Estimating utility values for health states of type 2 diabetic patients using the EQ-5D (UKPDS 62)

Med Decis Making. Jul-Aug 2002;22(4):340-9. doi: 10.1177/0272989X0202200412.

Abstract

Purpose: The aim of this study was to analyze quality-of-life data from the United Kingdom Prospective Diabetes Study (UKPDS) to estimate the impact of diabetes-related complications on utility-based measures of quality of life.

Methods: The EuroQol EQ-5D instrument was administered in 1996 to 3667 UKPDS patients with type 2 diabetes. Tobit and censored least absolute deviations (CLAD) regression analysis based on data from the 3192 respondents was used to estimate the impact of major complications on (1) the visual analog scale (VAS) and (2) the EQ-5D utilities derived from population-based time trade-off values.

Results: Using the tobit model, the effect on tariff values was as follows: myocardial infarction = -0.055 (95% confidence interval [CI] = -0.067, -0.042), blindness in 1 eye = -0.074 (95% CI= -0.124, -0.052), ischemic heart disease = -0.090 (95% CI = -0.126, -0.054), heartfailure = -0.108 (95% CI= -0.169, -0.048), stroke = -0.164 (95% CI = -0.222, -0.105), and amputation = -0.280 (95% CI = -0.389, -0.170). The impact on the VAS scores was smaller, but the ranking was identical. Estimates of these effects, based on the nonparametric CLAD estimator, are also reported and compared.

Conclusion: These results demonstrate the magnitude of the impact of 6 complications on utility-based measures of quality of life, which can be used to estimate the outcome of interventions that reduce these diabetes-related complications.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.
  • Validation Study

MeSH terms

  • Adolescent
  • Child
  • Diabetes Mellitus, Type 2 / complications*
  • Diabetes Mellitus, Type 2 / psychology
  • Female
  • Humans
  • Male
  • Outcome Assessment, Health Care
  • Pain Measurement
  • Prospective Studies
  • Quality of Life / psychology*
  • Regression Analysis
  • Sickness Impact Profile*
  • Surveys and Questionnaires
  • United Kingdom