Objectives: To develop algorithms for a conversion of disease-specific quality-of-life into health state values for morbidly obese patients before or after bariatric surgery.
Methods: A total of 893 patients were enrolled in a prospective cross-sectional multicenter study. In addition to demographic and clinical data, health-related quality-of-life (HRQoL) data were collected using the disease-specific Moorehead-Ardelt II questionnaire (MA-II) and two generic questionnaires, the EuroQoL-5D (EQ-5D) and the Short Form-6D (SF-6D). Multiple regression models were constructed to predict EQ-5D- and SF-6D-based utility values from MA-II scores and additional demographic variables.
Results: The mean body mass index was 39.4, and 591 patients (66%) had already undergone surgery. The average EQ-5D and SF-6D scores were 0.830 and 0.699. The MA-IIwas correlated to both utility measures (Spearman's r = 0.677 and 0.741). Goodness-of-fit was highest (R(2) = 0.55 in the validation sample) for the following item-based transformation algorithm: utility (MA-II-based) = 0.4293 + (0.0336 x MA1) + (0.0071 x MA2) + (0.0053 x MA3) + (0.0107 x MA4) + (0.0001 x MA5). This EQ-5D-based mapping algorithm outperformed a similar SF-6D-based algorithm in terms of mean absolute percentage error (P = 0.045).
Conclusions: Because the mapping algorithm estimated utilities with only minor errors, it appears to be a valid method for calculating health state values in cost-utility analyses. The algorithm will help to define the role of bariatric surgery in morbid obesity.