title: Mapping utility scores from a disease-specific quality-of-life measure in bariatric surgery patients.
abstract: OBJECTIVE
  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.
authors.affiliation: Institut für Forschung in der Operativen Medizin, University of Witten/Herdecke, Cologne, Germany. stefan.sauerland@ifom-uniwh.de
authors.forename: Stefan
authors.initials: S
authors.lastname: Sauerland
authors.forename: Sylvia
authors.initials: S
authors.lastname: Weiner
authors.forename: Karin
authors.initials: K
authors.lastname: Dolezalova
authors.forename: Luigi
authors.initials: L
authors.lastname: Angrisani
authors.forename: Carlos Masdevall
authors.initials: CM
authors.lastname: Noguera
authors.forename: Manuel
authors.initials: M
authors.lastname: García-Caballero
authors.forename: Frédéric
authors.initials: F
authors.lastname: Rupprecht
authors.forename: Marc
authors.initials: M
authors.lastname: Immenroth
mesh_terms: D000328:Adult; D000465:Algorithms; D050110:Bariatric Surgery / Q000523:psychology*; D015992:Body Mass Index; D003430:Cross-Sectional Studies; D005260:Female; D006305:Health Status Indicators; D006306:Health Surveys; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D009767:Obesity, Morbid / Q000523:psychology / Q000601:surgery*; D011446:Prospective Studies; D011594:Psychometrics; D011788:Quality of Life / Q000523:psychology*; D019057:Quality-Adjusted Life Years; D012044:Regression Analysis; D012720:Severity of Illness Index; D018434:Sickness Impact Profile; D018709:Statistics, Nonparametric; D011795:Surveys and Questionnaires