Nathanael R. Fillmore
Topics / Lung Cancer
Topic

Lung Cancer

Fillmore has focused on improving prognostic accuracy and treatment selection for patients with lung cancer, with a particular emphasis on older veterans and those with significant comorbidities. His work examines how frailty, multisystem impairment, and the use of immune checkpoint inhibitors influence survival and hospitalization risks. Additionally, he has developed scalable machine learning frameworks and predictive tools to refine lung cancer screening and mortality forecasting within the Veterans Affairs health system.

U.S. Veterans and VA Data 10 Retrospective Cohort Study 5 Overall Survival 4 Cox Proportional Hazards Model 4 Cancer Patients 4 Real World Evidence 4 Electronic Health Records 3 Patient Outcomes 3 Advanced Stage Malignancy 3 Immune Checkpoint Inhibitors 3 Mortality Prediction 3 Predictive Modeling 3

Publications (10)

2025

Rapid Support and Implementation of an Application for the Prediction Augmented Screening Initiative (PASI) Planning Phase Through the Enabling Technologies for Rapid Learning Health Systems Platform (ENTHRALL) at the Department of Veterans Affairs (VA).

Hannah M. Tosi, Chunlei Zheng, Amelia H. Tarren, Meghana Yellanki, Stephen J. Miller, Oleg V. Soloviev, June K. Corrigan, George R. Schneeloch, Hormuzd A. Katki, Lauren E. Kearney, Tanner J. Caverly, Nichole T. Tanner, Renda Soylemez Wiener, Mary Brophy, Nathanael R. Fillmore, Nhan V. Do, Danne C. Elbers

Cancer Informatics24, 11769351251389781
U.S. Veterans and VA Data Electronic Health Records Lung Cancer Natural Language Processing Learning Health Systems
2025

Multimorbidity and Its Impact in Older U.S. Veterans Newly Treated for Advanced Non-Small Cell Lung Cancer.

Joseph R. Larsen†, Chunlei Zheng†, Jennifer La, Julie Tsu-Yu Wu, Michael Kelley, J. Michael Gaziano, Mary Brophy, Nhan V. Do, Dae H. Kim, Jane A. Driver, Clark DuMontier‡, Nathanael R. Fillmore‡† Equal first authorship · ‡ Equal senior authorship

Annals of the American Thoracic Society22(4), 598-608
U.S. Veterans and VA Data Retrospective Cohort Study Lung Cancer Overall Survival Geriatric Oncology
2019

Machine Learning Methods to Predict Lung Cancer Survival Using the Veterans Affairs Research Precision Oncology Data Commons.

Nhan V. Do, Jaime C. Ramos, Nathanael R. Fillmore, Robert L. Grossman, Michael Fitzsimons, Danne C. Elbers, Frank Meng, Brett R. Johnson, Samuel Ajjarapu, Corri L. DeDomenico, Karen E. Pierce-Murray, Robert B. Hall, Andrew F. Do, Kelly Gaynor, Peter L. Elkin, Mary T. Brophy

Studies in Health Technology and Informatics264, 1453
U.S. Veterans and VA Data Lung Cancer Machine Learning Predictive Modeling Overall Survival