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Dove Medical Press

Serum biomarker panels for diagnosis of gastric cancer

Overview of attention for article published in OncoTargets and therapy, April 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

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2 X users
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1 patent
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1 Facebook page
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1 Google+ user

Citations

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38 Dimensions

Readers on

mendeley
34 Mendeley
Title
Serum biomarker panels for diagnosis of gastric cancer
Published in
OncoTargets and therapy, April 2016
DOI 10.2147/ott.s86139
Pubmed ID
Authors

Weihua Tong, Fei Ye, Liang He, Lifeng Cui, Miao Cui, Yuan Hu, Wei Li, Jing Jiang, David Y Zhang, Jian Suo

Abstract

Currently, serum biomarkers that are sufficiently sensitive and specific for early detection and risk classification of gastric adenocarcinomas are not known. In this study, ten serum markers were assessed using the Luminex system and enzyme-linked immunosorbent assay for the diagnosis of gastric cancer and analysis of the relation between prognosis and metastases. A training set consisting of 228 gastric adenocarcinoma and 190 control samples was examined. A Luminex multiplex panel with nine biomarkers, consisting of three proteins discovered through our previous studies and six proteins previously reported to be cancer-associated, was constructed. One additional biomarker was detected using a commercial kit containing EDTA. Logistic regression, random forest (RF), and support vector machine (SVM) were used to identify the panel of discriminatory biomarkers in the training set. After selecting five proteins as candidate biomarkers, multivariate classification analyses were used to identify algorithms for diagnostic biomarker combinations. These algorithms were independently validated using a set of 57 gastric adenocarcinoma and 48 control samples. Serum pepsinogen I, serum pepsinogen II, A Disintegrin And Metalloproteinase domain-containing protein 8 (ADAM8), vascular endothelial growth factor (VEGF), and serum IgG to Helicobacter pylori were selected as classifiers in the three algorithms. These algorithms differentiated between the majority of gastric adenocarcinoma and control serum samples in the training/test set with high accuracy (RF 79.0%, SVM 83.8%, logistic regression 76.2%). These algorithms also differentiated the samples in the validation set (accuracy: RF 82.5%, SVM 86.1%, logistic regression 78.7%). A panel of combinatorial biomarkers comprising VEGF, ADAM8, IgG to H. pylori, serum pepsinogen I, and pepsinogen II were developed. The use of biomarkers is a less invasive method for the diagnosis of gastric adenocarcinoma. They may supplement clinical gastroscopic evaluation of symptomatic gastric cancer patients and enhance the diagnostic accuracy.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 15%
Other 4 12%
Student > Master 4 12%
Researcher 4 12%
Student > Postgraduate 2 6%
Other 5 15%
Unknown 10 29%
Readers by discipline Count As %
Medicine and Dentistry 9 26%
Biochemistry, Genetics and Molecular Biology 5 15%
Agricultural and Biological Sciences 3 9%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Business, Management and Accounting 1 3%
Other 2 6%
Unknown 13 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 June 2022.
All research outputs
#6,823,235
of 25,584,565 outputs
Outputs from OncoTargets and therapy
#335
of 2,967 outputs
Outputs of similar age
#89,892
of 315,181 outputs
Outputs of similar age from OncoTargets and therapy
#18
of 128 outputs
Altmetric has tracked 25,584,565 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,967 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 315,181 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 128 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.