Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

PURPOSE: To assess different mapping methods for the estimation of a group's mean EQ-5D score based on responses to the Oxford hip score (OHS) questionnaire. METHODS: Four models were considered: a) linear regression using total OHS as a continuous regressor; b) linear regression employing responses to the twelve OHS questions as categorical predictors; c) two-part approach combining logistic and linear regression; and d) response mapping. The models were internally validated on the estimation data set, which included OHS and EQ-5D scores for total hip replacements, both before and six months after procedure for 1,759 operations. An external validation was also performed. RESULTS: All models estimated the mean EQ-5D score within 0.005 of an observed health-state utility estimate, ordinary least squares (OLS) continuous being the most accurate and OLS categorical the most consistent. Age, gender and deprivation did not improve the models. More accurate estimations at the individual level were achieved for higher scores of observed OHS and EQ-5D. CONCLUSION: Based on these results, when EQ-5D scores are not available, answers to the OHS questionnaire can be used to estimate a group's mean EQ-5D with a high degree of accuracy.

Original publication

DOI

10.1007/s11136-012-0174-y

Type

Journal article

Journal

Qual life res

Publication Date

04/2013

Volume

22

Pages

665 - 675

Keywords

Adult, Algorithms, Arthroplasty, Replacement, Hip, Female, Humans, Least-Squares Analysis, Longitudinal Studies, Male, Predictive Value of Tests, Quality of Life, Regression Analysis, Reproducibility of Results, Surveys and Questionnaires