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Combined clinical and genetic testing algorithm for cervical cancer diagnosis

Overview of attention for article published in Clinical Epigenetics, June 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

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1 blog
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9 X users

Citations

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33 Dimensions

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79 Mendeley
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Title
Combined clinical and genetic testing algorithm for cervical cancer diagnosis
Published in
Clinical Epigenetics, June 2016
DOI 10.1186/s13148-016-0232-3
Pubmed ID
Authors

Yu-Ligh Liou, Tao-Lan Zhang, Tian Yan, Ching-Tung Yeh, Ya-Nan Kang, Lanqin Cao, Nayiyuan Wu, Chi-Feng Chang, Huei-Jen Wang, Carolyn Yen, Tang-Yuan Chu, Yi Zhang, Yu Zhang, Honghao Zhou

Abstract

Opportunistic screening in hospitals is widely used to effectively reduce the incidence rate of cervical cancer in China and other developing countries. This study aimed to identify clinical risk factor algorithms that combine gynecologic examination and molecular testing (paired box gene 1 (PAX1) or zinc finger protein 582 (ZNF582) methylation or HPV16/18) results to improve diagnostic accuracy. The delta Cp of methylated PAX1 and ZNF582 was obtained via quantitative methylation-specific PCR in a training set (57 CIN2- and 43 cervical intraepithelial neoplasia ≥grade 3 (CIN3+) women), and the individual and combination gene sensitivities and specificities were determined. The detection accuracy of three algorithms combining gynecologic findings and genetic test results was then compared in a randomized case-control study comprising 449 women referred for colposcopic examination by gynecologists in the outpatient department of Xiangya Hospital between November 2011 and March 2013. Significant association was observed between CIN3+ and methylated PAX1 or ZNF582 in combination with HPV16/18 (OR:15.52, 95 % CI:7.73-31.18). The sensitivities and specificities of methylated PAX1 or ZNF582 combined with HPV16/18 for CIN3+ women were 89.2 and 76.0 %, or 85.4 and 80.1 %, respectively. Of the three algorithms applied to cohort data and validated in the study, two indicated 100 % sensitivity in detecting cervical cancer and a low rate of referrals for colposcopy. These algorithms might contribute to precise and objective cervical cancer diagnostics in the outpatient departments of hospitals in countries with high mortality and low screening rates or areas with uneven resource distribution.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 20 25%
Student > Master 10 13%
Researcher 7 9%
Student > Ph. D. Student 7 9%
Student > Doctoral Student 5 6%
Other 7 9%
Unknown 23 29%
Readers by discipline Count As %
Medicine and Dentistry 28 35%
Biochemistry, Genetics and Molecular Biology 12 15%
Nursing and Health Professions 6 8%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Agricultural and Biological Sciences 2 3%
Other 9 11%
Unknown 20 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 07 January 2019.
All research outputs
#2,553,552
of 22,876,619 outputs
Outputs from Clinical Epigenetics
#153
of 1,259 outputs
Outputs of similar age
#47,188
of 345,197 outputs
Outputs of similar age from Clinical Epigenetics
#6
of 31 outputs
Altmetric has tracked 22,876,619 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,259 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has done well, scoring higher than 87% 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 345,197 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 86% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.