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

PURPOSE: As treatment options for advanced non-small cell lung cancer (NSCLC) evolve, biomarkers are needed to guide therapy selection while balancing efficacy and toxicity. Although tumor burden is a promising candidate, its prognostic role in guiding epidermal growth factor receptor (EGFR)-targeted kinase inhibitor (TKI) therapies remains understudied in real-world settings. METHODS: -mutant NSCLC treated with first-line EGFR-TKI at Stanford Health Care (2000-2021). Tumor burden metrics were manually annotated from 592 baseline radiology reports, encompassing size, number, and location (1,807 lesions). Multivariable Cox regression evaluated associations between tumor burden metric and overall survival (OS), adjusting for confounders, in the overall cohort and an osimertinib subgroup. A weighted composite tumor burden score was constructed using statistically significant metrics to stratify risk. RESULTS: = .03) for low versus high tumor burden. CONCLUSION: Tumor burden may serve as a prognostic biomarker in advanced NSCLC receiving EGFR-TKIs. These findings raise the hypothesis that durable survival in low-burden patients may be achievable with monotherapy, potentially sparing unnecessary toxicity from combination regimens. This warrants prospective validation comparing monotherapy versus combination strategies.

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Publication Details

Journal
JCO Precision Oncology
Published
2026-04-01
DOI
https://doi.org/10.1200/po-25-00884
Primary Topic
Lung Cancer Treatments and Mutations
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Fatma Güntürkün, Joel W. Neal, Heather A. Wakelee, Julie Wu et al.
JCO Precision Oncology
Lung Cancer Treatments and Mutations
article

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

Fatma Güntürkün, Joel W. Neal, Heather A. Wakelee, Julie Wu, Rika Terashima, Chloe C. Su, Stefan Thottunkal, Annabel Xulin Tan, Allison W. Kurian, Judy Fan, Michelle C. Odden, Aparajita Khan, Timothy John Ellis-Caleo, Summer S. Han, Ingrid Luo, Archana Bhat, Solomon Henry, Victoria Y. Ding, Grant M. Nieda, Emily M. Rodriguez, Maggie Shaw, Xiaomei Fan, Mina Satoyoshi
article en

Abstract

PURPOSE: As treatment options for advanced non-small cell lung cancer (NSCLC) evolve, biomarkers are needed to guide therapy selection while balancing efficacy and toxicity. Although tumor burden is a promising candidate, its prognostic role in guiding epidermal growth factor receptor (EGFR)-targeted kinase inhibitor (TKI) therapies remains understudied in real-world settings. METHODS: -mutant NSCLC treated with first-line EGFR-TKI at Stanford Health Care (2000-2021). Tumor burden metrics were manually annotated from 592 baseline radiology reports, encompassing size, number, and location (1,807 lesions). Multivariable Cox regression evaluated associations between tumor burden metric and overall survival (OS), adjusting for confounders, in the overall cohort and an osimertinib subgroup. A weighted composite tumor burden score was constructed using statistically significant metrics to stratify risk. RESULTS: = .03) for low versus high tumor burden. CONCLUSION: Tumor burden may serve as a prognostic biomarker in advanced NSCLC receiving EGFR-TKIs. These findings raise the hypothesis that durable survival in low-burden patients may be achievable with monotherapy, potentially sparing unnecessary toxicity from combination regimens. This warrants prospective validation comparing monotherapy versus combination strategies.

JCO Precision OncologyVol. 10(4)
Jacobi Medical Center (US), Stanford Health Care (US), Indian Institute of Technology BHU (IN), Banaras Hindu University (IN), Stanford University (US)
Good health and well-being
Openalex Percentile: Top 23%
Lung Cancer Treatments and Mutations
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