Level of agreement between patient-reported EQ-5D responses and EQ-5D responses mapped from the SF-12 in an injury population

Abstract

BackgroundComparing health-related quality of life (HRQL) outcomes between studies is difficult due to the wide variety of instruments used. Comparing study outcomes and facilitating pooled data analyses requires valid “crosswalks” between HRQL instruments. Algorithms exist to map 12-item Short Form Health Survey (SF-12) responses to EQ-5D item responses and preference weights, but none have been validated in populations where disability is prevalent, such as injury.MethodsData were extracted from the Validating and Improving injury Burden Estimates Study (Injury-VIBES) for 10,166 adult, hospitalized trauma patients, with both the three-level EQ-5D (EQ-5D-3L) and SF-12 data responses at six and 12-months postinjury. Agreement between actual (patient-reported) and estimated (mapped from SF-12) EQ-5D-3L item responses and preference weights was assessed using Kappa, Prevalence-Adjusted Bias-Adjusted Kappa statistics and Bland-Altman plots.ResultsModerate agreement was observed for usual activities, pain/discomfort, and anxiety/depression. Agreement was substantial for mobility and self-care items. The mean differences in preference weights were -0.024 and -0.012 at six and 12 months (p < 0.001), respectively. The Bland-Altman plot limits of agreement were large compared to the range of valid preference weight values (-0.56 to 1.00). Estimated EQ-5D-3L responses under-reported disability for all items except pain/discomfort.ConclusionsCaution should be taken when using EQ-5D-3L responses mapped from the SF-12 to describe patient outcomes or when undertaking economic evaluation, due to the underestimation of disability associated with mapped values. The findings from this study could be used to adjust expected EQ-5D-3L preference weights when estimated from SF-12 item responses when combining data from studies that use either instrument.Electronic supplementary materialThe online version of this article (doi:10.1186/s12963-015-0047-z) contains supplementary material, which is available to authorized users.

Disability weights based on patient-reported data from a multinational injury cohort

“…The three-level EQ-5D questionnaire was used for the Australian cases from 2009 onwards and for all the injury cases included in the participating British, Dutch and New Zealand data sets. For all the other cases we considered, the recorded responses to the questions in the 12-item Short Form Health Survey 24 had to be translated into EQ-5D responses 24 . EQ-5D responses are used to calculate a preference score for each respondent.…”

Recovery of health-related quality of life after burn injuries: An individual participant data meta-analysis

“…Transformation of HRQL data was needed in order to combine the different datasets, therefore we applied the algorithm of Gray et al [21] to map the SF-12 to the EQ-5D-3L and the algorithm of van Hout et al [23] to map the EQ-5D-5L to the 3L version. An earlier study showed that the quality of these estimated scores based on the algorithm of Gray et al ranged from moderate to good for the different dimensions [56], though this algorithm is the only one estimating EQ-5D dimension scores from SF-12 scores. Except for the dimension pain/discomfort, all estimated dimension scores reported less problems compared to directly assessed EQ-5D outcomes [56].…”

“…An earlier study showed that the quality of these estimated scores based on the algorithm of Gray et al ranged from moderate to good for the different dimensions [56], though this algorithm is the only one estimating EQ-5D dimension scores from SF-12 scores. Except for the dimension pain/discomfort, all estimated dimension scores reported less problems compared to directly assessed EQ-5D outcomes [56]. In total, 33% of all of our outcomes were mapped by this algorithm.…”

Improved and standardized method for assessing years lived with disability after burns and its application to estimate the non-fatal burden of disease of burn injuries in Australia, New Zealand and the Netherlands

“…A limitation is the transformation of HRQL data to derive one dataset. We applied the algorithm of Gray et al [29] to transform SF-36 data to EQ-5D data which has shown to have moderate to good ability to estimate EQ-5D scores [54] and this method was used before for the purpose of deriving disability weights [39]. Another limitation is that incidence rates of the different registries included different case definitions; data from BRANZ included patients that were admitted for at least 24 h to a burn centre or had surgery; data from the Dutch Burn Repository R3 included patients admitted for at least two hours to a specialized burn centre.…”