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Serum microRNA Biomarkers for Detection of Non-Small Cell Lung Cancer

Overview of attention for article published in PLOS ONE, February 2012
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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8 X users
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2 patents

Citations

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161 Dimensions

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151 Mendeley
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Title
Serum microRNA Biomarkers for Detection of Non-Small Cell Lung Cancer
Published in
PLOS ONE, February 2012
DOI 10.1371/journal.pone.0032307
Pubmed ID
Authors

Patrick T. Hennessey, Tiffany Sanford, Ashish Choudhary, Wojciech W. Mydlarz, David Brown, Alex Tamas Adai, Michael F. Ochs, Steven A. Ahrendt, Elizabeth Mambo, Joseph A. Califano

Abstract

Non small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality world-wide and the majority of cases are diagnosed at late stages of disease. There is currently no cost-effective screening test for NSCLC, and the development of such a test is a public health imperative. Recent studies have suggested that chest computed tomography screening of patients at high risk of lung cancer can increase survival from disease, however, the cost effectiveness of such screening has not been established. In this Phase I/II biomarker study we examined the feasibility of using serum miRNA as biomarkers of NSCLC using RT-qPCR to examine the expression of 180 miRNAs in sera from 30 treatment naive NSCLC patients and 20 healthy controls. Receiver operating characteristic curves (ROC) and area under the curve were used to identify differentially expressed miRNA pairs that could distinguish NSCLC from healthy controls. Selected miRNA candidates were further validated in sera from an additional 55 NSCLC patients and 75 healthy controls. Examination of miRNA expression levels in serum from a multi-institutional cohort of 50 subjects (30 NSCLC patients and 20 healthy controls) identified differentially expressed miRNAs. A combination of two differentially expressed miRNAs miR-15b and miR-27b, was able to discriminate NSCLC from healthy controls with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 100% in the training set. Upon further testing on additional 130 subjects (55 NSCLC and 75 healthy controls), this miRNA pair predicted NSCLC with a specificity of 84% (95% CI 0.73-0.91), sensitivity of 100% (95% CI; 0.93-1.0), NPV of 100%, and PPV of 82%. These data provide evidence that serum miRNAs have the potential to be sensitive, cost-effective biomarkers for the early detection of NSCLC. Further testing in a Phase III biomarker study in is necessary for validation of these results.

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X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
Spain 1 <1%
China 1 <1%
Belgium 1 <1%
Unknown 147 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 37 25%
Student > Ph. D. Student 28 19%
Student > Master 15 10%
Student > Bachelor 13 9%
Student > Doctoral Student 10 7%
Other 26 17%
Unknown 22 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 40 26%
Biochemistry, Genetics and Molecular Biology 29 19%
Medicine and Dentistry 29 19%
Engineering 5 3%
Nursing and Health Professions 3 2%
Other 16 11%
Unknown 29 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 22 August 2023.
All research outputs
#4,222,009
of 23,510,717 outputs
Outputs from PLOS ONE
#63,824
of 201,403 outputs
Outputs of similar age
#26,722
of 156,869 outputs
Outputs of similar age from PLOS ONE
#766
of 3,544 outputs
Altmetric has tracked 23,510,717 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 201,403 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.3. This one has gotten more attention than average, scoring higher than 68% 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 156,869 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 3,544 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.