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Modeling risk assessment for breast cancer in symptomatic women: a Saudi Arabian study
BACKGROUND: Despite the continuing increase in the breast cancer incidence rate among Saudi Arabian women, no breast cancer risk-prediction model is available in this population. The aim of this research was to develop a risk-assessment tool to distinguish between high risk and low risk of breast ca...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366356/ https://www.ncbi.nlm.nih.gov/pubmed/30787637 http://dx.doi.org/10.2147/CMAR.S189883 |
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author | Ahmed, Anwar E McClish, Donna K Alghamdi, Thamer Alshehri, Abdulmajeed Aljahdali, Yasser Aburayah, Khalid Almaymoni, Abdulrahman Albaijan, Monirah Al-Jahdali, Hamdan Jazieh, Abdul Rahman |
author_facet | Ahmed, Anwar E McClish, Donna K Alghamdi, Thamer Alshehri, Abdulmajeed Aljahdali, Yasser Aburayah, Khalid Almaymoni, Abdulrahman Albaijan, Monirah Al-Jahdali, Hamdan Jazieh, Abdul Rahman |
author_sort | Ahmed, Anwar E |
collection | PubMed |
description | BACKGROUND: Despite the continuing increase in the breast cancer incidence rate among Saudi Arabian women, no breast cancer risk-prediction model is available in this population. The aim of this research was to develop a risk-assessment tool to distinguish between high risk and low risk of breast cancer in a sample of Saudi women who were screened for breast cancer. METHODS: A retrospective chart review was conducted on symptomatic women who underwent breast mass biopsies between September 8, 2015 and November 8, 2017 at King Abdulaziz Medical City, Riyadh, Saudi Arabia. RESULTS: A total of 404 (63.8%) malignant breast biopsies and 229 (36.2%) benign breast biopsies were analyzed. Women ≥40 years old (aOR: 6.202, CI 3.497–11.001, P=0.001), hormone-replacement therapy (aOR 24.365, 95% CI 8.606–68.987, P=0.001), postmenopausal (aOR 3.058, 95% CI 1.861–5.024, P=0.001), and with a family history of breast cancer (aOR 2.307, 95% CI 1.142–4.658, P=0.020) were independently associated with an increased risk of breast cancer. This model showed an acceptable fit and had area under the receiver-operating characteristic curve of 0.877 (95% CI 0.851–0.903), with optimism-corrected area under the curve of 0.865. CONCLUSION: The prediction model developed in this study has a high ability in predicting increased breast cancer risk in our facility. Combining information on age, use of hormone therapy, postmenopausal status, and family history of breast cancer improved the degree of discriminatory accuracy of breast cancer prediction. Our risk model may assist in initiating population-screening programs and prompt clinical decision making to manage cases and prevent unfavorable outcomes. |
format | Online Article Text |
id | pubmed-6366356 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63663562019-02-20 Modeling risk assessment for breast cancer in symptomatic women: a Saudi Arabian study Ahmed, Anwar E McClish, Donna K Alghamdi, Thamer Alshehri, Abdulmajeed Aljahdali, Yasser Aburayah, Khalid Almaymoni, Abdulrahman Albaijan, Monirah Al-Jahdali, Hamdan Jazieh, Abdul Rahman Cancer Manag Res Original Research BACKGROUND: Despite the continuing increase in the breast cancer incidence rate among Saudi Arabian women, no breast cancer risk-prediction model is available in this population. The aim of this research was to develop a risk-assessment tool to distinguish between high risk and low risk of breast cancer in a sample of Saudi women who were screened for breast cancer. METHODS: A retrospective chart review was conducted on symptomatic women who underwent breast mass biopsies between September 8, 2015 and November 8, 2017 at King Abdulaziz Medical City, Riyadh, Saudi Arabia. RESULTS: A total of 404 (63.8%) malignant breast biopsies and 229 (36.2%) benign breast biopsies were analyzed. Women ≥40 years old (aOR: 6.202, CI 3.497–11.001, P=0.001), hormone-replacement therapy (aOR 24.365, 95% CI 8.606–68.987, P=0.001), postmenopausal (aOR 3.058, 95% CI 1.861–5.024, P=0.001), and with a family history of breast cancer (aOR 2.307, 95% CI 1.142–4.658, P=0.020) were independently associated with an increased risk of breast cancer. This model showed an acceptable fit and had area under the receiver-operating characteristic curve of 0.877 (95% CI 0.851–0.903), with optimism-corrected area under the curve of 0.865. CONCLUSION: The prediction model developed in this study has a high ability in predicting increased breast cancer risk in our facility. Combining information on age, use of hormone therapy, postmenopausal status, and family history of breast cancer improved the degree of discriminatory accuracy of breast cancer prediction. Our risk model may assist in initiating population-screening programs and prompt clinical decision making to manage cases and prevent unfavorable outcomes. Dove Medical Press 2019-02-04 /pmc/articles/PMC6366356/ /pubmed/30787637 http://dx.doi.org/10.2147/CMAR.S189883 Text en © 2019 Ahmed et al. 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. |
spellingShingle | Original Research Ahmed, Anwar E McClish, Donna K Alghamdi, Thamer Alshehri, Abdulmajeed Aljahdali, Yasser Aburayah, Khalid Almaymoni, Abdulrahman Albaijan, Monirah Al-Jahdali, Hamdan Jazieh, Abdul Rahman Modeling risk assessment for breast cancer in symptomatic women: a Saudi Arabian study |
title | Modeling risk assessment for breast cancer in symptomatic women: a Saudi Arabian study |
title_full | Modeling risk assessment for breast cancer in symptomatic women: a Saudi Arabian study |
title_fullStr | Modeling risk assessment for breast cancer in symptomatic women: a Saudi Arabian study |
title_full_unstemmed | Modeling risk assessment for breast cancer in symptomatic women: a Saudi Arabian study |
title_short | Modeling risk assessment for breast cancer in symptomatic women: a Saudi Arabian study |
title_sort | modeling risk assessment for breast cancer in symptomatic women: a saudi arabian study |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366356/ https://www.ncbi.nlm.nih.gov/pubmed/30787637 http://dx.doi.org/10.2147/CMAR.S189883 |
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