Causal Inference for radiotherapy

This research project aims to apply causal inference in the complex context of radiotherapy. The objective is to understand the mechanisms underlying the phenomena observed during and after treatment, to deeply analyse the cause-and-effect relationships between the variables involved. Each objective will be guided by a specific, predefined causal question, which will be addressed through the adoption and development of various methodologies. 

In the initial phase, the project will focus on building a causal inference model to predict the development of radiotherapy-induced side effects. The risk of toxicity varies significantly among patients, reflecting the multifactorial nature of this phenomenon. Key determinants include the cumulative dose delivered to healthy tissues, the individual's genetic background, pre-existing clinical conditions, and the concomitant use of systemic oncological therapies. 

Causal inference enables the integration of patient-specific clinical, imaging, genetic, and transcriptomic data, enhancing the ability to identify the causal effect of radiation doses and other patient-specific features on the normal tissue functional damage. 

A suitable population (with available detailed information and long-term follow-up) will allow the development of causal inference models, which can support the design of personalized treatment plans, contribute to the mitigation of adverse effects, and ultimately improve clinical outcomes and patients’ long-term quality of life.