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Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?

BACKGROUND: Mammography (MG) is highly sensitive for detecting microcalcifications, but has low specificity. This study investigates whether establishing a preoperative nomogram including ultrasonographic findings can help predict the likelihood of malignancy in patients with mammographic microcalci...

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Autores principales: Wang, Hongli, Lai, Jianguo, Li, Jiao, Gu, Ran, Liu, Fengtao, Hu, Yue, Mei, Jingsi, Jiang, Xiaofang, Shen, Shiyu, Yu, Fengyan, Su, Fengxi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610836/
https://www.ncbi.nlm.nih.gov/pubmed/31269987
http://dx.doi.org/10.1186/s40644-019-0229-1
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author Wang, Hongli
Lai, Jianguo
Li, Jiao
Gu, Ran
Liu, Fengtao
Hu, Yue
Mei, Jingsi
Jiang, Xiaofang
Shen, Shiyu
Yu, Fengyan
Su, Fengxi
author_facet Wang, Hongli
Lai, Jianguo
Li, Jiao
Gu, Ran
Liu, Fengtao
Hu, Yue
Mei, Jingsi
Jiang, Xiaofang
Shen, Shiyu
Yu, Fengyan
Su, Fengxi
author_sort Wang, Hongli
collection PubMed
description BACKGROUND: Mammography (MG) is highly sensitive for detecting microcalcifications, but has low specificity. This study investigates whether establishing a preoperative nomogram including ultrasonographic findings can help predict the likelihood of malignancy in patients with mammographic microcalcification. METHODS: Between May 2012 and January 2017, 475 patients with suspicious microcalcifications detected on MG underwent ultrasonography (US). The χ(2) test was used to screen risk factors among the variables. Then, a multivariate logistic regression analysis was performed to identify independent predictors of malignant microcalcifications. A mammographic nomogram (M nomogram) and mammographic-ultrasonographic nomogram (M-U nomogram) were established based on multivariate logistic regression models. The discriminatory ability and clinical utility of both nomograms were compared by the receiver operating characteristics curve and decision curve analysis. The calibration ability was evaluated using a calibration curve. RESULTS: Among the cases, 68.2% (324/475) were pathologically diagnosed as breast cancer and 31.8% (151/475) were benign lesions. Based on multivariate logistic regression analysis, age, clinical manifestation, morphology and distribution of microcalcifications on MG and lesions associated with microcalcifications on US were confirmed as independent predictors of malignant microcalcifications. In terms of discrimination ability, the C-index of the M-U nomogram was significantly higher than that of the M nomogram (0.917 vs 0.897, p = 0.006). The bias-corrected curve was close to the ideal line in the calibration curve. Decision curve analysis suggested that the M-U nomogram was superior to M nomogram. CONCLUSIONS: Combining mammographic parameters with ultrasonographic findings in a nomogram provided better performance than an M nomogram alone, especially for dense breasts, which suggests the value of ultrasonographic finding for individualized prediction of malignancy in patients with microcalcifications.
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spelling pubmed-66108362019-07-16 Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications? Wang, Hongli Lai, Jianguo Li, Jiao Gu, Ran Liu, Fengtao Hu, Yue Mei, Jingsi Jiang, Xiaofang Shen, Shiyu Yu, Fengyan Su, Fengxi Cancer Imaging Research Article BACKGROUND: Mammography (MG) is highly sensitive for detecting microcalcifications, but has low specificity. This study investigates whether establishing a preoperative nomogram including ultrasonographic findings can help predict the likelihood of malignancy in patients with mammographic microcalcification. METHODS: Between May 2012 and January 2017, 475 patients with suspicious microcalcifications detected on MG underwent ultrasonography (US). The χ(2) test was used to screen risk factors among the variables. Then, a multivariate logistic regression analysis was performed to identify independent predictors of malignant microcalcifications. A mammographic nomogram (M nomogram) and mammographic-ultrasonographic nomogram (M-U nomogram) were established based on multivariate logistic regression models. The discriminatory ability and clinical utility of both nomograms were compared by the receiver operating characteristics curve and decision curve analysis. The calibration ability was evaluated using a calibration curve. RESULTS: Among the cases, 68.2% (324/475) were pathologically diagnosed as breast cancer and 31.8% (151/475) were benign lesions. Based on multivariate logistic regression analysis, age, clinical manifestation, morphology and distribution of microcalcifications on MG and lesions associated with microcalcifications on US were confirmed as independent predictors of malignant microcalcifications. In terms of discrimination ability, the C-index of the M-U nomogram was significantly higher than that of the M nomogram (0.917 vs 0.897, p = 0.006). The bias-corrected curve was close to the ideal line in the calibration curve. Decision curve analysis suggested that the M-U nomogram was superior to M nomogram. CONCLUSIONS: Combining mammographic parameters with ultrasonographic findings in a nomogram provided better performance than an M nomogram alone, especially for dense breasts, which suggests the value of ultrasonographic finding for individualized prediction of malignancy in patients with microcalcifications. BioMed Central 2019-07-03 /pmc/articles/PMC6610836/ /pubmed/31269987 http://dx.doi.org/10.1186/s40644-019-0229-1 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Wang, Hongli
Lai, Jianguo
Li, Jiao
Gu, Ran
Liu, Fengtao
Hu, Yue
Mei, Jingsi
Jiang, Xiaofang
Shen, Shiyu
Yu, Fengyan
Su, Fengxi
Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?
title Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?
title_full Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?
title_fullStr Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?
title_full_unstemmed Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?
title_short Does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?
title_sort does establishing a preoperative nomogram including ultrasonographic findings help predict the likelihood of malignancy in patients with microcalcifications?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610836/
https://www.ncbi.nlm.nih.gov/pubmed/31269987
http://dx.doi.org/10.1186/s40644-019-0229-1
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