Evidence map›Paper›PMID 33793424›Full record

Trial reportThe Journal of clinical investigation2021

Accurate diagnosis of pulmonary nodules using a noninvasive DNA methylation test.

Wenhua Liang, Zhiwei Chen, Caichen Li, Jun Liu, Jinsheng Tao, Xin Liu, Dezhi Zhao, Weiqiang Yin, Hanzhang Chen, Chao Cheng and 21 more

Registry-linked trialOpen access · greenAbstract readClinical TrialMulticenter Study
In one paragraph

Trial report in The Journal of clinical investigation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07593833 (Prospective Clinical Validation Study of a Blood-Based cfDNA Methylation Assay for the Detection of Ovarian Cancer), which is not on this map. Cited by 65 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 2 pooled it
12.2field-weighted citation impact, top 1% of its field
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.

NCT07593833 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Prospective Clinical Validation Study of a Blood-Based cfDNA Methylation Assay for the Detection of Ovarian Cancer

TypeobservationalSponsorTongji HospitalRan2026 to 2029Enrolled1,000ConditionsOvarian Neoplasms, Ovarian Cancer, Early Detection of CancerArmsBlood-Based cfDNA Methylation Assay for Ovarian Cancer Detection
3 · Its place in the literature

Who cites it

65 citing papers in PubMed, 2 syntheses or guidelines pooled it, 112 citations in OpenAlex.

  1. Pooled it
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  3. A Noninvasive Circulating Tumor DNA Methylation Classifier to Identify Benign Pulmonary Nodules.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
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5 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

31 authors at 15 institutions in 2 countries.

Wenhua LiangDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou, China.
Zhiwei ChenAnchorDx Medical Co., Guangzhou, China.
Caichen LiDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou, China.
Jun LiuDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou, China.
Jinsheng TaoAnchorDx Medical Co., Guangzhou, China.
Xin LiuAnchorDx Inc., Fremont, California, USA.
Dezhi ZhaoAnchorDx Medical Co., Guangzhou, China.
Weiqiang YinDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou, China.
Hanzhang ChenDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou, China.
Chao ChengDepartment of Thoracic Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Fenglei YuDepartment of Thoracic Surgery, The Second Xiangya Hospital of Central South University, Changsha, China.
Chunfang ZhangDepartment of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, China.
Luxu LiuDepartment of Thoracic Surgery, West China Hospital of Sichuan University, Chengdu, China.
Hui TianDepartment of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan, China.
Kaican CaiDepartment of Thoracic Surgery, Nanfang Hospital of Southern Medical University, Guangzhou, China.
Xiang LiuDepartment of Thoracic Surgery, The Second Hospital, University of South China, Hengyang, China.
Zheng WangDepartment of Thoracic Surgery, Shenzhen People's Hospital, Shenzhen, China.
Ning XuDepartment of Thoracic Surgery, Anhui Chest Hospital, Hefei, China.
Qing DongDepartment of Thoracic Surgery, Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Liang ChenDepartment of Thoracic Surgery, Jiangsu Province Hospital, Nanjing, China.
Yue YangDepartment of Thoracic Surgery, Beijing Cancer Hospital, Beijing, China.
Xiuyi ZhiDepartment of Thoracic Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
Hui LiAnchorDx Medical Co., Guangzhou, China.
Xixiang TuAnchorDx Medical Co., Guangzhou, China.
Xiangrui CaiCollege of Computer Science, Nankai University, Tianjin, China.
Zeyu JiangAnchorDx Medical Co., Guangzhou, China.
Hua JiCollege of Computer Science, Nankai University, Tianjin, China.
Lili MoDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou, China.
Jiaxuan WangDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou, China.
Jian-Bing FanAnchorDx Medical Co., Guangzhou, China.
Jianxing HeDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou, China.
First Affiliated Hospital of Guangzhou Medical University · CNCentral South University · CNNankai University · CNUniversity of South China · CNCapital Medical University · CNHarbin Medical University · CNJiangsu Province Hospital · CNNanfang Hospital · CNPeking University · CNQilu Hospital of Shandong University · CNShenZhen People’s Hospital · CNSichuan University · CNSouthern Medical University · CNSun Yat-sen University · CNXi'an Chest Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

DNA MethylationLung NeoplasmsMultiple Pulmonary NodulesTomography, X-Ray ComputedAdultAgedAged, 80 and overDNA, NeoplasmFemaleHumansMaleMiddle AgedRetrospective StudiesDNA, NeoplasmDiagnosticsGeneticsLung cancerOncology

Identifiers

PMID33793424
PMCPMC8121527
OpenAlexW3151454118

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.