Tumor volume as a predictor of cell free DNA mutation detection in advanced non-small cell lung cancer.
Transl Lung Cancer Res
; 11(8): 1578-1590, 2022 Aug.
Article
em En
| MEDLINE
| ID: mdl-36090640
ABSTRACT
Background:
Cell free DNA (cfDNA) is an exciting biomarker with applications across the cancer care continuum. Determinants of cfDNA shedding dynamics remain an active research area. We performed a detailed analysis of tumor volume and factors associated with detection of cfDNA mutations.Methods:
Patients with advanced non-small cell lung cancers (NSCLCs) were prospectively enrolled on a plasma biomarker protocol. Next generation sequencing (NGS) was performed using a validated, bias-corrected, hybrid-capture panel assay of lung cancer-associated genes. Volume of tumor in different subsites and total tumor volume were determined through manual volume delineation using PET/CT and brain magnetic resonance imaging (MRI) imaging. The primary endpoint was detection of cfDNA mutation; secondary endpoints were overall survival (OS) and variant allele frequency (VAF).Results:
There were 110 patients included, 78 of whom had at least one mutation detected. Median total tumor volume for the entire cohort, patients with mutation detected, and patients with no mutation detected were 66 mL (range, 2-1,383 mL), 76 mL (range, 5-1,383 mL), and 45 mL (range, 2-460 mL), respectively (P=0.002; mutation detected vs. not). The optimal total tumor volume threshold to predict increased probability of mutation detection was 65 mL (P=0.006). Total tumor volume greater than 65 mL was a significant predictor of mutation detection on multivariate analysis (OR 4.30, P=0.003). Significant predictors of OS were age (HR 1.04, P=0.002), detection of cfDNA mutation (HR 2.11, P=0.024), and presence of bone metastases (HR 1.66, P=0.047).Conclusions:
Total tumor volume greater than 65 mL was associated with cfDNA mutation detection in patients with advanced NSCLC.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Transl Lung Cancer Res
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos