Evidence map›Paper›PMID 33209621›Full record

ArticleTranslational lung cancer research2020

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.

Wenhua Liang, Dan Liu, Min Li, Wei Wang, Zheng Qin, Jian Zhang, Yong Zhang, Yang Hu, Hairong Bao, Yi Xiang and 29 more

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational lung cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03651986 (Diagnostic and Monitoring Significance of Circulating Tumor DNA), which is not on this map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03651986 unknown statusnot on this map

Diagnostic and Monitoring Significance of Circulating Tumor DNA (ctDNA) Methylation Analysis by Next-Generation Sequencing in Benign and Malignant Pulmonary Nodules

TypeobservationalSponsorAnchorDx Medical Co., Ltd.Ran2018 to 2025Enrolled10,560ConditionsPulmonary NodulesArmsctDNA methylation analysis by NGS
3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Effects ofHeliyon · 2024
    Article
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  7. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

39 authors.

Wenhua LiangDepartment of Thoracic Surgery/Oncology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Institute of Respiratory Disease & Health, China State Key Laboratory and National Clinical Research Center for Respiratory Disease, Guangzhou, China.
Dan LiuDepartment of Respiratory Medicine, West China Hospital of Sichuan University, Chengdu, China.
Min LiDepartment of Respiratory Medicine, Xiangya Cancer Center, Xiangya Hospital, Central South University, Changsha, China.
Wei WangSchool of Medicine, Shandong University, Jinan, China.
Zheng QinDepartment of Respiratory Medicine, The First Hospital of China Medical University, Shenyang, China.
Jian ZhangDepartment of Pulmonary Medicine, Xijing Hospital, Air Force Medical University of PLA, Xi'an, China.
Yong ZhangDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Yang HuDepartment of Respiratory Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
Hairong BaoDepartment of Gerontol Respiratory Medicine, The Frist Hospital of Lanzhou University, Lanzhou, China.
Yi XiangDepartment of Pulmonary & Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Bo WangAnchorDx Medical Co., Ltd., Guangzhou, China.
Jing WuAnchorDx Medical Co., Ltd., Guangzhou, China.
Jianyu SunAnchorDx Medical Co., Ltd., Guangzhou, China.
Chengping HuDepartment of Respiratory Medicine, Xiangya Cancer Center, Xiangya Hospital, Central South University, Changsha, China.
Xianwei YeDepartment of Respiratory and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang, China.
Xiangyan ZhangDepartment of Respiratory and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang, China.
Wei XiaoDepartment of Respiratory Medicine, QILU Hospital, Shandong University, Jinan, China.
Chunmei YunDepartment of Pulmonary and Critical Care Medicine, Inner Mongolia Autonomous Region People's Hospital, Hohhot, China.
Dejun SunDepartment of Pulmonary and Critical Care Medicine, Inner Mongolia Autonomous Region People's Hospital, Hohhot, China.
Wei WangDepartment of Respiratory Medicine, The First Hospital of China Medical University, Shenyang, China.
Ning ChangDepartment of Pulmonary Medicine, Xijing Hospital, Air Force Medical University of PLA, Xi'an, China.
Yunhui ZhangDepartment of Respiratory Medicine, The First People's Hospital of Yunnan Province, Kunming, China.
Jianping ZhaoDepartment of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xin ZhangDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Jinfu XuDepartment of Respiratory Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
Di WuDepartment of Respiratory Medicine, Shenzhen People's Hospital, Shenzhen, China.
Xiaoju LiuDepartment of Gerontol Respiratory Medicine, The Frist Hospital of Lanzhou University, Lanzhou, China.
Yubiao GuoDepartment of Pulmonary Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Qichuan ZhangDepartment of Respiratory Medicine, Shantou Central Hospital, Shantou, China.
Wei ZhangDepartment of Respiration, The First Affiliated Hospital of Nanchang University, Nanchang, China.
Lan YangDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
Zhanqing LiDepartment of Cardiothoracic Surgery, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China.
Xiaoju ZhangDepartment of Respiratory Medicine, Henan Provincial People's Hospital, Zhengzhou, China.
Baohui HanDepartment of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China.
Zhaohui TongDepartment of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Jianxing HeDepartment of Thoracic Surgery/Oncology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Institute of Respiratory Disease & Health, China State Key Laboratory and National Clinical Research Center for Respiratory Disease, Guangzhou, China.
Jieming QuDepartment of Pulmonary & Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jian-Bing FanAnchorDx Medical Co., Ltd., Guangzhou, China.
Nanshan ZhongNational Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung 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.

methodsA 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.

trial registrationClinicaltrials.gov NCT03651986.

Indexed as

liquid biopsylung cancer early diagnosisPulmonary nodule

Identifiers

PMID33209621
PMCPMC7653103

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