Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Jun 13, 2020
Date Accepted: Jan 17, 2021
Development of a Web-based System for Exploring Cancer Risk with Long-term-use Drugs: A Logistic-Regression Approach
ABSTRACT
Background:
Existing epidemiological evidence remains controversial regarding the association between long-term use of drugs and cancer risk.
Objective:
We aimed to use a systems approach for exploring cancer risk with long-term-use drugs.
Methods:
A nationwide population-based nested case-control study was conducted within the National Health Insurance Research Database (NHIRD) sample cohort 1999-2013 in Taiwan. We identified cases who were aged 20 years and older, received treatment at least two months before the index date. We randomly selected control patients from the patient without cancer diagnosis during the 15 years (1999-2013) of the study periods. Cases and controls 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 drug and comorbidity.
Results:
There were 79,245 cancer cases and 316,980 matched controls included in this study. After using a systems approach for cancer risk with long-term-use drugs, a total of 47,080 associations were observed; however, 2,516 associations were significant. Benzodiazepine derivatives were associated with an increased risk of brain cancer (AOR: 1.37, 95%CI: 1.13-1.67). Statins were associated with reduced risk of liver cancer (AOR: 0.47, 95%CI: 0.42-0.51) and gastric cancer (AOR: 0.78, 95%CI: 0.67-0.90). A web-based system (http://ltd-cancer.aimhi.tw/) which includes comprehensive associations contains 2 domains: (1) Drug and cancer association, (2) Overview.
Conclusions:
Our study provided a systems approach for exploring cancer risk with long-term-use drugs by temporal model. Visualization of the associations could help to enlist the long-term-use drugs with personalized cancer risk and researchers directly would able to quantify them. It could also help develop research on chemoprevention, for example, conducting randomized control trials. Individuals with chronic diseases and a family history of cancer or high risk of specific cancer can also be prescribed with the more suitable drug. It would play an important role in personalized cancer prevention. Clinical Trial: N/A
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.