| Literature DB >> 33793424 |
Wenhua Liang1, Zhiwei Chen2,3, Caichen Li1, Jun Liu1, Jinsheng Tao2, Xin Liu3, Dezhi Zhao2, Weiqiang Yin1, Hanzhang Chen1, Chao Cheng4, Fenglei Yu5, Chunfang Zhang6, Luxu Liu7, Hui Tian8, Kaican Cai9, Xiang Liu10, Zheng Wang11, Ning Xu12, Qing Dong13, Liang Chen14, Yue Yang15, Xiuyi Zhi16, Hui Li2, Xixiang Tu2, Xiangrui Cai17, Zeyu Jiang2, Hua Ji17,18, Lili Mo1, Jiaxuan Wang1, Jian-Bing Fan2,19, Jianxing He1,9.
Abstract
BACKGROUNDCurrent clinical management of patients with pulmonary nodules involves either repeated low-dose CT (LDCT)/CT scans or invasive procedures, yet causes significant patient misclassification. An accurate noninvasive test is needed to identify malignant nodules and reduce unnecessary invasive tests.METHODWe developed a diagnostic model based on targeted DNA methylation sequencing of 389 pulmonary nodule patients' plasma samples and then validation in 140 plasma samples independently. We tested the model in different stages and subtypes of pulmonary nodules.RESULTSA 100-feature model was developed and validated for pulmonary nodule diagnosis; the model achieved a receiver operating characteristic curve-AUC (ROC-AUC) of 0.843 on 140 independent validation samples, with an accuracy of 0.800. The performance was well maintained in (a) a 6 to 20 mm size subgroup (n = 100), with a sensitivity of 1.000 and adjusted negative predictive value (NPV) of 1.000 at 10% prevalence; (b) stage I malignancy (n = 90), with a sensitivity of 0.971; (c) different nodule types: solid nodules (n = 78) with a sensitivity of 1.000 and adjusted NPV of 1.000, part-solid nodules (n = 75) with a sensitivity of 0.947 and adjusted NPV of 0.983, and ground-glass nodules (n = 67) with a sensitivity of 0.964 and adjusted NPV of 0.989 at 10% prevalence. This methylation test, called PulmoSeek, outperformed PET-CT and 2 clinical prediction models (Mayo Clinic and Veterans Affairs) in discriminating malignant pulmonary nodules from benign ones.CONCLUSIONThis study suggests that the blood-based DNA methylation model may provide a better test for classifying pulmonary nodules, which could help facilitate the accurate diagnosis of early stage lung cancer from pulmonary nodule patients and guide clinical decisions.FUNDINGThe National Key Research and Development Program of China; Science and Technology Planning Project of Guangdong Province; The National Natural Science Foundation of China National.Entities:
Keywords: Diagnostics; Genetics; Lung cancer; Oncology
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Year: 2021 PMID: 33793424 PMCID: PMC8121527 DOI: 10.1172/JCI145973
Source DB: PubMed Journal: J Clin Invest ISSN: 0021-9738 Impact factor: 14.808