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Prediction of breast cancer risk among women of the Mariana Islands: the BRISK retrospective case–control study

OBJECTIVES: To develop a breast cancer risk prediction model for Chamorro and Filipino women of the Mariana Islands and compare its performance to that of the Breast Cancer Risk Assessment Tool (BCRAT). DESIGN: Case–control study. SETTING: Clinics/facilities and other community-based settings on Gua...

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Autores principales: Shvetsov, Yurii B, Wilkens, Lynne R, White, Kami K, Chong, Marie, Buyum, Arielle, Badowski, Grazyna, Leon Guerrero, Rachael T, Novotny, Rachel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9743286/
https://www.ncbi.nlm.nih.gov/pubmed/36600333
http://dx.doi.org/10.1136/bmjopen-2022-061205
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author Shvetsov, Yurii B
Wilkens, Lynne R
White, Kami K
Chong, Marie
Buyum, Arielle
Badowski, Grazyna
Leon Guerrero, Rachael T
Novotny, Rachel
author_facet Shvetsov, Yurii B
Wilkens, Lynne R
White, Kami K
Chong, Marie
Buyum, Arielle
Badowski, Grazyna
Leon Guerrero, Rachael T
Novotny, Rachel
author_sort Shvetsov, Yurii B
collection PubMed
description OBJECTIVES: To develop a breast cancer risk prediction model for Chamorro and Filipino women of the Mariana Islands and compare its performance to that of the Breast Cancer Risk Assessment Tool (BCRAT). DESIGN: Case–control study. SETTING: Clinics/facilities and other community-based settings on Guam and Saipan (Northern Mariana Islands). PARTICIPANTS: 245 women (87 breast cancer cases and 158 controls) of Chamorro or Filipino ethnicity, age 25–80 years, with no prior history of cancer (other than skin cancer), residing on Guam or Saipan for at least 5 years. PRIMARY AND SECONDARY OUTCOME MEASURES: Breast cancer risk models were constructed using combinations of exposures previously identified to affect breast cancer risk in this population, population breast cancer incidence rates and all-cause mortality rates for Guam. RESULTS: Models using ethnic-specific relative risks performed better than those with relative risks estimated from all women. The model with the best performance among both ethnicities (the Breast Cancer Risk Model (BRISK) model; area under the receiver operating characteristic curve (AUC): 0.64 and 0.67 among Chamorros and Filipinos, respectively) included age at menarche, age at first live birth, number of relatives with breast cancer and waist circumference. The 10-year breast cancer risk predicted by the BRISK model was 1.28% for Chamorros and 0.89% for Filipinos. Performance of the BCRAT was modest among both Chamorros (AUC: 0.60) and Filipinos (AUC: 0.55), possibly due to incomplete information on BCRAT risk factors. CONCLUSIONS: The ability to develop breast cancer risk models for Mariana Islands women is constrained by the small population size and limited availability of health services and data. Nonetheless, we have demonstrated that breast cancer risk prediction models with adequate discriminatory performance can be built for small populations such as in the Mariana Islands. Anthropometry, in particular waist circumference, was important for estimating breast cancer risk in this population.
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spelling pubmed-97432862022-12-13 Prediction of breast cancer risk among women of the Mariana Islands: the BRISK retrospective case–control study Shvetsov, Yurii B Wilkens, Lynne R White, Kami K Chong, Marie Buyum, Arielle Badowski, Grazyna Leon Guerrero, Rachael T Novotny, Rachel BMJ Open Epidemiology OBJECTIVES: To develop a breast cancer risk prediction model for Chamorro and Filipino women of the Mariana Islands and compare its performance to that of the Breast Cancer Risk Assessment Tool (BCRAT). DESIGN: Case–control study. SETTING: Clinics/facilities and other community-based settings on Guam and Saipan (Northern Mariana Islands). PARTICIPANTS: 245 women (87 breast cancer cases and 158 controls) of Chamorro or Filipino ethnicity, age 25–80 years, with no prior history of cancer (other than skin cancer), residing on Guam or Saipan for at least 5 years. PRIMARY AND SECONDARY OUTCOME MEASURES: Breast cancer risk models were constructed using combinations of exposures previously identified to affect breast cancer risk in this population, population breast cancer incidence rates and all-cause mortality rates for Guam. RESULTS: Models using ethnic-specific relative risks performed better than those with relative risks estimated from all women. The model with the best performance among both ethnicities (the Breast Cancer Risk Model (BRISK) model; area under the receiver operating characteristic curve (AUC): 0.64 and 0.67 among Chamorros and Filipinos, respectively) included age at menarche, age at first live birth, number of relatives with breast cancer and waist circumference. The 10-year breast cancer risk predicted by the BRISK model was 1.28% for Chamorros and 0.89% for Filipinos. Performance of the BCRAT was modest among both Chamorros (AUC: 0.60) and Filipinos (AUC: 0.55), possibly due to incomplete information on BCRAT risk factors. CONCLUSIONS: The ability to develop breast cancer risk models for Mariana Islands women is constrained by the small population size and limited availability of health services and data. Nonetheless, we have demonstrated that breast cancer risk prediction models with adequate discriminatory performance can be built for small populations such as in the Mariana Islands. Anthropometry, in particular waist circumference, was important for estimating breast cancer risk in this population. BMJ Publishing Group 2022-12-09 /pmc/articles/PMC9743286/ /pubmed/36600333 http://dx.doi.org/10.1136/bmjopen-2022-061205 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Epidemiology
Shvetsov, Yurii B
Wilkens, Lynne R
White, Kami K
Chong, Marie
Buyum, Arielle
Badowski, Grazyna
Leon Guerrero, Rachael T
Novotny, Rachel
Prediction of breast cancer risk among women of the Mariana Islands: the BRISK retrospective case–control study
title Prediction of breast cancer risk among women of the Mariana Islands: the BRISK retrospective case–control study
title_full Prediction of breast cancer risk among women of the Mariana Islands: the BRISK retrospective case–control study
title_fullStr Prediction of breast cancer risk among women of the Mariana Islands: the BRISK retrospective case–control study
title_full_unstemmed Prediction of breast cancer risk among women of the Mariana Islands: the BRISK retrospective case–control study
title_short Prediction of breast cancer risk among women of the Mariana Islands: the BRISK retrospective case–control study
title_sort prediction of breast cancer risk among women of the mariana islands: the brisk retrospective case–control study
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9743286/
https://www.ncbi.nlm.nih.gov/pubmed/36600333
http://dx.doi.org/10.1136/bmjopen-2022-061205
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