Evidence map›Paper›PMID 32543098›Full record

ArticleThoracic cancer2020

Integrated strategy combining endobronchial ultrasound with positron emission tomography to diagnose peripheral pulmonary lesions.

Xiao Wu, Zhou An, Kui Zhao, Sijia Yang, Xu Lin, Xiaona Dai, Derek Radisky, Jian Hu

Abstract read
In one paragraph

Article in Thoracic cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xiao WuDepartment of Thoracic Surgery, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Zhou AnDepartment of Thoracic Surgery, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Kui ZhaoPET Center, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Sijia Yang
Xu LinDepartment of Thoracic Surgery, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Xiaona DaiHospital Administration Office of Zhejiang University, Hangzhou, China.
Derek RadiskyDepartment of Cancer Biology, Mayo Clinic Cancer Center, Jacksonville, Florida, USA.
Jian HuDepartment of Thoracic Surgery, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.

Funding

General research program of medical and health in Zhejiang Province 2015KYB140The National Key Research and Development Program of China 2017YFC0113500Zhejiang Province Major Science and Technology Special Project 2014C03032Zhejiang Provincial Key Discipline of Traditional Chinese Medicine 2017-XK-A33
6 · The paper itself

Abstract

backgroundEndobronchial ultrasound-guided transbronchial lung biopsy (EBUS-TBLB) and fluorodeoxyglucose positron emission tomography (FDG-PET) have been widely used in the diagnosis of peripheral pulmonary lesions (PPLs). This study was conducted to determine the diagnostic value of EBUS-TBLB combined with FDG-PET in the assessment of PPLs.

methodsThe clinical data of 76 patients with PPLs who received both FDG-PET and EBUS-TBLB from January 2016 to February 2018 were retrospectively evaluated. Further subgroup analysis was performed according to lesion diameter (≤20 mm or >20 mm). Related diagnostic indices were calculated and compared between groups.

resultsWhen combining EBUS-TBLB with FDG-PET, the diagnostic accuracy rate, sensitivity, specificity, Youden's index, positive predictive value, and negative predictive value for PPLs were 86.8%, 90.2%, 73.3%, 63.5%, 93.2%, and 64.7%, respectively. In addition, the diagnostic accuracy rate of the combined approach was significantly higher than the single EBUS-TBLB and FDG-PET (P < 0.01 and P < 0.05, respectively), and its Youden's index was also at a higher level. When stratified by lesion diameter, the combined approach showed a significantly higher diagnostic accuracy rate (P < 0.05) and a higher Youden's index for PPLs >20 mm than PPLs ≤20 mm. In addition, we found that positive bronchus sign and probe within the probe were two important factors conducing to enhancing the diagnostic accuracy rate for EBUS-TBLB.

conclusionsAn integrated approach combining EBUS-TBLB with FDG-PET is particularly useful for diagnosing PPLs, and the improved diagnostic yields were especially evident for PPLs >20 mm.

Indexed as

AgedBronchoscopyEndosonographyFemaleHumansLung NeoplasmsMaleMiddle AgedPositron-Emission TomographyDiagnosisendobronchial ultrasoundperipheral pulmonary lesionspositron emission tomographytransbronchial lung biopsy

Identifiers

PMID32543098
PMCPMC7396360

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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.