Evaluating Tumor Burden as a Predictive Biomarker for Epidermal Growth Factor Receptor Targeted Kinase Inhibitor Therapy in Advanced Non-Small Cell Lung Cancer.

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Title: Evaluating Tumor Burden as a Predictive Biomarker for Epidermal Growth Factor Receptor Targeted Kinase Inhibitor Therapy in Advanced Non-Small Cell Lung Cancer.
Authors: Terashima R; Department of Medicine, Jacobi Medical Center, Albert Einstein College of Medicine, Bronx, NY.; Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA., Fan J; Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA., Gunturkun F; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA., Nieda G; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA., Fan X; Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA., Rodriguez EM; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA., Tan AX; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA., Thottunkal S; Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA., Shaw M; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA., Su CC; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA., Khan A; Department of Computer Science and Engineering, Indian Institute of Technology (BHU) Varanasi, Varanasi, India., Ding VY; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA., Luo I; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA., Satoyoshi M; Technology and Digital Solutions (TDS), Research Technology, and Research Data Services, Stanford Health Care and Stanford University School of Medicine, Stanford, CA., Bhat A; Technology and Digital Solutions (TDS), Research Technology, and Research Data Services, Stanford Health Care and Stanford University School of Medicine, Stanford, CA., Gu B; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA., Henry SM; Technology and Digital Solutions (TDS), Research Technology, and Research Data Services, Stanford Health Care and Stanford University School of Medicine, Stanford, CA., Ellis-Caleo TJ; Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA., Odden M; Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA., Kurian AW; Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA.; Stanford Cancer Institute, Stanford University, Stanford, CA., Neal JW; Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA.; Stanford Cancer Institute, Stanford University, Stanford, CA., Wakelee HA; Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA.; Stanford Cancer Institute, Stanford University, Stanford, CA., Wu JT; Stanford Cancer Institute, Stanford University, Stanford, CA., Han SS; Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA.; Stanford Cancer Institute, Stanford University, Stanford, CA.; Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA.
Source: JCO precision oncology [JCO Precis Oncol] 2026 Apr; Vol. 10 (4), pp. e2500884. Date of Electronic Publication: 2026 Apr 09.
Publication Type: Journal Article
Journal Info: Publisher: American Society of Clinical Oncology Country of Publication: United States NLM ID: 101705370 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2473-4284 (Electronic) Linking ISSN: 24734284 NLM ISO Abbreviation: JCO Precis Oncol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2473-4284
DOI:10.1200/PO-25-00884