Topic

Immunotherapy

Fillmore has investigated the determinants of treatment access and clinical outcomes for patients receiving cancer immunotherapy. His work includes the development of machine learning tools to automate the extraction of PD-L1 expression levels from electronic health records to facilitate large-scale population analyses. Additionally, he has examined how frailty influences the administration and efficacy of immunotherapy in patients with advanced non-small cell lung cancer, identifying significant disparities in survival based on performance status.

U.S. Veterans and VA Data 2 Retrospective Cohort Study 1 Cancer Patients 1 Lung Cancer 1 Advanced Stage Malignancy 1 Immune Checkpoint Inhibitors 1 Frailty 1 Electronic Frailty Index 1 Performance Status 1 Overall Survival 1 Logistic Regression 1 Cox Proportional Hazards Model 1

Publications (2)

2024

The performance status gap in immunotherapy for frail patients with advanced non-small cell lung cancer.

Julie Tsu-Yu Wu, June Corrigan, Chloe Su, Clark Dumontier, Jennifer La, Aparjita Khan, Shipra Arya, Alex H. S. Harris, Leah Backhus, Millie Das, Nhan V. Do, Mary T. Brophy, Summer S. Han, Michael Kelley, Nathanael R. Fillmore

Cancer Immunology, Immunotherapy73(9), 172

U.S. Veterans and VA Data Retrospective Cohort Study Cancer Patients Lung Cancer Advanced Stage Malignancy

2023

Machine learning-based natural language processing to extract PD-L1 expression levels from clinical notes.

Eric Lin^†, Robert Zwolinski^†, Julie Tsu-Yu Wu, Jennifer La, Sergey Goryachev, Linden Huhmann, Cenk Yildrim, David P. Tuck, Danne C. Elbers, Mary T. Brophy, Nhan V. Do^‡, Nathanael R. Fillmore^‡^† Equal first authorship · ^‡ Equal senior authorship

Health Informatics Journal29(3), 14604582231198021

U.S. Veterans and VA Data Electronic Health Records Natural Language Processing Machine Learning PD-L1 Expression