Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Ahmed, Anwar E, McClish, Donna K, Alghamdi, Thamer, Alshehri, Abdulmajeed, Aljahdali, Yasser, Aburayah, Khalid, Almaymoni, Abdulrahman, Albaijan, Monirah, Al-Jahdali, Hamdan, Jazieh, Abdul Rahman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2019
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
_version_ 1783393607157284864
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
work_keys_str_mv AT ahmedanware modelingriskassessmentforbreastcancerinsymptomaticwomenasaudiarabianstudy
AT mcclishdonnak modelingriskassessmentforbreastcancerinsymptomaticwomenasaudiarabianstudy
AT alghamdithamer modelingriskassessmentforbreastcancerinsymptomaticwomenasaudiarabianstudy
AT alshehriabdulmajeed modelingriskassessmentforbreastcancerinsymptomaticwomenasaudiarabianstudy
AT aljahdaliyasser modelingriskassessmentforbreastcancerinsymptomaticwomenasaudiarabianstudy
AT aburayahkhalid modelingriskassessmentforbreastcancerinsymptomaticwomenasaudiarabianstudy
AT almaymoniabdulrahman modelingriskassessmentforbreastcancerinsymptomaticwomenasaudiarabianstudy
AT albaijanmonirah modelingriskassessmentforbreastcancerinsymptomaticwomenasaudiarabianstudy
AT aljahdalihamdan modelingriskassessmentforbreastcancerinsymptomaticwomenasaudiarabianstudy
AT jaziehabdulrahman modelingriskassessmentforbreastcancerinsymptomaticwomenasaudiarabianstudy