Evidence map›Paper›PMID 41786899›Full record

ArticleScientific reports2026

GC-IMS-based analysis of serum volatile organic compounds for diagnosis of gastric cancer.

Yuxiao Zhao, Yueming Xin, Mai Mao, Xin Zheng, Fuwei Liang, Xin Zhang, Chengxi Sun, Tong Liu, Nannan Ning, Helgi B Schiöth and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2026. 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

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

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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.

  1. Article
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

12 authors.

Yuxiao Zhao *Department of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, 250012, China.
Yueming Xin *Department of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, 250012, China.
Mai Mao *Department of Blood Transfusion, Qilu Hospital of Shandong University, Jinan, 250012, China.
Xin ZhengDepartment of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, 250031, China.
Fuwei LiangDepartment of Clinical Laboratory, The Fifth People's Hospital of Jinan, Jinan, 250022, China.
Xin ZhangDepartment of Blood Transfusion, Qilu Hospital of Shandong University, Jinan, 250012, China.
Chengxi SunDepartment of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, 250012, China.
Tong LiuDepartment of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, 250012, China.
Nannan NingDepartment of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, 250012, China.
Helgi B SchiöthDepartment of Surgical Sciences, Functional Pharmacology and Neuroscience Biomedicinskt Centrum, Uppsala University, Husargatan 3, 751 24, Uppsala, Sweden.
Yanli ZhangDepartment of Clinical Laboratory, Shandong Provincial Third Hospital, Shandong University, Jinan, 250031, China. zyl_2960@126.com.
Yi ZhangDepartment of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, 250012, China. yizhang@sdu.edu.cn.

Funding

National Natural Science Foundation of China 82572647Natural Science Foundation of Shandong Province ZR2021MH110Taishan scholar program of Shandong Province tsqn202306346Taishan scholar program of Shandong Province tstp20221156
6 · The paper itself

Abstract

Gastric cancer detection remains challenging due to the lack of noninvasive early diagnostic tools. This study investigates profiling of serum volatile organic compounds (VOCs) using gas chromatography-ion mobility spectrometry (GC-IMS) for gastric cancer screening. Serum samples were obtained from 277 participants, including 123 patients with gastric cancer, 38 patients with precancerous diseases (PD), and 116 healthy controls (HC). In the model development group, Kruskal-Wallis tests showed that the levels of 19 VOCs differed significantly among gastric cancer, PD, and HC groups (p < 0.05). Based on the VOCs that differed significantly, a support vector machine (SVM) model achieved the best performance among the six models tested. Using importance ranking and forward selection, 11 VOCs were selected for the final model, achieving 96.4% accuracy in the validation set and 92.9% in an independent test set, showing higher diagnostic accuracy than the traditional tumor marker carcinoembryonic antigen. The model also achieved 100% sensitivity and > 90% specificity for detecting early gastric cancer in both the validation and test sets. Collectively, our findings suggest that GC-IMS-based serum VOC profiling may offer a potential noninvasive approach for gastric cancer detection.

Indexed as

Biomarkers, TumorStomach NeoplasmsVolatile Organic CompoundsAdultAgedCase-Control StudiesEarly Detection of CancerFemaleGas Chromatography-Mass SpectrometryHumansIon Mobility SpectrometryMaleMiddle AgedSensitivity and SpecificitySupport Vector MachineBiomarkers, TumorVolatile Organic CompoundsGas chromatography-ion mobility spectrometryGastric cancerSerumVolatile organic compounds

Identifiers

PMID41786899
PMCPMC12988151

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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.