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Female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in Taiwan
BACKGROUND: Breast cancer is an umbrella term referring to a group of biologically and molecularly heterogeneous diseases originating from the breast. Globally, incidences of breast cancer has been increasing dramatically over the past decades. Analyses of multiple clinical “big data” can aid us in...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351234/ https://www.ncbi.nlm.nih.gov/pubmed/35927682 http://dx.doi.org/10.1186/s12885-022-09913-6 |
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author | Liu, Ping-Hung Wei, James Cheng-Chung Wang, Yu-Hsun Yeh, Ming-Hsin |
author_facet | Liu, Ping-Hung Wei, James Cheng-Chung Wang, Yu-Hsun Yeh, Ming-Hsin |
author_sort | Liu, Ping-Hung |
collection | PubMed |
description | BACKGROUND: Breast cancer is an umbrella term referring to a group of biologically and molecularly heterogeneous diseases originating from the breast. Globally, incidences of breast cancer has been increasing dramatically over the past decades. Analyses of multiple clinical “big data” can aid us in clarifying the means of preventing the disease. In addition, predisposing risk factors will be the most important issues if we can confirm their relevance. This study aims to provide an overview of the predisposing factors that contribute to a higher possibility of developing breast cancer and emphasize the signs that we ought to pay more attention to. METHODS: This is a matched nested case-control study. The cohort focused on identifying the eligible risk factors in breast cancer development by data screening (2000-2013) from the Taiwan National Health Insurance Research Database (NHIRD) under approved protocol. A total of 486,069 females were enrolled from a nationwide sampled database, and 3281 females was elligible as breast cancer cohort, 478,574 females who had never diagnosed with breast cancer from 2000 to 2013 were eligible as non-breast cancer controls, and matched to breast cancer cases according to age using a 1:6 ratio. RESULTS: We analyzed 3281 breast cancer cases and 19,686 non-breast cancer controls after an age-matched procedure. The significant predisposing factors associated with breast cancer development including obesity, hyperlipidemia, thyroid cancer and liver cancer. As for patients under the age of 55, gastric cancer does seem to have an impact on the development of breast cancer; compared with their counterparts over the age of 55, endometrial cancer appears to exhibit an evocative effect. CONCLUSIONS: In this nationwide matched nested case-control study, we identified obesity, hyperlipidemia, previous cancers of the thyroid, stomach and liver as risk factors associated with breast cancer. However, the retrospective nature and limited case numbers of certain cancers still difficult to provide robust evidence. Further prospective studies are necessitated to corroborate this finding in order to nip the disease in the bud. TRIAL REGISTRATION: The studies involving human participants were reviewed and approved by the China Medical University Hospital [CMUH104-REC2-115(AR-4)]. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09913-6. |
format | Online Article Text |
id | pubmed-9351234 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-93512342022-08-05 Female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in Taiwan Liu, Ping-Hung Wei, James Cheng-Chung Wang, Yu-Hsun Yeh, Ming-Hsin BMC Cancer Research BACKGROUND: Breast cancer is an umbrella term referring to a group of biologically and molecularly heterogeneous diseases originating from the breast. Globally, incidences of breast cancer has been increasing dramatically over the past decades. Analyses of multiple clinical “big data” can aid us in clarifying the means of preventing the disease. In addition, predisposing risk factors will be the most important issues if we can confirm their relevance. This study aims to provide an overview of the predisposing factors that contribute to a higher possibility of developing breast cancer and emphasize the signs that we ought to pay more attention to. METHODS: This is a matched nested case-control study. The cohort focused on identifying the eligible risk factors in breast cancer development by data screening (2000-2013) from the Taiwan National Health Insurance Research Database (NHIRD) under approved protocol. A total of 486,069 females were enrolled from a nationwide sampled database, and 3281 females was elligible as breast cancer cohort, 478,574 females who had never diagnosed with breast cancer from 2000 to 2013 were eligible as non-breast cancer controls, and matched to breast cancer cases according to age using a 1:6 ratio. RESULTS: We analyzed 3281 breast cancer cases and 19,686 non-breast cancer controls after an age-matched procedure. The significant predisposing factors associated with breast cancer development including obesity, hyperlipidemia, thyroid cancer and liver cancer. As for patients under the age of 55, gastric cancer does seem to have an impact on the development of breast cancer; compared with their counterparts over the age of 55, endometrial cancer appears to exhibit an evocative effect. CONCLUSIONS: In this nationwide matched nested case-control study, we identified obesity, hyperlipidemia, previous cancers of the thyroid, stomach and liver as risk factors associated with breast cancer. However, the retrospective nature and limited case numbers of certain cancers still difficult to provide robust evidence. Further prospective studies are necessitated to corroborate this finding in order to nip the disease in the bud. TRIAL REGISTRATION: The studies involving human participants were reviewed and approved by the China Medical University Hospital [CMUH104-REC2-115(AR-4)]. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09913-6. BioMed Central 2022-08-04 /pmc/articles/PMC9351234/ /pubmed/35927682 http://dx.doi.org/10.1186/s12885-022-09913-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Liu, Ping-Hung Wei, James Cheng-Chung Wang, Yu-Hsun Yeh, Ming-Hsin Female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in Taiwan |
title | Female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in Taiwan |
title_full | Female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in Taiwan |
title_fullStr | Female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in Taiwan |
title_full_unstemmed | Female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in Taiwan |
title_short | Female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in Taiwan |
title_sort | female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in taiwan |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351234/ https://www.ncbi.nlm.nih.gov/pubmed/35927682 http://dx.doi.org/10.1186/s12885-022-09913-6 |
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