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01-12-2021 | Human Papillomavirus | Research article

Development of models for cervical cancer screening: construction in a cross-sectional population and validation in two screening cohorts in China

Authors: Zeni Wu, Tingyuan Li, Yongli Han, Mingyue Jiang, Yanqin Yu, Huifang Xu, Lulu Yu, Jianfeng Cui, Bin Liu, Feng Chen, Jian Yin, Xun Zhang, Qinjing Pan, Youlin Qiao, Wen Chen

Published in: BMC Medicine | Issue 1/2021

Abstract

Background

Current methods for cervical cancer screening result in an increased number of referrals and unnecessary diagnostic procedures. This study aimed to develop and evaluate a more accurate model for cervical cancer screening.

Methods

Multiple predictors including age, cytology, high-risk human papillomavirus (hrHPV) DNA/mRNA, E6 oncoprotein, HPV genotyping, and p16/Ki-67 were used for model construction in a cross-sectional population including women with normal cervix (N = 1085), cervical intraepithelial neoplasia (CIN, N = 279), and cervical cancer (N = 551) to predict CIN2+ or CIN3+. A base model using age, cytology, and hrHPV was calculated, and extended versions with additional biomarkers were considered. External validations in two screening cohorts with 3-year follow-up were further conducted (N_Cohort-I = 3179, N_Cohort-II = 3082).

Results

The base model increased the area under the curve (AUC, 0.91, 95% confidence interval [CI] = 0.88–0.93) and reduced colposcopy referral rates (42.76%, 95% CI = 38.67–46.92) compared to hrHPV and cytology co-testing in the cross-sectional population (AUC 0.80, 95% CI = 0.79–0.82, referrals rates 61.62, 95% CI = 59.4–63.8) to predict CIN2+. The AUC further improved when HPV genotyping and/or E6 oncoprotein were included in the base model. External validation in two screening cohorts further demonstrated that our models had better clinical performances than routine screening methods, yielded AUCs of 0.92 (95% CI = 0.91–0.93) and 0.94 (95% CI = 0.91–0.97) to predict CIN2+ and referrals rates of 17.55% (95% CI = 16.24–18.92) and 7.40% (95% CI = 6.50–8.38) in screening cohort I and II, respectively. Similar results were observed for CIN3+ prediction.

Conclusions

Compared to routine screening methods, our model using current cervical screening indicators can improve the clinical performance and reduce referral rates.

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Title: Development of models for cervical cancer screening: construction in a cross-sectional population and validation in two screening cohorts in China
Authors: Zeni Wu
Tingyuan Li
Yongli Han
Mingyue Jiang
Yanqin Yu
Huifang Xu
Lulu Yu
Jianfeng Cui
Bin Liu
Feng Chen
Jian Yin
Xun Zhang
Qinjing Pan
Youlin Qiao
Wen Chen
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Human Papillomavirus
Colposcopy
Cervical Cancer
Colposcopy
Cervical Cancer
Published in: BMC Medicine / Issue 1/2021
Electronic ISSN: 1741-7015
DOI: https://doi.org/10.1186/s12916-021-02078-2

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Development of models for cervical cancer screening: construction in a cross-sectional population and validation in two screening cohorts in China

Abstract

Background

Methods

Results

Conclusions

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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