Evaluating the diagnostic accuracy of a ctDNA methylation classifier for incidental lung nodules: protocol for a prospective, observational, and multicenter clinical trial of 10,560 cases
机构：[1]Department of Thoracic Surgery/Oncology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Institute of RespiratoryDisease & Health, China State Key Laboratory and National Clinical Research Center for Respiratory Disease, Guangzhou, China[2]Department ofRespiratory Medicine, West China Hospital of Sichuan University, Chengdu, China四川大学华西医院[3]Department of Respiratory Medicine, Xiangya Cancer Center,Xiangya Hospital, Central South University, Changsha, China[4]School of Medicine, Shandong University, Jinan, China[5]Department of RespiratoryMedicine, The First Hospital of China Medical University, Shenyang, China[6]Department of Pulmonary Medicine, Xijing Hospital, Air Force MedicalUniversity of PLA, Xi’an, China[7]Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China[8]Department ofRespiratory Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China[9]Department of Gerontol RespiratoryMedicine, The Frist Hospital of Lanzhou University, Lanzhou, China[10]Department of Pulmonary & Critical Care Medicine, Ruijin Hospital,Shanghai Jiao Tong University School of Medicine, Shanghai, China[11]AnchorDx Medical Co., Ltd., Guangzhou, China[12]Department of Respiratoryand Critical Care Medicine, Guizhou Provincial People’s Hospital, Guiyang, China[13]Department of Respiratory Medicine, QILU Hospital, ShandongUniversity, Jinan, China[14]Department of Pulmonary and Critical Care Medicine, Inner Mongolia Autonomous Region People’s Hospital, Hohhot,China[15]Department of Respiratory Medicine, The First People’s Hospital of Yunnan Province, Kunming, China内科片呼吸与危重症医学科云南省第一人民医院[16]Department of Respiratory andCritical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China华中科技大学同济医学院附属同济医院[17]Department ofRespiratory Medicine, Shenzhen People’s Hospital, Shenzhen, China深圳市康宁医院深圳市人民医院深圳医学信息中心[18]Department of Pulmonary Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China中山大学附属第一医院[19]Department of Respiratory Medicine, Shantou Central Hospital, Shantou, China[20]Department of Respiration,The First Affiliated Hospital of Nanchang University, Nanchang, China[21]Department of Pulmonary and Critical Care Medicine, The First AffiliatedHospital, Xi'an Jiaotong University, Xi’an, China[22]Department of Cardiothoracic Surgery, The Second Affiliated Hospital of Xiamen MedicalCollege, Xiamen, China[23]Department of Respiratory Medicine, Henan Provincial People’s Hospital, Zhengzhou, China[24]Department of PulmonaryMedicine, Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China[25]Department of Respiratory and Critical Care Medicine, BeijingInstitute of Respiratory Medicine, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China北京朝阳医院[26]Department of Pathology, School of BasicMedical Science, Southern Medical University, Guangzhou, China[27]National Clinical Research Center for Respiratory Disease, State Key Laboratoryof Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
Background: Lung nodules are a diagnostic challenge. Current clinical management of lung nodule patients is inefficient and therefore causes patient misclassification, which increases healthcare expenses. However, a precise and robust lung nodule classifier to minimize discomfort for patients and healthcare costs is still lacking. The aim of the present protocol is to evaluate the effectiveness of using a liquid biopsy classifier to diagnose nodules compared to physician estimates and whether the classifier can reduce the number of unnecessary biopsies in benign cases. Methods: A prospective cohort of 10,560 patients enrolled at 23 clinical centers in China with non-calcified pulmonary nodules, ranging from 0.5 to 3 cm in diameter, indicated by LDCT or CT will be included. After signed consent forms, the participants' pulmonary nodules will be assessed using three evaluation tools: (I) physician cancer probability estimates (II) validated lung nodule risk models, including Mayo Clinic and Veteran's Affairs models (III) ctDNA methylation classifier previously established. Each patient will undergo LDCT/CT follow-ups for 2 to 3 years and their information and one blood sample will be collected at baseline, 3, 6, 12, 24 and 36 months. The primary study outcomes will be the diagnostic accuracy of the methylation classifier in the cohort. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) will be used to compare the diagnostic value of each testing tool in differentiating benign and malignant pulmonary nodules. Discussion: We are conducting an observational study to explore the accuracy of using a ctDNA methylation classifier for incidental lung nodules diagnosis
基金：
China National Science FoundationNational Natural Science Foundation of China (NSFC) [81871893]; Key Project of Guangzhou Scientific Research Project [201804020030]; National key Research and Development Program [2017YFC0907903]; Scheme of Guangzhou Economic and Technological Development District for Leading Talents in Innovation and Entrepreneurship [2017-L152]; Scheme of Guangzhou for Leading Talents in Innovation and Entrepreneurship [2016007]; Science and Technology Planning Project of Guangdong Province, China [2017B020226005]; National Key Research and Development Program of China [2017YFC1309002]; AnchorDx Medical Co., Ltd.; Scheme of Guangzhou for Leading Team in Innovation [201909010010]
第一作者机构：[1]Department of Thoracic Surgery/Oncology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Institute of RespiratoryDisease & Health, China State Key Laboratory and National Clinical Research Center for Respiratory Disease, Guangzhou, China
共同第一作者：
通讯作者：
通讯机构：[11]AnchorDx Medical Co., Ltd., Guangzhou, China[26]Department of Pathology, School of BasicMedical Science, Southern Medical University, Guangzhou, China[27]National Clinical Research Center for Respiratory Disease, State Key Laboratoryof Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China[*1]Department of Pathology, School of Basic Medical Science, Southern Medical University, Guangzhou 510515, China[*2]National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China
推荐引用方式(GB/T 7714)：
Wenhua Liang,Dan Liu,Min Li,et al.Evaluating the diagnostic accuracy of a ctDNA methylation classifier for incidental lung nodules: protocol for a prospective, observational, and multicenter clinical trial of 10,560 cases[J].TRANSLATIONAL LUNG CANCER RESEARCH.2020,9(5):2016-2026.doi:10.21037/tlcr-20-701.
APA：
Wenhua Liang,Dan Liu,Min Li,Wei Wang,Zheng Qin...&Nanshan Zhong.(2020).Evaluating the diagnostic accuracy of a ctDNA methylation classifier for incidental lung nodules: protocol for a prospective, observational, and multicenter clinical trial of 10,560 cases.TRANSLATIONAL LUNG CANCER RESEARCH,9,(5)
MLA：
Wenhua Liang,et al."Evaluating the diagnostic accuracy of a ctDNA methylation classifier for incidental lung nodules: protocol for a prospective, observational, and multicenter clinical trial of 10,560 cases".TRANSLATIONAL LUNG CANCER RESEARCH 9..5(2020):2016-2026
