CODAGLIO 2.0: Combining clinical trial datasets in glioma patients to answer clinically relevant questions about patients’ health related quality of life

The CODAGLIO 2.0 project is an extension of the CODAGLIO project in which we combined clinical and health-related quality of life (HRQoL) data of available randomized controlled trials in glioma patients (n=6084) to answer clinically relevant questions. The project is a collaboration between the EORTC Quality of Life Group, the Brain Tumour Group and the Quality of Life Department, and resulted in five publications in highly ranked journals.

Since the start of the project, we have worked on obtaining approval from the principal investigators or pharmaceutical companies to include the data collected in clinical trials in our database. We also finalized the data sharing process as well as the setting up the statistical analysis plans for all five clinically relevant questions.

The agreements are now in place, and the data has been sent from EORTC to LUMC. The researcher is currently harmonizing and cleaning all the data for a comprehensive and accurate data analysis.

For the remaining time of the project, we will conduct the statistical analyses and write up the manuscripts.

Patients with a glioma, the most prevalent primary malignant brain tumour, demonstrate a high symptom burden and experience many disease-specific symptoms such as cognitive dysfunction and seizures. Although patients receive treatment with surgery, radiotherapy and chemotherapy, current treatment options are not curative. Therefore, the quality of survival is for these patients at least as important as the duration of survival. Because primary brain tumours are relatively rare, and the number of trials that included assessments of health-related quality of life (HRQoL) are limited, it is essential to combine these datasets. By combining these datasets we will be able to answer clinically relevant questions that could not be answered until now. For example, we will study if there are differences in HRQoL trajectories between males and females, and between patients with different tumor characteristics.