Development and validation of a predictive model for the risk of endocervical curettage positivity
ObjectiveThis 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...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-03-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1559087/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849773687460331520 |
|---|---|
| author | Fang Feng Hui-hui Tuo Jin-meng Yao Wei-hong Wang Feng-lan Guo Rui-fang An |
| author_facet | Fang Feng Hui-hui Tuo Jin-meng Yao Wei-hong Wang Feng-lan Guo Rui-fang An |
| author_sort | Fang Feng |
| collection | DOAJ |
| description | ObjectiveThis 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.MethodsA 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.ResultsAmong 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 χ2 value of 10.489 (P=0.2324), and the calibration and clinical decision curves demonstrated that the model exhibited satisfactory calibration and clinical utility.ConclusionsThe 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. |
| format | Article |
| id | doaj-art-80221982bd4e461494e320398d9ba9b9 |
| institution | DOAJ |
| issn | 2234-943X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj-art-80221982bd4e461494e320398d9ba9b92025-08-20T03:01:58ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-03-011510.3389/fonc.2025.15590871559087Development and validation of a predictive model for the risk of endocervical curettage positivityFang Feng0Hui-hui Tuo1Jin-meng Yao2Wei-hong Wang3Feng-lan Guo4Rui-fang An5Department of Gynecology and Obstetrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaDepartment of Dermatology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaDepartment of Gynecology and Obstetrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaDepartment of Gynecology and Obstetrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaDepartment of Gynecology and Obstetrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaDepartment of Gynecology and Obstetrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, ChinaObjectiveThis 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.MethodsA 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.ResultsAmong 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 χ2 value of 10.489 (P=0.2324), and the calibration and clinical decision curves demonstrated that the model exhibited satisfactory calibration and clinical utility.ConclusionsThe 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.https://www.frontiersin.org/articles/10.3389/fonc.2025.1559087/fullendocervical curettagecervical lesionsprediction modelnomogramclinical decision-making |
| spellingShingle | Fang Feng Hui-hui Tuo Jin-meng Yao Wei-hong Wang Feng-lan Guo Rui-fang An Development and validation of a predictive model for the risk of endocervical curettage positivity Frontiers in Oncology endocervical curettage cervical lesions prediction model nomogram clinical decision-making |
| title | Development and validation of a predictive model for the risk of endocervical curettage positivity |
| title_full | Development and validation of a predictive model for the risk of endocervical curettage positivity |
| title_fullStr | Development and validation of a predictive model for the risk of endocervical curettage positivity |
| title_full_unstemmed | Development and validation of a predictive model for the risk of endocervical curettage positivity |
| title_short | Development and validation of a predictive model for the risk of endocervical curettage positivity |
| title_sort | development and validation of a predictive model for the risk of endocervical curettage positivity |
| topic | endocervical curettage cervical lesions prediction model nomogram clinical decision-making |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2025.1559087/full |
| work_keys_str_mv | AT fangfeng developmentandvalidationofapredictivemodelfortheriskofendocervicalcurettagepositivity AT huihuituo developmentandvalidationofapredictivemodelfortheriskofendocervicalcurettagepositivity AT jinmengyao developmentandvalidationofapredictivemodelfortheriskofendocervicalcurettagepositivity AT weihongwang developmentandvalidationofapredictivemodelfortheriskofendocervicalcurettagepositivity AT fenglanguo developmentandvalidationofapredictivemodelfortheriskofendocervicalcurettagepositivity AT ruifangan developmentandvalidationofapredictivemodelfortheriskofendocervicalcurettagepositivity |