Published in:
Open Access 01-12-2010 | Research
Exploring the validity of estimating EQ-5D and SF-6D utility values from the health assessment questionnaire in patients with inflammatory arthritis
Published in: Health and Quality of Life Outcomes | Issue 1/2010
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Background
Utility scores are used to estimate Quality Adjusted Life Years (QALYs), applied in determining the cost-effectiveness of health care interventions. In studies where no preference based measures are collected, indirect methods have been developed to estimate utilities from clinical instruments. The aim of this study was to evaluate a published method of estimating the EuroQol-5D (EQ-5D) and Short Form-6D (SF-6D) (preference based) utility scores from the Health Assessment Questionnaire (HAQ) in patients with inflammatory arthritis.
Methods
Data were used from 3 cohorts of patients with: early inflammatory arthritis (<10 weeks duration); established (>5 years duration) stable rheumatoid arthritis (RA); and RA being treated with anti-TNF therapy. Patients completed the EQ-5D, SF-6D and HAQ at baseline and a follow-up assessment. EQ-5D and SF-6D scores were predicted from the HAQ using a published method. Differences between predicted and observed EQ-5D and SF-6D scores were assessed using the paired t-test and linear regression.
Results
Predicted utility scores were generally higher than observed scores (range of differences: EQ-5D 0.01 - 0.06; SF-6D 0.05 - 0.10). Change between predicted values of the EQ-5D and SF-6D corresponded well with observed change in patients with established RA. Change in predicted SF-6D scores was, however, less than half of that in observed values (p < 0.001) in patients with more active disease. Predicted EQ-5D scores underestimated change in cohorts of patients with more active disease.
Conclusion
Predicted utility scores overestimated baseline values but underestimated change. Predicting utility values from the HAQ will therefore likely underestimate the QALYs of interventions, particularly for patients with active disease. We recommend the inclusion of at least one preference based measure in future clinical studies.