Evidence map›Paper›PMID 35274488›Full record

ArticleCancer medicine2022

Comparison of sampling methods for next generation sequencing for patients with lung cancer.

Kei Kunimasa, Shingo Matsumoto, Kazumi Nishino, Keiichiro Honma, Noboru Maeda, Hanako Kuhara, Motohiro Tamiya, Takako Inoue, Takahisa Kawamura, Toru Kimura and 4 more

Abstract read
In one paragraph

Article in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

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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

14 authors.

Kei KunimasaDepartment of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan.ORCID 0000-0002-5241-3486
Shingo MatsumotoDepartment of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan.
Kazumi NishinoDepartment of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan.
Keiichiro HonmaDepartment of Diagnostic Pathology & Cytology, Osaka International Cancer Institute, Osaka, Japan.
Noboru MaedaDepartment of Diagnostic and Interventional Radiology, Osaka International Cancer Institute, Osaka, Japan.
Hanako KuharaDepartment of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan.
Motohiro TamiyaDepartment of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan.
Takako InoueDepartment of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan.
Takahisa KawamuraDepartment of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan.
Toru KimuraDepartment of General Thoracic Surgery, Osaka International Cancer Institute, Osaka, Japan.
Tomohiro ManiwaDepartment of General Thoracic Surgery, Osaka International Cancer Institute, Osaka, Japan.
Jiro OkamiDepartment of General Thoracic Surgery, Osaka International Cancer Institute, Osaka, Japan.
Koichi GotoDepartment of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan.
Toru KumagaiDepartment of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSuccess of next generation sequencing (NGS) analysis is becoming indispensable in the treatment of advanced lung cancer. However, the advantages and disadvantages of each sampling method in the NGS analysis have not yet been clarified.

methodsWe compared the success rates of NGS analysis, and DNA and RNA yields for transbronchial biopsy (TBB), endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), computed tomography (CT)-guided biopsy, fluid sample, and surgical biopsy for NGS analysis in patients through the lung cancer genomic screening project for individualized medicine (LC-SCRUM)-Asia, a nationwide NGS screening project. In case, sufficient samples could not be collected by TBB and EBUS-TBNA, re-biopsy (genome re-biopsy) was performed.

resultsA total of 223 patients were enrolled and success rates of NGS analysis were not different between samples obtained through TBB, EBUS-TBNA, and CT-guided biopsy; however, success rates for fluid samples and surgical biopsy samples were significantly higher than those of other methods. The risk of genome re-biopsy was higher with TBB for centrally located lesions. CT-guided biopsy yielded more samples but had a lower success rate for analysis of RNA-based NGS than TBB.

conclusionsTBB is the mainstay of sampling methods, but for centrally located lesions, EBUS-TBNA may be a better strategy. For CT-guided biopsy, the success rate of RNA-based NGS analysis is low. Fluid samples are expected to yield successful results as surgical biopsy samples, but the latter are better for sample preservation. Determining the optimal method for genome biopsy for each case is important.

Indexed as

High-Throughput Nucleotide SequencingLung NeoplasmsEndoscopic Ultrasound-Guided Fine Needle AspirationHumansImage-Guided BiopsyRNARNAlung cancernext generation sequencingNGS success ratere-biopsysampling method

Identifiers

PMID35274488
PMCPMC9302352

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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.