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在一个未进行筛查的高风险社区中,使用PAPNET系统对原发性宫颈癌筛查进行模拟。

Simulation of primary cervical cancer screening by the PAPNET system in an unscreened, high-risk community.

作者信息

Michelow P M, Hlongwane N F, Leiman G

机构信息

Department of Anatomical Pathology, School of Pathology, South African Institute for Medical Research, Johannesburg, South Africa.

出版信息

Acta Cytol. 1997 Jan-Feb;41(1):88-92. doi: 10.1159/000332311.

DOI:10.1159/000332311
PMID:9022732
Abstract

OBJECTIVE

To evaluate the performance of the PAPNET system as a primary cervical cancer screening modality in an unscreened population with a high prevalence of cervical cancer and its precursor lesions.

STUDY DESIGN

Consecutive cervical smears from 3,106 women, screened and reported in the usual manner, were submitted for analysis by the PAPNET system. The original manual screening diagnoses were compared with those obtained by PAPNET analysis. By inclusion of normal and abnormal smears, this evaluation not only provided quality assurance for the laboratory but also simulated primary screening by automation.

RESULTS

Comparison of the two methods of screening showed statistically significant superiority of the PAPNET over conventional screening (89.6% vs. 63.8%, respectively) in low grade lesions, including atypical squamous and atypical glandular cells of uncertain significance (ASCUS and AGUS, respectively) and low grade squamous intraepithelial lesion. Conversely, there was no significant difference between PAPNET and manual detection (87.5% vs. 94.6%) for more significant abnormalities, including high grade squamous intraepithelial lesions and invasive carcinoma.

CONCLUSION

The PAPNET system, which would probably not be affordable as a quality assurance modality only in the public health sector of this country, was shown to be more than sufficiently effective as a primary screening method for the large numbers of women likely to undergo cervical cancer screening in anticipated mass population programs.

摘要

目的

评估PAPNET系统作为宫颈癌初筛方式在宫颈癌及其癌前病变患病率较高的未筛查人群中的表现。

研究设计

以常规方式进行筛查和报告的3106名女性的连续宫颈涂片,被提交给PAPNET系统进行分析。将最初的手工筛查诊断结果与PAPNET分析得出的结果进行比较。通过纳入正常和异常涂片,该评估不仅为实验室提供了质量保证,还模拟了自动化初筛。

结果

两种筛查方法的比较显示,在低级别病变中,包括意义不明确的非典型鳞状细胞和非典型腺细胞(分别为ASCUS和AGUS)以及低级别鳞状上皮内病变,PAPNET在统计学上显著优于传统筛查(分别为89.6%和63.8%)。相反,对于更严重的异常情况,包括高级别鳞状上皮内病变和浸润癌,PAPNET与手工检测之间没有显著差异(分别为87.5%和94.6%)。

结论

PAPNET系统在该国公共卫生部门仅作为质量保证方式可能难以负担得起,但作为一种初筛方法,对于预期大规模人群项目中可能接受宫颈癌筛查的大量女性而言,已显示出足够的有效性。

相似文献

1
Simulation of primary cervical cancer screening by the PAPNET system in an unscreened, high-risk community.在一个未进行筛查的高风险社区中,使用PAPNET系统对原发性宫颈癌筛查进行模拟。
Acta Cytol. 1997 Jan-Feb;41(1):88-92. doi: 10.1159/000332311.
2
Negative cervical smears before CIN 3/carcinoma. Reevaluation with the PAPNET Testing System.CIN 3/癌之前的宫颈涂片阴性。采用PAPNET检测系统进行重新评估。
Acta Cytol. 1997 Jan-Feb;41(1):74-8. doi: 10.1159/000332308.
3
Quality assurance in cervical cytology screening. Comparison of rapid rescreening and the PAPNET Testing System.宫颈细胞学筛查中的质量保证。快速重新筛查与PAPNET检测系统的比较。
Acta Cytol. 1997 Jan-Feb;41(1):79-81. doi: 10.1159/000332309.
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Consistency of a double PAPNET scan of cervical smears.
Acta Cytol. 1997 Jan-Feb;41(1):82-7. doi: 10.1159/000332310.
5
Clinical validation of interactive cytologic screening. Automating the search, not the interpretation.
Acta Cytol. 1997 Jan-Feb;41(1):93-7. doi: 10.1159/000332312.
6
PAPNET-assisted rescreening of cervical smears: cost and accuracy compared with a 100% manual rescreening strategy.PAPNET辅助的宫颈涂片复查:与100%人工复查策略相比的成本和准确性
JAMA. 1998 Jan 21;279(3):235-7. doi: 10.1001/jama.279.3.235.
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PAPNET Testing System. Technical update.PAPNET检测系统。技术更新。
Acta Cytol. 1997 Jan-Feb;41(1):65-73. doi: 10.1159/000332307.
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Evaluation of the PAPNET system in a general pathology service.PAPNET系统在常规病理学服务中的评估。
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Detection of unsuspected abnormalities by PAPNET-assisted review.
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PAPNET testing for HSILs. The few cell/small cell challenge.用于高级别鳞状上皮内病变(HSILs)的PAPNET检测。少量细胞/小细胞难题。
Acta Cytol. 1998 Jan-Feb;42(1):253-9. doi: 10.1159/000331554.

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Diagnosis of Cervical Cancer and Pre-Cancerous Lesions by Artificial Intelligence: A Systematic Review.人工智能用于宫颈癌及癌前病变的诊断:一项系统评价
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