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

Abstract

Purpose 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. Methods 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). Results OLS was the best-performing model of the three compared, as this produced the lowest RMSE and MAE, and the highest R 2 . Conclusions 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.

Mapping the disease-specific LupusQoL to the SF-6D

“…These issues, however, are mainly directed at the suitability of OLS for predicting EQ-5D utility scores due its bi-or often tri-modal distribution [29] and the well documented ceiling effect of the instrument [30,31], which typically results in a concentration of observations at 1. A number of studies have found OLS to be appropriate when mapping to the SF-6D, often finding this method to demonstrate superior performance to alternatives such as Tobit, CLAD, two-part models and response mapping methods in this context [32][33][34]. The distribution of the SF-6D scores in both the estimation and validation data sets were therefore tested for normality in order to assess the appropriateness of OLS to model this particular relationship.…”

The MAPS Reporting Statement for Studies Mapping onto Generic Preference-Based Outcome Measures: Explanation and Elaboration

“…Although the MAE, MSE, and RMSE are criteria for evaluating model performance, we present the models that have the lowest RMSE. This is because the RMSE is measured in the same units as the data, is representative of the size of a 'typical' error, and is more sensitive than other measures to the occasional large error'' [33].…”

Repeatability of contrast sensitivity testing in patients with age-related macular degeneration, glaucoma, and cataract

“…CS has become more important for quality of life assessments, which have been receiving increase attention in recent years (37)(38)(39) . CS is involved with differentiating low-contrast objects, such as human faces, and recognizing movement (37,40) .…”

“…Keywords: Macular degeneration; Contrast sensitivity; Glaucoma; Age effect; Repro ducibility of results , glaucoma, catarata e AMD foram, respectivamente, ICC 0,87; 0,90; 0,76; 0,69, e COR 0,24; 0,20; 0,38; 0,25 …”

“…Conclusion: In subjects with good visual acuity, the FVA system is useful for evaluating CS and demonstrates good repeatability, as shown by ICC and COR. Because there is no ceiling effect, this system is beneficial for evaluation of early changes in CS, particularly in patients with glaucoma or AMD.Keywords: Macular degeneration; Contrast sensitivity; Glaucoma; Age effect; Repro ducibility of results , glaucoma, catarata e AMD foram, respectivamente, ICC 0,87; 0,90; 0,76; 0,69, e COR 0,24; 0,20; 0,38; 0,25 …”