To determine whether Assessment of Quality of Life (AQoL) utility scores can be reliably estimated from Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores in people with hip and knee joint disease (arthritis or osteoarthritis).
WOMAC and AQoL data were analysed from 219 people recruited for a national population-based study. Generalised linear models were used to estimate AQoL utility scores based on WOMAC total and subscale scores and personal characteristics. Goodness of fit was assessed for each model, and plots of prediction errors versus actual AQoL utility scores were used to gauge bias.
Each model closely predicted the average AQoL utility score for the overall sample (actual mean AQoL 0.64, range of predicted means 0.63-0.64; actual median AQoL 0.71, range of predicted medians 0.68-0.69). No clear preferred model was identified, and overall, the models predicted 40-46% of the variance in AQoL utility scores. The WOMAC function subscale model performed similarly to the total score model. The models functioned best at the mid-range of AQoL scores, with greater bias observed for extreme scores. Inaccuracies in individual-level estimates and low/high health-related quality of life (HRQoL) subgroup estimates were evident.
Reliable overall group-level estimates were produced, supporting the application of these techniques at a population level. Using WOMAC scores to predict individual AQoL utility scores is not recommended, and the models may produce inaccurate estimates in studies targeting patients with low/high HRQoL. Where pain and stiffness data are unavailable, the WOMAC function subscale can be used to generate a reasonable utility estimate.