Non-invasive diagnosis of pulmonary nodules by circulating tumor DNA methylation: A prospective multicenter study.
Lung Cancer
; 195: 107930, 2024 Aug 11.
Article
en En
| MEDLINE
| ID: mdl-39146624
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.CONCLUSION:
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. CLINICAL TRIAL REGISTRATION www. CLINICALTRIALS gov (NCT03989219).
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Bases de datos:
MEDLINE
Idioma:
En
Revista:
Lung Cancer
Asunto de la revista:
NEOPLASIAS
Año:
2024
Tipo del documento:
Article
País de afiliación:
China