Evidence map›Paper›PMID 40731391›Full record

ArticleBMC cancer2025

Assessing the risk of undetected cervical cancer in women with a biopsy of high-grade cervical intraepithelial neoplasia: predictive value of cytology and endocervical curettage (ECC).

Xiaoxi Yao, Mingrong Qie, Leni Kang, Mengyao Li, Qingyu Liu, Xiao Liang, Guangdong Liao

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Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

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7 authors.

Xiaoxi YaoDepartment of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.
Mingrong QieDepartment of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.
Leni KangNational Office for Maternal and Child Health Surveillance, West China Second University Hospital, Sichuan University, Chengdu, China.
Mengyao LiDepartment of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.
Qingyu LiuDepartment of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China.
Xiao LiangFaculty of Business and Economics, University of Hong Kong, Hong Kong, SAR, China.
Guangdong LiaoDepartment of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, China. 5135662@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify risk factors for a final diagnosis of cervical cancer in patients initially diagnosed with high-grade cervical intraepithelial neoplasia and to evaluate a combined Cytology-Endocervical Curettage (ECC) index for predicting cancer risk.

methodsThis retrospective study included 11,651 patients at West China Second University Hospital (WCSUH) with biopsy-confirmed high-grade cervical intraepithelial neoplasia over a five-year period. Patients were divided into two groups based on whether they ultimately received a diagnosis of cervical cancer following surgery. Multivariate logistic regression was used to identify independent risk factors, and receiver operating characteristic (ROC) curves were constructed to assess the performance of the Cytology-ECC index.

resultsOf the 11,651 patients, 229 were subsequently diagnosed with cervical cancer. Multivariate analysis identified age (OR = 1.10, 95% CI: 1.06-1.14), abnormal vaginal bleeding (OR = 2.94, 95% CI: 1.75-4.92), human papillomavirus (HPV)16/18 infection (OR = 2.56, 95% CI: 1.62-4.03), single HPV type infection (OR = 1.68, 95% CI: 1.03-2.75), atypical squamous cells, cannot exclude HSIL (ASC-H) (OR = 3.77, 95% CI: 1.68-8.45), high-grade squamous intraepithelial lesion (HSIL) (OR = 4.65, 95% CI: 2.16-10.05), and endocervical glandular involvement (OR = 1.59, 95% CI: 1.01-2.49) as independent risk factors (all P < 0.05). The Cytology-ECC index demonstrated a predictive accuracy with an area under the curve (AUC) of 0.787, outperforming cytology or ECC alone.

conclusionsAge, abnormal vaginal bleeding, HPV16/18, single HPV type infection, ASC-H, HSIL, and endocervical glandular involvement were independent predictors of cervical cancer in patients with an initial biopsy of high-grade cervical intraepithelial neoplasia. The combined Cytology-ECC index showed enhanced predictive value in clinical decision-making and may aid in earlier identification of patients at elevated risk for undetected invasive disease.

Indexed as

Uterine Cervical DysplasiaUterine Cervical NeoplasmsAdultAgedBiopsyCervix UteriChinaCurettageFemaleHumansMiddle AgedNeoplasm GradingPapillomavirus InfectionsRetrospective StudiesRisk FactorsROC CurveCervical cancerCervical intraepithelial neoplasiaColposcopyCytologyEndocervical curettageMisdiagnosis

Identifiers

PMID40731391
PMCPMC12309198

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.