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Concordance analysis of methylation biomarkers detection in self-collected and physician-collected samples in cervical neoplasm

Overview of attention for article published in BMC Cancer, May 2015
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Title
Concordance analysis of methylation biomarkers detection in self-collected and physician-collected samples in cervical neoplasm
Published in
BMC Cancer, May 2015
DOI 10.1186/s12885-015-1411-x
Pubmed ID
Authors

Cheng-Chang Chang, Rui-Lan Huang, Yu-Ping Liao, Po-Hsuan Su, Yaw-Wen Hsu, Hui-Chen Wang, Chau-Yang Tien, Mu-Hsien Yu, Ya-Wen Lin, Hung-Cheng Lai

Abstract

Non-attendance at gynecological clinics is a major limitation of cervical cancer screening and self-collection of samples may improve this situation. Although HPV testing of self-collected vaginal samples is acceptable, the specificity is inadequate. The current focus is increasing self-collection of vaginal samples to minimize clinic visits. In this study, we analyzed the concordance and clinical performance of DNA methylation biomarker (PAX1, SOX1, and ZNF582) detection in self-collected vaginal samples and physician-collected cervical samples for the identification of cervical neoplasm. We enrolled 136 cases with paired methylation data identified from abnormal Pap smears (n = 126) and normal controls (n = 10) regardless of HPV status at gynecological clinics. The study group comprised 37 cervical intraepithelial neoplasm I (CIN1), 23 cervical intraepithelial neoplasm II (CIN2), 16 cervical intraepithelial neoplasm III (CIN3), 30 carcinoma in situ (CIS), 13 squamous cell carcinomas (SCCs) and seven adenocarcinomas (ACs)/adenosquamous carcinomas (ASCs). PAX1, SOX1 and ZNF582 methylation in study samples was assessed by real-time quantitative methylation-specific polymerase chain reaction analysis. We generated methylation index cutoff values for the detection of CIN3+ in physician-collected cervical samples for analysis of the self-collected group. Concordance between the physician-collected and self-collected groups was evaluated by Cohen's Kappa. Sensitivity, specificity and area under curve (AUC) were calculated for detection of CIN3+ lesions. Finally, we produced an optimal cutoff value with the best sensitivity from the self-collected groups. We generated a methylation index cutoff value from physician-collected samples for detection of CIN3+. There were no significant differences in sensitivity, specificity of PAX1, SOX1 and ZNF582 between the self-collected and physician-collected groups. The methylation status of all three genes in the normal control samples, and the CIN 1, CIN2, CIN3, CIS, ACs/ASCs and SCC samples showed reasonable to good concordance between the two groups (κ = 0.443, 0.427, and 0.609 for PAX1, SOX1, and ZNF582, respectively). In determining the optimal cutoff values from the self-collected group, ZNF582 showed the highest sensitivity (0.77; 95%CI, 0.65-0.87) using a cutoff value of 0.0204. Methylation biomarker analysis of the three genes for detection of CIN3+ lesions shows reasonable to good concordance between the self-collected and physician-collected samples. Therefore, self-collection of samples could be adopted to decrease non-attendance and improve cervical screening.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 16 21%
Student > Master 10 13%
Researcher 8 11%
Student > Ph. D. Student 8 11%
Student > Postgraduate 5 7%
Other 9 12%
Unknown 19 25%
Readers by discipline Count As %
Medicine and Dentistry 26 35%
Biochemistry, Genetics and Molecular Biology 9 12%
Nursing and Health Professions 7 9%
Agricultural and Biological Sciences 5 7%
Immunology and Microbiology 2 3%
Other 6 8%
Unknown 20 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 05 February 2016.
All research outputs
#19,015,492
of 23,577,654 outputs
Outputs from BMC Cancer
#5,573
of 8,530 outputs
Outputs of similar age
#194,480
of 267,561 outputs
Outputs of similar age from BMC Cancer
#163
of 217 outputs
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