Evidence map›Paper›PMID 30981987›Full record

Trial reportJournal of medical genetics2019

Resectable lung lesions malignancy assessment and cancer detection by ultra-deep sequencing of targeted gene mutations in plasma cell-free DNA.

Muyun Peng, Yuancai Xie, Xiaohua Li, Youhui Qian, Xiaonian Tu, Xumei Yao, Fangsheng Cheng, Feiyue Xu, Deju Kong, Bing He and 6 more

Registry-linked trialAbstract readClinical TrialMulticenter Study
In one paragraph

Trial report in Journal of medical genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03081741 (A Prospective Study of Circulating Tumor DNA Detection in Surveillance for Lung Cancer Patients), which is not on this map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 pooled it
–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.

NCT03081741 unknown statusnot on this map

A Prospective Study of Circulating Tumor DNA Detection in Surveillance for Lung Cancer Patients

TypeobservationalSponsorShenzhen Gene Health Bio Tech Co., Ltd.Ran2017 to 2020Enrolled500ConditionsLung Neoplasms
3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Biomarkers Suitable for Early Detection of Intrathoracic Cancers in Primary Care: A Systematic Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
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  13. A scoping review of artificial intelligence applications in thoracic surgery.European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery · 2022
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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

16 authors.

Muyun Peng *Department of Thoracic Surgery, Second Xiangya Hospital, Changsha, China.
Yuancai Xie *Department of Thoracic Surgery, Peking University Shenzhen Hospital, Shenzhen, China.
Xiaohua Li *Vienomics Corp Ltd, Shenzhen, China.
Youhui QianDepartment of Thoracic Surgery, Shenzhen Second People's Hospital, Shenzhen, China.
Xiaonian TuVienomics Corp Ltd, Shenzhen, China.
Xumei YaoVienomics Corp Ltd, Shenzhen, China.
Fangsheng ChengVienomics Corp Ltd, Shenzhen, China.
Feiyue XuVienomics Corp Ltd, Shenzhen, China.
Deju KongVienomics Corp Ltd, Shenzhen, China.
Bing HeDepartment of Clinical Pharmacy, Regents of the University of Michigan, Ann Arbor, Michigan, USA.
Chaoyu LiuVienomics Corp Ltd, Shenzhen, China.
Fengjun CaoOncology Center, Hubei University of Medicine, Shiyan, China.
Haoxian YangDepartment of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China.
Fenglei YuDepartment of Thoracic Surgery, Second Xiangya Hospital, Changsha, China.
Chuanbo XuVienomics Corp Ltd, Shenzhen, China.ORCID 0000-0002-2019-2092
Geng TianDepartment of Medical Oncology, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly detection of lung cancer to allow curative treatment remains challenging. Cell-free circulating tumour (ct) DNA (ctDNA) analysis may aid in malignancy assessment and early cancer diagnosis of lung nodules found in screening imagery.

methodsThe multicentre clinical study enrolled 192 patients with operable occupying lung diseases. Plasma ctDNA, white cell count genomic DNA (gDNA) and tumour tissue gDNA of each patient were analysed by ultra-deep sequencing to an average of 35 000× of the coding regions of 65 lung cancer-related genes.

resultsThe cohort consists of a quarter of benign lung diseases and three quarters of cancer patients with all histopathology subtypes. 64% of the cancer patients are at stage I. Gene mutations detection in tissue gDNA and plasma ctDNA results in a sensitivity of 91% and specificity of 88%. When ctDNA assay was used as the test, the sensitivity was 69% and specificity 96%. As for the lung cancer patients, the assay detected 63%, 83%, 94% and 100%, for stages I, II, III and IV, respectively. In a linear discriminant analysis, combination of ctDNA, patient age and a panel of serum biomarkers boosted the overall sensitivity to 80% at a specificity of 99%. 29 out of the 65 genes harboured mutations in the patients with lung cancer with the largest number found in

conclusionPlasma ctDNA was analysed in lung nodule assessment and early cancer detection, while an algorithm combining clinical information enhanced the test performance. TRIAL REGISTRATION NUMBER: NCT03081741.

Indexed as

AdultAgedCell-Free Nucleic AcidsCirculating Tumor DNACohort StudiesFemaleHigh-Throughput Nucleotide SequencingHumansLung NeoplasmsMaleMiddle AgedMutationNeoplasmsProspective StudiesSensitivity and SpecificitySequence Analysis, DNACell-Free Nucleic AcidsCirculating Tumor DNAcirculating tumor DNAliquid biopsylung cancer detectionlung nodule malignancytargeted gene NGS sequencing

Identifiers

PMID30981987
PMCPMC6817693

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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.