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Trends and Projections in Breast Cancer Mortality among four Asian countries (1990–2017): Evidence from five Stochastic Mortality Models

The current study aimed to explore some important insights into the breast cancer mortality (BCM) trends and projections among four Asian countries by using five advanced stochastic mortality models. BCM data over 28 years from 1990–2017 with ages 20–84 were retrieved from the Global Burden of Disea...

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Autores principales: Mubarik, Sumaira, Wang, Fang, Fawad, Muhammad, Wang, Yafeng, Ahmad, Ishfaq, Yu, Chuanhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7096499/
https://www.ncbi.nlm.nih.gov/pubmed/32214176
http://dx.doi.org/10.1038/s41598-020-62393-1
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author Mubarik, Sumaira
Wang, Fang
Fawad, Muhammad
Wang, Yafeng
Ahmad, Ishfaq
Yu, Chuanhua
author_facet Mubarik, Sumaira
Wang, Fang
Fawad, Muhammad
Wang, Yafeng
Ahmad, Ishfaq
Yu, Chuanhua
author_sort Mubarik, Sumaira
collection PubMed
description The current study aimed to explore some important insights into the breast cancer mortality (BCM) trends and projections among four Asian countries by using five advanced stochastic mortality models. BCM data over 28 years from 1990–2017 with ages 20–84 were retrieved from the Global Burden of Disease (GBD) Study 2017 for four Asian countries, namely, China, India, Pakistan, and Thailand. Five stochastic mortality models with the family of generalized age-period-cohort were implemented to find the present and future BCM trends in these four Asian countries. Based on Cairns-Blake-Dowd (CBD) model and Lee-Carter model (LCM), overall, results revealed that BCM increased with the passage of time. Aging factor was the most influential factor of elevated BCM in each Asian country under consideration. Projection of BCM showed that mortality rates might continue to grow with time, especially in older ages in each Asian country under study. The highest forecasted BCM rates were observed in Pakistan as compared to other countries. The obvious increase in BCM suggested that earlier tactics should be implemented to reduce the subsequent morbidity and mortality due to breast cancer. The last but not least, some additional tactics to mitigate the BCM in older ages must be adopted.
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spelling pubmed-70964992020-03-30 Trends and Projections in Breast Cancer Mortality among four Asian countries (1990–2017): Evidence from five Stochastic Mortality Models Mubarik, Sumaira Wang, Fang Fawad, Muhammad Wang, Yafeng Ahmad, Ishfaq Yu, Chuanhua Sci Rep Article The current study aimed to explore some important insights into the breast cancer mortality (BCM) trends and projections among four Asian countries by using five advanced stochastic mortality models. BCM data over 28 years from 1990–2017 with ages 20–84 were retrieved from the Global Burden of Disease (GBD) Study 2017 for four Asian countries, namely, China, India, Pakistan, and Thailand. Five stochastic mortality models with the family of generalized age-period-cohort were implemented to find the present and future BCM trends in these four Asian countries. Based on Cairns-Blake-Dowd (CBD) model and Lee-Carter model (LCM), overall, results revealed that BCM increased with the passage of time. Aging factor was the most influential factor of elevated BCM in each Asian country under consideration. Projection of BCM showed that mortality rates might continue to grow with time, especially in older ages in each Asian country under study. The highest forecasted BCM rates were observed in Pakistan as compared to other countries. The obvious increase in BCM suggested that earlier tactics should be implemented to reduce the subsequent morbidity and mortality due to breast cancer. The last but not least, some additional tactics to mitigate the BCM in older ages must be adopted. Nature Publishing Group UK 2020-03-25 /pmc/articles/PMC7096499/ /pubmed/32214176 http://dx.doi.org/10.1038/s41598-020-62393-1 Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Mubarik, Sumaira
Wang, Fang
Fawad, Muhammad
Wang, Yafeng
Ahmad, Ishfaq
Yu, Chuanhua
Trends and Projections in Breast Cancer Mortality among four Asian countries (1990–2017): Evidence from five Stochastic Mortality Models
title Trends and Projections in Breast Cancer Mortality among four Asian countries (1990–2017): Evidence from five Stochastic Mortality Models
title_full Trends and Projections in Breast Cancer Mortality among four Asian countries (1990–2017): Evidence from five Stochastic Mortality Models
title_fullStr Trends and Projections in Breast Cancer Mortality among four Asian countries (1990–2017): Evidence from five Stochastic Mortality Models
title_full_unstemmed Trends and Projections in Breast Cancer Mortality among four Asian countries (1990–2017): Evidence from five Stochastic Mortality Models
title_short Trends and Projections in Breast Cancer Mortality among four Asian countries (1990–2017): Evidence from five Stochastic Mortality Models
title_sort trends and projections in breast cancer mortality among four asian countries (1990–2017): evidence from five stochastic mortality models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7096499/
https://www.ncbi.nlm.nih.gov/pubmed/32214176
http://dx.doi.org/10.1038/s41598-020-62393-1
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