Screening history in women with cervical cancer in a Danish population-based screening program

Kirschner, Benny; Poll, Susanne; Rygaard, Carsten; Wåhlin, Anne; Junge, Jette

doi:10.1016/j.ygyno.2010.09.021

Cited by 47 publications

(48 citation statements)

References 23 publications

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“…However, if it is not performed in accordance with the quality control standards, the rate of false-negative results is high [1,2,3,4]. …”

Section: Introductionmentioning

confidence: 99%

Internal Quality Control for Cervical Cytopathology: Comparison of Potential False-Negatives Detected at Rapid Prescreening and at 100% Rapid Review

Tavares¹,

Souza²,

Manrique³

et al. 2014

Acta Cytologica

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Objective: To evaluate the performance of rapid prescreening (RPS) and 100% rapid review (RR-100%) as internal quality control (IQC) methods assessed by outcome at colposcopy, histopathology and repeat cytopathology for cases with false-negative results on cervical cytopathology at routine screening (RS). Study Design: Out of 12,208 cytology smears analyzed, 900 were abnormal. Of these, 656 were identified at RS, and 244 were false-negative, with 90.2% identified at RPS and 57.4% at RR-100%. Of the 900 abnormal cases, 436 were submitted for additional testing. Results: Of the 244 women with cytopathological abnormalities identified only by the IQC methods, 114 had supplementary examinations: 35 were submitted for colposcopy, 22 for biopsy and 99 for repeat cytopathology. The sensitivity of RPS for the detection of abnormalities identified on colposcopy, histopathology and repeat cytopathology was 87.5% (95% CI 67.6-97.3), 82.4% (95% CI 56.6-96.2) and 95.7% (95% CI 85.2-99.5), respectively. The sensitivity of RR-100% was 54.2% (95% CI 32.8-74.4), 52.9% (95% CI 27.8-77.0) and 47.8% (95% CI 32.9-63.1), respectively. RPS was more sensitive than RR-100% when compared to the findings on colposcopy (p = 0.011) and repeat cytopathology (p = 0.000). When compared to colposcopy, histopathology and repeat cytopathology, the sensitivity of RS was 83.2% (95% CI 76.1-88.9), 85.7% (95% CI 78.1-91.5) and 73.3% (95% CI 66.0-79.7), respectively. Conclusion: RPS performed better than RR-100% when compared to the results of colposcopy and repeat cytopathology.

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“…However, if it is not performed in accordance with the quality control standards, the rate of false-negative results is high [1,2,3,4]. …”

Section: Introductionmentioning

confidence: 99%

Internal Quality Control for Cervical Cytopathology: Comparison of Potential False-Negatives Detected at Rapid Prescreening and at 100% Rapid Review

Tavares¹,

Souza²,

Manrique³

et al. 2014

Acta Cytologica

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“…Although the proportion of women who are never or underscreened is generally not very large in countries with cervical cancer screening (56,63,64), they account for a large proportion of SCC cases (13,51,65,66). In our simulations, vaccination did not fully eliminate absolute SCC incidence rate differences between groups with different screening participation.…”

Section: Discussionmentioning

confidence: 77%

Changing Inequalities in Cervical Cancer: Modeling the Impact of Vaccine Uptake, Vaccine Herd Effects, and Cervical Cancer Screening in the Post-Vaccination Era

Malagón

Drolet

Boily

et al. 2015

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background: Inequalities in cervical cancer may be increased following mass vaccination against the human papillomavirus (HPV) if girls with low vaccine uptake also have low future participation in cervical cancer screening. We evaluated how vaccine uptake distribution affects inequalities in squamous cell carcinoma (SCC) incidence between groups with different screening participation.Methods: We used an individual-based transmission dynamic model of HPV infection and disease (HPV-ADVISE). Females were stratified by routine screening frequency. We modeled the impact of vaccination on SCC incidence rate differences (absolute inequality) and incidence rate ratios (relative inequality) between women who have routine screening intervals of <5 years (frequently screened), !5 years (underscreened), and who are never screened. We compared simulations with uniform vaccine uptake with scenarios with unequal vaccine uptake, in which never and underscreened

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“…Currently, the term squamous intraepithelial lesion (SIL) indicate the presence of abnormal tissue that can be associated with two diagnostics: a) low-grade SIL (LSIL), which presents early changes in the size, shape and number of cells -precancerous low-grade lesions are also known as mild dysplasia or cervical intraepithelial neoplasia 1 (CIN 1); b) high-grade SIL (HSIL) indicates that the precancerous changes are more severe, with displasia, and potential for the development of cervical cancer. For that reason, an adequate analysis of the specimens, including inspection of microstructure of the cervix cells and ancyllary cells is indispensable [10], [3]. The Papanicolau test allows the discrimination between precancerous conditions and cancer of the cervix, however the cells on the surface of the cervix sometimes appear abnormal but may not cancerous.…”

Section: Previous Workmentioning

confidence: 99%

“…This test allows detection of pre-neoplasic lesions, however the efficiency of the method is still contradictory because of the number of false-negatives. Therefore, several women that are diagnosed as presenting healthy cervix cells have developed cervical cancer [3].…”

Section: Introductionmentioning

confidence: 99%

Automated Pap Smear Cell Analysis: Optimizing the Cervix Cytological Examination

Ushizima

Gomes

Carneiro

et al. 2013

2013 12th International Conference on Machine Learning and Applications

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Cervical cancer screening is one of the most widespread tests in the world, and the acquisition of digital images of Pap smears is about to become part of the laboratories routine. The ability to collect these standard exam data has increased drastically, and available tools for image analysis and quantification are not accurate and/or customized enough to deliver relevant information about the image content. Aiming at enabling pathology laboratories to deal with large amounts of digitized Pap smears slides, we propose to design computer vision algorithms for quantitative analysis and pattern recognition from 2D images. The goal is to bring high technology to laboratories focused on underserved communities of women for the prevention of cervical cancer; in these public health care institutions, there is no perspective of using "omics" data in the medium term, but only clinical annotations and Pap smears slides. Here, we describe our project and propose computational tools adapted to this application, addressing the needs from end-to-end, including enhancement, noise minimization, segmentation of regions of interest, extraction and classification of objects.

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Screening history in women with cervical cancer in a Danish population-based screening program

Cited by 47 publications

References 23 publications

Internal Quality Control for Cervical Cytopathology: Comparison of Potential False-Negatives Detected at Rapid Prescreening and at 100% Rapid Review

Internal Quality Control for Cervical Cytopathology: Comparison of Potential False-Negatives Detected at Rapid Prescreening and at 100% Rapid Review

Changing Inequalities in Cervical Cancer: Modeling the Impact of Vaccine Uptake, Vaccine Herd Effects, and Cervical Cancer Screening in the Post-Vaccination Era

Automated Pap Smear Cell Analysis: Optimizing the Cervix Cytological Examination

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