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Development and Validation of a Nomogram Prediction Model for Endometrial Malignancy in Patients with Abnormal Uterine Bleeding
PURPOSE: This study aimed to identify the risk factors and sonographic variables that could be integrated into a predictive model for endometrial cancer (EC) and atypical endometrial hyperplasia (AEH) in women with abnormal uterine bleeding (AUB). MATERIALS AND METHODS: This retrospective study incl...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Yonsei University College of Medicine
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9971439/ https://www.ncbi.nlm.nih.gov/pubmed/36825346 http://dx.doi.org/10.3349/ymj.2022.0239 |
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author | Ruan, Hengchao Chen, Suhan Li, Jingyi Ma, Linjuan Luo, Jie Huang, Yizhou Ying, Qian Zhou, Jianhong |
author_facet | Ruan, Hengchao Chen, Suhan Li, Jingyi Ma, Linjuan Luo, Jie Huang, Yizhou Ying, Qian Zhou, Jianhong |
author_sort | Ruan, Hengchao |
collection | PubMed |
description | PURPOSE: This study aimed to identify the risk factors and sonographic variables that could be integrated into a predictive model for endometrial cancer (EC) and atypical endometrial hyperplasia (AEH) in women with abnormal uterine bleeding (AUB). MATERIALS AND METHODS: This retrospective study included 1837 patients who presented with AUB and underwent endometrial sampling. Multivariable logistic regression was developed based on clinical and sonographic covariates [endometrial thickness (ET), resistance index (RI) of the endometrial vasculature] assessed for their association with EC/AEH in the development group (n=1369), and a predictive nomogram was proposed. The model was validated in 468 patients. RESULTS: Histological examination revealed 167 patients (12.2%) with EC or AEH in the development group. Using multivariable logistic regression, the following variables were incorporated in the prediction of endometrial malignancy: metabolic diseases [odds ratio (OR)=7.764, 95% confidence intervals (CI) 5.042–11.955], family history (OR=3.555, 95% CI 1.055–11.971), age ≥40 years (OR=3.195, 95% CI 1.878–5.435), RI ≤0.5 (OR=8.733, 95% CI 4.311–17.692), and ET ≥10 mm (OR=8.479, 95% CI 5.440–13.216). A nomogram was created using these five variables with an area under the curve of 0.837 (95% CI 0.800–0.874). The calibration curve showed good agreement between the observed and predicted occurrences. For the validation group, the model provided acceptable discrimination and calibration. CONCLUSION: The proposed nomogram model showed moderate prediction accuracy in the differentiation between benign and malignant endometrial lesions among women with AUB. |
format | Online Article Text |
id | pubmed-9971439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Yonsei University College of Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-99714392023-03-01 Development and Validation of a Nomogram Prediction Model for Endometrial Malignancy in Patients with Abnormal Uterine Bleeding Ruan, Hengchao Chen, Suhan Li, Jingyi Ma, Linjuan Luo, Jie Huang, Yizhou Ying, Qian Zhou, Jianhong Yonsei Med J Original Article PURPOSE: This study aimed to identify the risk factors and sonographic variables that could be integrated into a predictive model for endometrial cancer (EC) and atypical endometrial hyperplasia (AEH) in women with abnormal uterine bleeding (AUB). MATERIALS AND METHODS: This retrospective study included 1837 patients who presented with AUB and underwent endometrial sampling. Multivariable logistic regression was developed based on clinical and sonographic covariates [endometrial thickness (ET), resistance index (RI) of the endometrial vasculature] assessed for their association with EC/AEH in the development group (n=1369), and a predictive nomogram was proposed. The model was validated in 468 patients. RESULTS: Histological examination revealed 167 patients (12.2%) with EC or AEH in the development group. Using multivariable logistic regression, the following variables were incorporated in the prediction of endometrial malignancy: metabolic diseases [odds ratio (OR)=7.764, 95% confidence intervals (CI) 5.042–11.955], family history (OR=3.555, 95% CI 1.055–11.971), age ≥40 years (OR=3.195, 95% CI 1.878–5.435), RI ≤0.5 (OR=8.733, 95% CI 4.311–17.692), and ET ≥10 mm (OR=8.479, 95% CI 5.440–13.216). A nomogram was created using these five variables with an area under the curve of 0.837 (95% CI 0.800–0.874). The calibration curve showed good agreement between the observed and predicted occurrences. For the validation group, the model provided acceptable discrimination and calibration. CONCLUSION: The proposed nomogram model showed moderate prediction accuracy in the differentiation between benign and malignant endometrial lesions among women with AUB. Yonsei University College of Medicine 2023-03 2023-02-07 /pmc/articles/PMC9971439/ /pubmed/36825346 http://dx.doi.org/10.3349/ymj.2022.0239 Text en © Copyright: Yonsei University College of Medicine 2023 https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Ruan, Hengchao Chen, Suhan Li, Jingyi Ma, Linjuan Luo, Jie Huang, Yizhou Ying, Qian Zhou, Jianhong Development and Validation of a Nomogram Prediction Model for Endometrial Malignancy in Patients with Abnormal Uterine Bleeding |
title | Development and Validation of a Nomogram Prediction Model for Endometrial Malignancy in Patients with Abnormal Uterine Bleeding |
title_full | Development and Validation of a Nomogram Prediction Model for Endometrial Malignancy in Patients with Abnormal Uterine Bleeding |
title_fullStr | Development and Validation of a Nomogram Prediction Model for Endometrial Malignancy in Patients with Abnormal Uterine Bleeding |
title_full_unstemmed | Development and Validation of a Nomogram Prediction Model for Endometrial Malignancy in Patients with Abnormal Uterine Bleeding |
title_short | Development and Validation of a Nomogram Prediction Model for Endometrial Malignancy in Patients with Abnormal Uterine Bleeding |
title_sort | development and validation of a nomogram prediction model for endometrial malignancy in patients with abnormal uterine bleeding |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9971439/ https://www.ncbi.nlm.nih.gov/pubmed/36825346 http://dx.doi.org/10.3349/ymj.2022.0239 |
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