Estimating quality-adjusted life years from patient-reported visual functioning

Abstract

Glaucoma is an important disease, the impacts of which on vision have been shown to have implications for patients' health-related quality of life (HRQoL). The primary aim of this study is to estimate a mapping algorithm to predict EQ-5D and SF-6D utility values based on the vision-specific measure, the 25-item Visual Functioning Questionnaire (VFQ-25), as well as the clinical measures of visual function, that is, integrated visual field, visual acuity, and contrast sensitivity. Ordinary least squares (OLS), Tobit, and censored least absolute deviations were compared using data taken from the Moorfields Eye Hospital in London, to assess mapping functions to predict the EQ-5D and SF-6D from the VFQ-25, and tests of visual function. These models were compared using root mean square error (RMSE), R(2), and mean absolute error (MAE). OLS was the best-performing model of the three compared, as this produced the lowest RMSE and MAE, and the highest R(2). The models provided initial algorithms to convert the VFQ-25 to the EQ-5D and SF-6D. Further analysis would be needed to validate the models or algorithms.