title: Mapping the 25-item National Eye Institute Visual Functioning Questionnaire (NEI VFQ-25) to EQ-5D utility scores.
abstract: OBJECTIVE
  To develop a mapping algorithm for the estimation of EQ-5D-based utility scores from observed 25-item National Eye Institute Visual Functioning Questionnaire (NEI VFQ-25) scores, a disease-specific, patient-reported outcome measure used in several retinal disorders to evaluate vision-specific functioning.
  
  
  METHODS
  The dataset comprised 951 paired EQ-5D/NEI VFQ-25 observations from 344 patients in RESTORE, a 12-month, randomized, double-blind trial in individuals with visual impairment due to diabetic macular edema. EQ-5D index scores (utilities) were calculated based on the UK tariff. We evaluated 11 models using predictor sets based on the NEI VFQ-25 subscales to estimate utility as a function of NEI VFQ-25 score, based on four modeling techniques. Model performance was assessed by 10-fold cross-validation comparing root mean squared error (RMSE), mean absolute error (MAE) and correlation with EQ-5D score (Pearson and Spearman correlation coefficients).
  
  
  RESULTS
  Mapping results were similar across all techniques and predictor sets. The reverse two-part generalized estimating equation model used fewest predictors and had the best predictive performance (RMSE 0.200, MAE 0.140). Predicted and original EQ-5D values were not strongly correlated (squared Spearman correlation coefficient, 0.34).
  
  
  CONCLUSIONS
  Although mapping disease-specific instruments to EQ-5D utilities is a preferred method by some reimbursement bodies, finding an appropriate mapping equation is not straightforward. In this study, mapping NEI VFQ-25 scores to EQ-5D utilities provided low predictive power, independent of the modeling methodology applied, suggesting an inability of the EQ-5D to discriminate vision-related activities, and highlighting that mapping exercises may lead to inaccurate utility values that do not represent patients' preferences.
authors.affiliation: Adelphi Real World , Bollington , UK and.
authors.forename: Stephen
authors.initials: S
authors.lastname: Kay
authors.forename: Alberto
authors.initials: A
authors.lastname: Ferreira
mesh_terms: D000465:Algorithms; D003930:Diabetic Retinopathy / Q000503:physiopathology*; D005260:Female; D006304:Health Status; D006801:Humans; D008269:Macular Edema / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D054554:National Eye Institute (U.S.); D011788:Quality of Life / Q000523:psychology; D016032:Randomized Controlled Trials as Topic; D018434:Sickness Impact Profile; D011795:Surveys and Questionnaires; D014481:United States; D014792:Visual Acuity / Q000502:physiology*