Evidence map›Paper›PMID 35813317›Full record

ArticleAnnals of translational medicine2022

The feasibility of granzyme B levels using an amperometric immunosensor for lung cancer detection.

Jae Heun Chung, Seong Hoon Yoon, Doosoo Jeon, Ho Jung Choi, Kisung Moon, Sunyoung Kwon, Heru Agung Saputra, Yun Seong Kim, Yoon-Bo Shim

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2022. 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
0.6field-weighted citation impact, top 36% 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.

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

1 citing paper in PubMed, 9 citations in OpenAlex.

  1. Review
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

9 authors at 2 institutions in 1 country.

Jae Heun Chung *Department of Internal Medicine, School of Medicine, Pusan National University, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea.
Seong Hoon Yoon *Department of Internal Medicine, School of Medicine, Pusan National University, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea.
Doosoo JeonDepartment of Internal Medicine, School of Medicine, Pusan National University, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea.
Ho Jung ChoiDepartment of Internal Medicine, School of Medicine, Pusan National University, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea.
Kisung MoonSchool of Biomedical Convergence Engineering, College of Information and Biomedical Engineering, Pusan National University, Yangsan, Republic of Korea.
Sunyoung KwonSchool of Biomedical Convergence Engineering, College of Information and Biomedical Engineering, Pusan National University, Yangsan, Republic of Korea.
Heru Agung SaputraDepartment of Chemistry and Institute of BioPhysio Sensor Technology (IBST), Pusan National University, Busan, Republic of Korea.
Yun Seong KimDepartment of Internal Medicine, School of Medicine, Pusan National University, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea.
Yoon-Bo ShimDepartment of Chemistry and Institute of BioPhysio Sensor Technology (IBST), Pusan National University, Busan, Republic of Korea.
Pusan National University Yangsan Hospital · KRPusan National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Low-dose computed tomography (LDCT) has improved the early detection of lung cancer. However, LDCT scans present several disadvantages, including the abundance of false-positive results, which lead to a high socioeconomic cost, psychological burden, and repeated exposure to radiation. Therefore, the identification of complementary biomarkers is needed to select high-risk individuals for LDCT. Here, we showed that granzyme B testing with the novel immunosensor has diagnostic value for identifying patients with lung cancer. Methods: We enrolled 44 patients with lung cancer and 51 health controls at Pusan National University Yangsan Hospital in Korea between March 2018 and September 2019. The immunosensor analyzed serum granzyme B levels, and their association with lung cancer detection was evaluated with machine learning models. Results: Serum granzyme B levels were assessed in samples from patients with lung cancer and healthy individuals. Granzyme B testing showed 100% sensitivity, 80% specificity, and an area under the curve of 0.938 for lung cancer detection. After combining granzyme B testing with clinical predictors such as age, smoking status, or pack-years, results from the five-fold cross-validation with random forest model improved diagnostic accuracy of 92.1%, with a sensitivity, specificity, and area under the curve of 92.0%, 92.1%, and 0.977, respectively. Conclusions: This feasibility study suggested that granzyme B may be utilized to detect lung cancer.

Indexed as

diagnosisgranzyme BimmunosensorLung cancerscreening

Identifiers

PMID35813317
PMCPMC9263765
OpenAlexW4285023703

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.