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Development of a Web-Based System for Exploring Cancer Risk With Long-term Use of Drugs: Logistic Regression Approach

BACKGROUND: Existing epidemiological evidence regarding the association between the long-term use of drugs and cancer risk remains controversial. OBJECTIVE: We aimed to have a comprehensive view of the cancer risk of the long-term use of drugs. METHODS: A nationwide population-based, nested, case-co...

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Autores principales: Yang, Hsuan-Chia, Islam, Md Mohaimenul, Nguyen, Phung Anh Alex, Wang, Ching-Huan, Poly, Tahmina Nasrin, Huang, Chih-Wei, Li, Yu-Chuan Jack
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7920756/
https://www.ncbi.nlm.nih.gov/pubmed/33587043
http://dx.doi.org/10.2196/21401
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author Yang, Hsuan-Chia
Islam, Md Mohaimenul
Nguyen, Phung Anh Alex
Wang, Ching-Huan
Poly, Tahmina Nasrin
Huang, Chih-Wei
Li, Yu-Chuan Jack
author_facet Yang, Hsuan-Chia
Islam, Md Mohaimenul
Nguyen, Phung Anh Alex
Wang, Ching-Huan
Poly, Tahmina Nasrin
Huang, Chih-Wei
Li, Yu-Chuan Jack
author_sort Yang, Hsuan-Chia
collection PubMed
description BACKGROUND: Existing epidemiological evidence regarding the association between the long-term use of drugs and cancer risk remains controversial. OBJECTIVE: We aimed to have a comprehensive view of the cancer risk of the long-term use of drugs. METHODS: A nationwide population-based, nested, case-control study was conducted within the National Health Insurance Research Database sample cohort of 1999 to 2013 in Taiwan. We identified cases in adults aged 20 years and older who were receiving treatment for at least two months before the index date. We randomly selected control patients from the patients without a cancer diagnosis during the 15 years (1999-2013) of the study period. Case and control patients were matched 1:4 based on age, sex, and visit date. Conditional logistic regression was used to estimate the association between drug exposure and cancer risk by adjusting potential confounders such as drugs and comorbidities. RESULTS: There were 79,245 cancer cases and 316,980 matched controls included in this study. Of the 45,368 associations, there were 2419, 1302, 662, and 366 associations found statistically significant at a level of P<.05, P<.01, P<.001, and P<.0001, respectively. Benzodiazepine derivatives were associated with an increased risk of brain cancer (adjusted odds ratio [AOR] 1.379, 95% CI 1.138-1.670; P=.001). Statins were associated with a reduced risk of liver cancer (AOR 0.470, 95% CI 0.426-0.517; P<.0001) and gastric cancer (AOR 0.781, 95% CI 0.678-0.900; P<.001). Our web-based system, which collected comprehensive data of associations, contained 2 domains: (1) the drug and cancer association page and (2) the overview page. CONCLUSIONS: Our web-based system provides an overview of comprehensive quantified data of drug-cancer associations. With all the quantified data visualized, the system is expected to facilitate further research on cancer risk and prevention, potentially serving as a stepping-stone to consulting and exploring associations between the long-term use of drugs and cancer risk.
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spelling pubmed-79207562021-03-05 Development of a Web-Based System for Exploring Cancer Risk With Long-term Use of Drugs: Logistic Regression Approach Yang, Hsuan-Chia Islam, Md Mohaimenul Nguyen, Phung Anh Alex Wang, Ching-Huan Poly, Tahmina Nasrin Huang, Chih-Wei Li, Yu-Chuan Jack JMIR Public Health Surveill Original Paper BACKGROUND: Existing epidemiological evidence regarding the association between the long-term use of drugs and cancer risk remains controversial. OBJECTIVE: We aimed to have a comprehensive view of the cancer risk of the long-term use of drugs. METHODS: A nationwide population-based, nested, case-control study was conducted within the National Health Insurance Research Database sample cohort of 1999 to 2013 in Taiwan. We identified cases in adults aged 20 years and older who were receiving treatment for at least two months before the index date. We randomly selected control patients from the patients without a cancer diagnosis during the 15 years (1999-2013) of the study period. Case and control patients were matched 1:4 based on age, sex, and visit date. Conditional logistic regression was used to estimate the association between drug exposure and cancer risk by adjusting potential confounders such as drugs and comorbidities. RESULTS: There were 79,245 cancer cases and 316,980 matched controls included in this study. Of the 45,368 associations, there were 2419, 1302, 662, and 366 associations found statistically significant at a level of P<.05, P<.01, P<.001, and P<.0001, respectively. Benzodiazepine derivatives were associated with an increased risk of brain cancer (adjusted odds ratio [AOR] 1.379, 95% CI 1.138-1.670; P=.001). Statins were associated with a reduced risk of liver cancer (AOR 0.470, 95% CI 0.426-0.517; P<.0001) and gastric cancer (AOR 0.781, 95% CI 0.678-0.900; P<.001). Our web-based system, which collected comprehensive data of associations, contained 2 domains: (1) the drug and cancer association page and (2) the overview page. CONCLUSIONS: Our web-based system provides an overview of comprehensive quantified data of drug-cancer associations. With all the quantified data visualized, the system is expected to facilitate further research on cancer risk and prevention, potentially serving as a stepping-stone to consulting and exploring associations between the long-term use of drugs and cancer risk. JMIR Publications 2021-02-15 /pmc/articles/PMC7920756/ /pubmed/33587043 http://dx.doi.org/10.2196/21401 Text en ©Hsuan-Chia Yang, Md Mohaimenul Islam, Phung Anh Alex Nguyen, Ching-Huan Wang, Tahmina Nasrin Poly, Chih-Wei Huang, Yu-Chuan Jack Li. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 15.02.2021. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Yang, Hsuan-Chia
Islam, Md Mohaimenul
Nguyen, Phung Anh Alex
Wang, Ching-Huan
Poly, Tahmina Nasrin
Huang, Chih-Wei
Li, Yu-Chuan Jack
Development of a Web-Based System for Exploring Cancer Risk With Long-term Use of Drugs: Logistic Regression Approach
title Development of a Web-Based System for Exploring Cancer Risk With Long-term Use of Drugs: Logistic Regression Approach
title_full Development of a Web-Based System for Exploring Cancer Risk With Long-term Use of Drugs: Logistic Regression Approach
title_fullStr Development of a Web-Based System for Exploring Cancer Risk With Long-term Use of Drugs: Logistic Regression Approach
title_full_unstemmed Development of a Web-Based System for Exploring Cancer Risk With Long-term Use of Drugs: Logistic Regression Approach
title_short Development of a Web-Based System for Exploring Cancer Risk With Long-term Use of Drugs: Logistic Regression Approach
title_sort development of a web-based system for exploring cancer risk with long-term use of drugs: logistic regression approach
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7920756/
https://www.ncbi.nlm.nih.gov/pubmed/33587043
http://dx.doi.org/10.2196/21401
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