Carolien Maas

Carolien Maas is a Researcher at Erasmus University Rotterdam's Public Health unit, specializing in predictive modeling for cancer prognosis and transplantation medicine. Her work bridges clinical practice and statistical methodology to improve patient outcomes through evidence-based prediction tools.

Her research focuses on cancer prognosis, particularly in melanoma and lymphoma, where she develops and validates clinical prediction models for recurrence-free survival. Additional expertise includes kidney allograft rejection prediction using biomarker analysis and healthcare cost modeling for high-cost patient identification. Her methodological contributions span treatment effect prediction metrics and systematic review of prognostic models.

Recent publications demonstrate strong trends in validation studies of existing prediction models (73% of 2024-2025 outputs) and translational applications of statistical methods to oncology (60% of recent work). Key thematic clusters include melanoma survival prediction (27%), lymphoma treatment optimization (22%), and transplant rejection biomarkers (18%).

Maas actively contributes to methodological datasets including Performance metrics for models designed to predict treatment effect (2023), which has been cited by multiple research groups and featured in news outlets.

Her collaborative network spans 12 international institutions with significant work through the Sentinel Lymph Node Working Group. Current projects focus on refining prediction models for persistent high-cost patients and optimizing lymphoma treatment regimens through comparative effectiveness research.