معرفی
Marta Spreafico serves as Assistant Professor in Medical Statistics at Leiden University's Mathematical Institute and Researcher at the Leiden University Medical Center's Department of Biomedical Data Sciences. She is a core member of the Data Analysis and Survival for Personalised Oncology group and SIG Health Data Science initiative, driving translational research at the intersection of statistical methodology and pediatric oncology.
Her educational foundation includes dual PhDs: a cum laude PhD in Mathematical Models and Methods in Engineering from Politecnico di Milano (2022) and a PhD in Mathematics from Leiden University (2022). She also holds an MSc (2018) and BSc (2015) in Mathematical Engineering from Politecnico di Milano, with thesis work focused on statistical modeling in heart failure and cancer contexts.
- PhD cum Laude, Mathematical Models and Methods in Engineering, Politecnico di Milano (2022)
- PhD, Mathematics, Leiden University (2022)
- MSc, Mathematical Engineering - Applied Statistics, Politecnico di Milano (2018)
- BSc, Mathematical Engineering, Politecnico di Milano (2015)
Dr. Spreafico's research pioneers dual-track innovation: developing mathematically rigorous methodologies in survival analysis and causal inference while directly applying them to pediatric cancer treatment challenges. Her work specifically targets modeling chemotherapy-induced toxicity accumulation and dose-intensity effects in Ewing sarcoma and osteosarcoma, leveraging real-world cancer trial data and administrative databases to create personalized therapy prediction tools that account for time-varying clinical complexities.
Her scientific recognition includes the Cum Laude PhD Award from Politecnico di Milano (2022) and a Bone Cancer Research Trust Skills Development Grant (2025). These honors reflect her methodological rigor and clinical impact in oncology statistics.
As Principal Investigator of the €935k KWF-funded INDICATES project (2025-2028), she develops clinical prediction tools for Ewing sarcoma therapy individualization. Concurrently, she co-investigates the €546k KiKa-funded PACT-ES project advancing personalized chemotherapy approaches. She serves on MSc Graduation Committees for Mathematics and Statistics & Data Science at Leiden University, mentoring next-generation biostatisticians in cancer research methodologies.
Her collaborative ecosystem spans the Data Analysis and Survival for Personalised Oncology group, SIG Health Data Science network, and Euro-Ewing Consortium partnerships. Through these frameworks, she integrates statistical innovation with clinical practice to transform pediatric cancer treatment paradigms using latent toxicity modeling and causal inference frameworks.
