The use of international datasets in radiation oncology is becoming increasingly important in improving treatment outcome and advancing the field. By pooling data from multiple centers and countries, researchers can gain a more comprehensive understanding of the factors that affect treatment outcomes and develop more effective treatment strategies. However, working with international datasets presents unique challenges, such as ensuring data quality, consistency, and privacy, as well as addressing institutional differences. This talk briefly illustrates these concepts based on the example of an international study for radiotherapy treatment of cervical cancer (EMBRACE).
An initial barrier when collecting international data is the need to establish common data definitions and protocols. This involves identifying and resolving discrepancies in the way data is collected, recorded, and reported, as well as developing standardized forms and procedures for data entry and analysis. In radiation oncology, the epitome of this challenge are naming conventions for targets and organs at risk, which can be hard to control even within individual centers. While accruing data, centralized data collection can help to overcome this issue. Another important challenge is dealing with data privacy and security, as well as ethical considerations, such as obtaining informed consent from patients.
When working with international datasets, it's important to consider the potential impact of unobserved bias on the results of the analysis, i.e., systematic differences between centers. One way to assess and account for unobserved bias in these datasets is by using random effect models. Random effects models allow taking into account the clustered structure of the data when estimating the effects of different variables on an outcome of interest. This type of model allows to account for both observed and unobserved sources of variation between centers by including a random effect at the center level in the model, leading to more robust estimation of center-specific effects.
Finally, international research does not happen in isolation. Because an international dataset is likely used by multiple working groups, it should also be noted that effective communication and organization are key to successful collaboration in this area. Regular meetings or communications between collaborators should be implemented to discuss progress, address any issues, and plan future direction for the research. In addition, there are several tools that can be used to collaborate on a dataset in an international setting. Cloud storage platforms allow researchers to securely store and share data files with others. Furthermore, version control systems such as Git can be used to keep track of changes and updates to the dataset.
In conclusion, working with international datasets in radiotherapy can provide valuable insights into the factors that affect treatment outcomes and help to improve patient care. However, it also requires careful planning, coordination, and collaboration among researchers to harness its full potential.