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ORIGINAL RESEARCH article

Front. Oncol.

Sec. Gynecological Oncology

Volume 15 - 2025 | doi: 10.3389/fonc.2025.1559087

Development and Validation of a Predictive Model for the Risk of Endocervical Curettage Positivity

Provisionally accepted
Fang Feng Fang Feng Hui-Hui Tuo Hui-Hui Tuo Jin-Meng Yao Jin-Meng Yao Wei-hong Wang Wei-hong Wang Feng-lan Guo Feng-lan Guo Rui-Fang An Rui-Fang An *
  • The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

The final, formatted version of the article will be published soon.

    Objective: This study aimed to analyze the clinical characteristics of patients undergoing endocervical curettage (ECC), identify factors influencing ECC positivity, and develop a predictive model to assess the risk of positive ECC results. The goal was to assist clinicians in making ECC decisions and reduce missed diagnoses of cervical lesions. Methods: A retrospective analysis was performed on 953 patients who underwent colposcopically directed biopsy and ECC at the gynecology clinic of the First Affiliated Hospital of Xi'an Jiaotong University between October 2021 and September 2023 due to abnormal screening results. Univariate and multivariate logistic regression analyses were used to identify predictive factors for ECC positivity. An individualized prediction model for ECC positivity risk was developed using R Studio, and the model was subsequently evaluated and validated. Results: Among the 953 women, the ECC positive rate was 31.48% (300/953). Logistic regression analysis identified age (P<0.001), human papillomavirus (HPV) status (P<0.01), cytology results (P<0.05), acetowhite changes (P<0.01), Lugol staining (P<0.01), and colposcopic impression (P<0.01) as independent predictors of ECC positivity. These factors were incorporated into the prediction model for ECC positivity risk. The area under the receiver operating characteristic curve (AUC) of the model was 0.792 (95% CI:0.760-0.824). The Hosmer-Lemeshow test yielded a χ 2 value of 10.489 (P=0.2324), and the calibration and clinical decision curves demonstrated that the model exhibited satisfactory calibration and clinical utility. Conclusions: The clinical prediction model developed in this study demonstrated good discrimination, calibration, and clinical utility. It can be used to evaluate the risk of ECC positivity in patients undergoing colposcopy, reduce missed diagnoses of cervical lesions, and aid clinicians in making ECC decisions.

    Keywords: Endocervical curettage, cervical lesions, Prediction model, nomogram, clinical decision-making

    Received: 11 Jan 2025; Accepted: 03 Mar 2025.

    Copyright: © 2025 Feng, Tuo, Yao, Wang, Guo and An. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Rui-Fang An, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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