Missing not at random in end of life care studies : multiple imputation and sensitivity analysis on data from the ACTION study

Background: Missing data are common in end-of-life care studies, but there is still relatively little exploration of which is the best method to deal with them, and, in particular, if the missing at random (MAR) assumption is valid or missing not at random (MNAR) mechanisms should be assumed. In this paper we investigated this issue through a sensitivity analysis within the ACTION study, a multicenter cluster randomized controlled trial testing advance care planning in patients with advanced lung or colorectal cancer. Methods: Multiple imputation procedures under MAR and MNAR assumptions were implemented. Possible violation of the MAR assumption was addressed with reference to variables measuring quality of life and symptoms. The MNAR model assumed that patients with worse health were more likely to have missing questionnaires, making a distinction between single missing items, which were assumed to satisfy the MAR assumption, and missing values due to completely missing questionnaire for which a MNAR mechanism was hypothesized. We explored the sensitivity to possible departures from MAR on gender differences between key indicators and on simple correlations. Results: Up to 39% of follow-up data were missing. Results under MAR reflected that missingness was related to poorer health status. Correlations between variables, although very small, changed according to the imputation method, as well as the differences in scores by gender, indicating a certain sensitivity of the results to the violation of the MAR assumption. Conclusions: The findings confirmed the importance of undertaking this kind of analysis in end-of-life care studies

General population normative data for the EORTC QLQ-C30 health-related quality of life questionnaire based on 15,386 persons across 13 European countries, Canada and the Unites States

OBJECTIVE: The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 health-related quality of life questionnaire is one of the most widely used cancer-specific health-related quality of life questionnaires worldwide. General population norm data can facilitate the interpretation of QLQ-C30 data obtained from cancer patients. This study aimed at systematically collecting norm data from the general population to develop European QLQ-C30 norm scores and to generate comparable norm data for individual countries in Europe and North America. METHODS: We collected QLQ-C30 data from the general population across 11 European Union (EU) countries, Russia, Turkey, Canada and United States (n \u3e /= 1000/country). Representative samples were stratified by sex and age groups (18-39, 40-49, 50-59, 60-69 and \u3e /= 70 years). After applying weights based on the United Nations population distribution statistics, we calculated QLQ-C30 domain scores to generate a \u27European QLQ-C30 Norm\u27 based on the EU countries. Further, we calculated QLQ-C30 norm scores for all 15 individual countries. RESULTS: A total of 15,386 respondents completed the online survey. For the EU sample, most QLQ-C30 domains showed differences by sex/age, with men scoring somewhat better health than women, while age effects varied across domains. Substantially larger differences were seen in inter-country comparisons, with Austrian and Dutch respondents reporting consistently better health compared with British and Polish respondents. CONCLUSIONS: This study is the first to systematically collect EORTC QLQ-C30 general population norm data across Europe and North America applying a consistent data collection method across 15 countries. These new norm data facilitate valid intra-country as well as inter-country comparisons and QLQ-C30 score interpretation