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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.

Original publication




Journal article


Statistics in medicine

Publication Date





5119 - 5132


Italian Group for Adult Hematologic Diseases (GIMEMA) Data Center and Health Outcomes Research Unit, Rome, Italy.


Humans, Blindness, Questionnaires, Bias (Epidemiology), Quality of Life, Computer Simulation, Female, Male, Propensity Score