Survival Analysis

Fillmore has extensively utilized survival analysis to identify prognostic biomarkers and refine risk stratification for patients with hematologic and solid malignancies. His research demonstrates that frailty, multimorbidity, and specific hematologic indices—such as lymphopenia and thrombocytopenia—are independent predictors of mortality across multiple cancer types. Additionally, he has developed and validated machine learning models and clinical risk scores to predict cardiovascular events and venous thromboembolism, providing a data-driven framework for personalizing preventative care and therapeutic selection.