Estimating utility data from clinical indicators for patients with stable angina

Eur J Health Econ. 2005 Dec;6(4):347-53. doi: 10.1007/s10198-005-0309-y.

Abstract

This study estimated a model from which data routinely collected in clinical trials of angina patients can be mapped to a utility scale and used to estimate quality-adjusted life years (QALYs). Patients with stable angina attending four cardiac out-patient clinics in the UK were included in the study. Data collected included information on patients' health-related quality of life (HRQL) using the EQ-5D, and severity of angina symptoms using two cardiac-specific measures [Breathlessness Grade and Canadian Cardiovascular Society (CCS) classification of angina]. Regression analysis was used to predict EQ-5D index values from the data. Data were obtained from 510 patients. For CCS grades, mean EQ-5D scores ranged from 0.36 (95% confidence interval 0.25-0.48) for grade 4 to 0.81 (0.77-0.85) for grade 0, and for breathlessness grades, EQ-5D scores ranged from 0.31 (0.06-0.55) for grade 0 to 0.84 (0.79-0.88) for grade 5. The final model used data on CCS grades, breathlessness grades, and patients' current medications to predict EQ-5D scores. The model had an R2 value of 0.37, and predictions for less severe angina were considered more reliable than the estimates for severe angina. In the absence of utility data collected as part of a clinical trial it is possible to map HRQL utility data from samples of patients with similar characteristics to those in the original trial. The uncertainty surrounding the estimates should be considered when using the results to estimate QALYs for purposes of economic evaluation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Angina Pectoris / economics
  • Angina Pectoris / physiopathology*
  • Angina Pectoris / therapy*
  • Attitude to Health*
  • Convalescence
  • Dyspnea
  • Humans
  • Interviews as Topic
  • Middle Aged
  • Multivariate Analysis
  • Outcome Assessment, Health Care / methods*
  • Policy Making
  • Quality-Adjusted Life Years*
  • Regression Analysis
  • Severity of Illness Index
  • Sickness Impact Profile*
  • United Kingdom