The added value of propensity score matching when using health-related quality of life reference data



Direct comparisons of health-related quality of life (HRQoL) outcomes between non-randomized groups might be biased, as outcomes are confounded by imbalance in pre-treatment patient characteristics. Such bias can be reduced by adjusting on observed covariates. This is the setting of HRQoL comparisons with reference data, where age and gender adjustment is commonly used for this purpose. However, other observed covariates can be used to lessen this bias and yield more precise estimates. The objective of this study is to show that more accurate HRQoL comparisons with reference data can be obtained, accounting for few covariates in addition to age and gender by a propensity score matching approach. Copyright © 2013 John Wiley & Sons, Ltd.