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Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features
PURPOSE: To explore the potential factors influencing the malignancy risk of amorphous calcifications and establish a predictive nomogram for malignancy risk stratification. PATIENTS AND METHODS: Consecutive mammograms from January 2013 to December 2018 were retrospectively reviewed. Traditional cli...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7811441/ https://www.ncbi.nlm.nih.gov/pubmed/33469367 http://dx.doi.org/10.2147/CMAR.S286269 |
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author | Shen, Lijuan Ma, Xiaowen Jiang, Tingting Shen, Xigang Yang, Wentao You, Chao Peng, Weijun |
author_facet | Shen, Lijuan Ma, Xiaowen Jiang, Tingting Shen, Xigang Yang, Wentao You, Chao Peng, Weijun |
author_sort | Shen, Lijuan |
collection | PubMed |
description | PURPOSE: To explore the potential factors influencing the malignancy risk of amorphous calcifications and establish a predictive nomogram for malignancy risk stratification. PATIENTS AND METHODS: Consecutive mammograms from January 2013 to December 2018 were retrospectively reviewed. Traditional clinical features were recorded, and mammographic features were estimated according to the 5th BI-RADS. Included calcifications were randomly divided into the training and validation cohorts. A nomogram was developed to graphically predict the risk of malignancy (risk) based on stepwise multivariate logistic regression analysis. The discrimination and calibration performance of the model were assessed in both the training and validation cohorts. RESULTS: Finally, 1018 amorphous calcifications with final pathological results in 907 women were identified with a malignancy rate of 28.4% (95% CI: 25.7%, 31.3%). The malignancy rates of subgroups divided by the distribution of calcifications, quantity of calcifications, age, menopausal status and family history of cancer were significantly different. There were 712 cases and 306 cases in the training and validation cohorts. The prediction nomogram was finally developed based on four risk factors, including age and distribution, maximum diameter and quantity of calcifications. The AUC of the nomogram was 0.799 (95% CI: 0.761, 0.836) in the training cohort and 0.795 (95% CI: 0.738, 0.852) in the validation cohort. CONCLUSION: On mammography, the distribution, maximum diameter and quantity of calcifications are independent predictors of malignant amorphous calcifications and can be easily obtained in the clinic. The nomogram developed in this study for individualized malignancy risk stratification of amorphous calcifications shows good discrimination performance. |
format | Online Article Text |
id | pubmed-7811441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-78114412021-01-18 Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features Shen, Lijuan Ma, Xiaowen Jiang, Tingting Shen, Xigang Yang, Wentao You, Chao Peng, Weijun Cancer Manag Res Original Research PURPOSE: To explore the potential factors influencing the malignancy risk of amorphous calcifications and establish a predictive nomogram for malignancy risk stratification. PATIENTS AND METHODS: Consecutive mammograms from January 2013 to December 2018 were retrospectively reviewed. Traditional clinical features were recorded, and mammographic features were estimated according to the 5th BI-RADS. Included calcifications were randomly divided into the training and validation cohorts. A nomogram was developed to graphically predict the risk of malignancy (risk) based on stepwise multivariate logistic regression analysis. The discrimination and calibration performance of the model were assessed in both the training and validation cohorts. RESULTS: Finally, 1018 amorphous calcifications with final pathological results in 907 women were identified with a malignancy rate of 28.4% (95% CI: 25.7%, 31.3%). The malignancy rates of subgroups divided by the distribution of calcifications, quantity of calcifications, age, menopausal status and family history of cancer were significantly different. There were 712 cases and 306 cases in the training and validation cohorts. The prediction nomogram was finally developed based on four risk factors, including age and distribution, maximum diameter and quantity of calcifications. The AUC of the nomogram was 0.799 (95% CI: 0.761, 0.836) in the training cohort and 0.795 (95% CI: 0.738, 0.852) in the validation cohort. CONCLUSION: On mammography, the distribution, maximum diameter and quantity of calcifications are independent predictors of malignant amorphous calcifications and can be easily obtained in the clinic. The nomogram developed in this study for individualized malignancy risk stratification of amorphous calcifications shows good discrimination performance. Dove 2021-01-12 /pmc/articles/PMC7811441/ /pubmed/33469367 http://dx.doi.org/10.2147/CMAR.S286269 Text en © 2021 Shen et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Shen, Lijuan Ma, Xiaowen Jiang, Tingting Shen, Xigang Yang, Wentao You, Chao Peng, Weijun Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features |
title | Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features |
title_full | Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features |
title_fullStr | Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features |
title_full_unstemmed | Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features |
title_short | Malignancy Risk Stratification Prediction of Amorphous Calcifications Based on Clinical and Mammographic Features |
title_sort | malignancy risk stratification prediction of amorphous calcifications based on clinical and mammographic features |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7811441/ https://www.ncbi.nlm.nih.gov/pubmed/33469367 http://dx.doi.org/10.2147/CMAR.S286269 |
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