{Reference Type}: Journal Article
{Title}: Non-invasive diagnosis of pulmonary nodules by circulating tumor DNA methylation: A prospective multicenter study.
{Author}: Li Y;Xie F;Zheng Q;Zhang Y;Li W;Xu M;He Q;Li Y;Sun J;
{Journal}: Lung Cancer
{Volume}: 195
{Issue}: 0
{Year}: 2024 Sep 11
{Factor}: 6.081
{DOI}: 10.1016/j.lungcan.2024.107930
{Abstract}: BACKGROUND: With the popularization of computed tomography, more and more pulmonary nodules (PNs) are being detected. Risk stratification of PNs is essential for detecting early-stage lung cancer while minimizing the overdiagnosis of benign nodules. This study aimed to develop a circulating tumor DNA (ctDNA) methylation-based, non-invasive model for the risk stratification of PNs.
METHODS: A blood-based assay ("LUNG-TRAC") was designed to include novel lung cancer ctDNA methylation markers identified from in-house reduced representative bisulfite sequencing data and known markers from the literature. A stratification model was trained based on 183 ctDNA samples derived from patients with benign or malignant PNs and validated in 62 patients. LUNG-TRAC was further single-blindly tested in a single- and multi-center cohort.
RESULTS: The LUNG-TRAC model achieved an area under the curve (AUC) of 0.810 (sensitivity = 74.4 % and specificity = 73.7 %) in the validation set. Two test sets were used to evaluate the performance of LUNG-TRAC, with an AUC of 0.815 in the single-center test (N = 61; sensitivity = 67.5 % and specificity = 76.2 %) and 0.761 in the multi-center test (N = 95; sensitivity = 50.7 % and specificity = 80.8 %). The clinical utility of LUNG-TRAC was further assessed by comparing it to two established risk stratification models: the Mayo Clinic and Veteran Administration models. It outperformed both in the validation and the single-center test sets.
CONCLUSIONS: The LUNG-TRAC model demonstrated accuracy and consistency in stratifying PNs for the risk of malignancy, suggesting its utility as a non-invasive diagnostic aid for early-stage peripheral lung cancer.
BACKGROUND: www.
RESULTS: gov (NCT03989219).