 4 months after disease onset. As far as EQ-5D-5L index is scored according to crosswalk approach, the EQ-5D-3L index appears to be more responsive in stroke population

Identification, review, and use of health state utilities in cost-effectiveness models: An ISPOR good practices for outcomes research task force report

Cost-effectiveness models that present results in terms of cost per quality-adjusted life-year for health technologies are used to inform policy decisions in many parts of the world. Health state utilities (HSUs) are required to calculate the quality-adjusted life-years. Even when clinical studies assessing the effectiveness of health technologies collect data on HSUs to populate a cost-effectiveness model, which rarely happens, analysts typically need to identify at least some additional HSUs from alternative sources. When possible, HSUs are identified by a systematic review of the literature, but, again, this rarely happens. In 2014, ISPOR established a Good Practices for Outcome Research Task Force to address the use of HSUs in cost-effectiveness models. This task force report provides recommendations for researchers who identify, review, and synthesize HSUs for use in cost-effectiveness models; analysts who use the results in models; and reviewers who critically appraise the suitability and validity of the HSUs selected for use in models. The associated Minimum Reporting Standards of Systematic Review of Utilities for Cost-Effectiveness checklist created by the task force provides criteria to judge the appropriateness of the HSUs selected for use in cost-effectiveness models and is suitable for use in different international settings

Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: A multi-country study

Purpose: The aim of this study was to assess the measurement properties of the 5-level classification system of the EQ-5D (5L), in comparison with the 3-level EQ-5D (3L). Methods: Participants (n = 3,919) from six countries, including eight patient groups with chronic conditions (

United States Valuation of EQ-5D-5L Health States Using an International Protocol

Objective To derive a US-based value set for the EQ-5D-5L questionnaire using an international, standardized protocol developed by the EuroQol Group. Methods Respondents from the US adult population were quota-sampled on the basis of age, sex, ethnicity, and race. Trained interviewers guided participants in completing composite time trade-off (cTTO) and discrete choice experiment (DCE) tasks using the EuroQol Valuation Technology software and routine quality control measures. Data were modeled using a Tobit model for cTTO data, a mixed logit model for DCE data, and a hybrid model that combined cTTO and DCE data. Model performance was compared on the basis of logical ordering of coefficients, statistical significance, parsimony, and theoretical considerations. Results Of 1134 respondents, 1062, 1099, and 1102 respondents provided useable cTTO, DCE, and cTTO or DCE responses, respectively, on the basis of quality control criteria and interviewer judgment. Respondent demographic characteristics and health status were similar to the 2015 US Census. The Tobit model was selected as the preferred model to generate the value set. Values ranged from −0.573 (55 555) to 1 (11 111), with 20% of all predicted health states scores less than 0 (ie, worse than dead). Conclusions A societal value set for the EQ-5D-5L was developed that can be used for economic evaluations and decision making in US health systems. The internationally established, standardized protocol used to develop this US-based value set was recommended by the EuroQol Group and can facilitate cross-country comparisons

Erratum to: Using a discrete choice experiment to value the QLU-C10D: feasibility and sensitivity to presentation format.

© 2017, Springer International Publishing Switzerland. In this article by R. Norman et al., the article by M. T. King et al. is cited as Reference 10, as ‘Submitted’ and ‘Under Review’. However, the Reference 10 should appear with year, volume and page numbers as: King et al., Quality of Life Research (2016); 25(3):625-636. Also an error was found in Table 1 in the reported wording of the Physical Functioning item. The error and correction are described below. The error was limited to Table 1. The survey described in the paper used the correct labelling, and the validity of the analysis is therefore unaffected by the error