Abstract
PURPOSE: To assess whether regression modeling can be used to predict EQ-5D-3L utility values from the Oswestry Disability Index (ODI) in low back pain (LBP) patients for use in cost-effectiveness analysis. METHODS: EQ-5D-3L utility values of LBP patients were estimated using their ODI scores as independent variables using regression analyses, while adjusting for case-mix variables. Six different models were estimated: (1) Ordinary Least Squares (OLS) regression, with total ODI score, (2) OLS, with ODI item scores as continuous variables, (3) OLS, with ODI item scores as ordinal variables, (4) Tobit model, with total ODI score, (5) Tobit model, with ODI item scores as continuous variables, and (6) Tobit model, with ODI item scores as ordinal variables. The models' performance was assessed using explained variance (R(2)) and root mean squared error (RMSE). The potential impact of using predicted instead of observed EQ-5D-3L utility values on cost-effectiveness outcomes was evaluated in two empirical cost-effectiveness analysis. RESULTS: Complete individual patient data of 18,692 low back pain patients were analyzed. All models had a more or less similar R(2) (range 45-52%) and RMSE (range 0.21-0.22). The two best performing models produced similar probabilities of cost-effectiveness for a range of willingness-to-pay (WTP) values compared to those based on the observed EQ-5D-3L values. For example, the difference in probabilities ranged from 2 to 5% at a WTP of 50,000 €/QALY gained. CONCLUSION: Results suggest that the ODI can be validly used to predict low back pain patients' EQ-5D-3L utility values and QALYs for use in cost-effectiveness analyses.