ArticleBMC cancer2021
Development and validation of a clinical prediction model for endocervical curettage decision-making in cervical lesions.
Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 23 citations in OpenAlex.
- Predicting Sarcopenia in Peritoneal Dialysis Patients: A Multimodal Ultrasound-Based Logistic Regression Analysis and Nomogram Model.Diagnostics (Basel, Switzerland) · 2025Article
- Yield of endocervical curettage in detecting cervical intraepithelial neoplasia grade 2 or higher during colposcopy: A prospective, cross-sectional study.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025Article
- Development and validation of a predictive model for the risk of endocervical curettage positivity.Frontiers in oncology · 2025Article
- Article
- PAX1 methylation as a robust predictor: developing and validating a nomogram for assessing endocervical curettage (ECC) necessity in human papillomavirus16/18-positive women undergoing colposcopy.Clinical epigenetics · 2024Article
- The Effect of Random Biopsy and Endo-Cervical Curettage in Diagnosis of Precancerous Cervical Lesions in Women With Normal Colposcopy.Journal of family & reproductive health · 2024Article
- The value of endocervical curettage for diagnosis of cervical precancers or worse at colposcopy of women with atypical glandular cells cytology.Frontiers in medicine · 2024Article
- Endocervical curettage for diagnosing high-grade squamous intraepithelial lesions or worse in women with type 3 transformation zone lesions: a retrospective, observational study.BMC women's health · 2023Observational
- CIN2 + detection in high-risk HPV patients with no or minor cervical cytologic abnormalities: a clinical approach validated by machine learning.Archives of gynecology and obstetrics · 2023Article
- Developing a predictive nomogram for colposcopists: a retrospective, multicenter study of cervical precancer identification in China.BMC cancer · 2023Article
- Development and validation of a predictive model for endocervical curettage in patients referred for colposcopy: A multicenter retrospective diagnostic study in China.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2022Article
- Risk Factors of Positive Endocervical Curettage and Predictive Model Construction Based on Primary Human Papillomavirus Screening.Technology in cancer research & treatmentArticle
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the absence of practical and reliable predictors for whether the endocervical curettage (ECC) procedure should be performed, decisions regarding patient selection are usually based on the colposcopists' clinical judgment instead of evidence. We aimed to develop and validate a practical prediction model that uses available information to reliably estimate the need to perform ECC in patients suspected of having cervical lesions.
methodsIn this retrospective study, 2088 patients who underwent colposcopy, colposcopically directed biopsy (CDB) and ECC procedures between September 2019 and September 2020 at the Second Hospital of Shanxi Medical University were included. The data were analyzed with univariate and multivariable logistic regression. Least absolute shrinkage and selection operator (LASSO) was used to select predictors for ECC positivity. The ECC prediction model was presented as a nomogram and evaluated in terms of discrimination and calibration. Furthermore, this model was validated internally with cross-validation and bootstrapping.
resultsSignificant trends were found for ECC positivity with increasing age (P = 0.001), menopause (P = 0.003), Human papillomavirus (HPV) status (P < 0.001), severity of ThinPrep Cytological Test (TCT) (P < 0.001), original squamous epithelium ectopia (P = 0.037) and colposcopy impression (P < 0.001) by multivariable logistic regression analysis. The ECC prediction model was developed based on the following predictors: age, menopause, symptom of contact bleeding, severity of TCT, HPV status, cervix visibility, original squamous epithelium ectopia, acetowhite changes and colposcopic impression. This model had satisfactory calibration and good discrimination, with an area under the receiver operator characteristic curve (AUC) of 0.869 (95% confidence interval 0.849 to 0.889).
conclusionsA readily applicable clinical prediction model was constructed to reliably estimate the probability of ECC positivity in patients suspicious of having cervical lesions, which may help clinicians make decisions regarding the ECC procedure and possibly prevent adverse effects.
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