Purpose To use published literature to estimate large, medium, and small differences in quality of life (QOL) data from the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). Methods An innovative method combining systematic review of published studies, expert opinions, and meta-analysis was used to estimate large, medium, and small differences for QLQ-C30 scores. Published mean data were identified from the literature. Differences (contrasts) between groups (eg, between treatment groups, age groups, and performance status groups) were reviewed by 34 experts in QOL measurement and cancer treatment. The experts, blinded to actual QOL results, were asked to predict these differences. A large difference was defined as one representing unequivocal clinical relevance. A medium difference was defined as likely to be clinically relevant but to a lesser extent. A small difference was one believed to be subtle but nevertheless clinically relevant. A trivial difference was used to describe circumstances unlikely to have any clinical relevance. Actual QOL results were combined using meta-analytic techniques to estimate differences corresponding to small, medium, or large effects. Results Nine hundred eleven articles were identified, leading to 152 relevant articles (2,217 contrasts) being reviewed by at least two experts. Resulting estimates from the meta-analysis varied depending on the subscale. Thus, the recommended minimum to detect medium differences ranges from 9 (cognitive functioning) to 19 points (role functioning). Conclusion Guidelines for the size of effects are provided for the QLQ-C30 subscales. These guidelines can be used for sample size calculations for clinical trials and can also be used to aid interpretation of differences in QLQ-C30 scores.
The Quality of Life Questionnaire Core 30 (QLQ-C30) and Functional Assessment of Cancer-General (FACT-G) differ in responsiveness, relative efficiency, and therefore required sample size
