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基于网络的长期用药癌症风险探索系统的开发:逻辑回归方法

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

作者信息

Yang Hsuan-Chia, Islam Md Mohaimenul, Nguyen Phung Anh Alex, Wang Ching-Huan, Poly Tahmina Nasrin, Huang Chih-Wei, Li Yu-Chuan Jack

机构信息

Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.

International Center for Health Information Technology, Taipei Medical University, Taipei, Taiwan.

出版信息

JMIR Public Health Surveill. 2021 Feb 15;7(2):e21401. doi: 10.2196/21401.

Abstract

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.

摘要

背景

关于长期用药与癌症风险之间关联的现有流行病学证据仍存在争议。

目的

我们旨在全面了解长期用药的癌症风险。

方法

在台湾1999年至2013年国民健康保险研究数据库样本队列中进行了一项基于全国人群的巢式病例对照研究。我们确定了在索引日期前接受至少两个月治疗的20岁及以上成年人中的病例。我们从研究期间15年(1999 - 2013年)内未患癌症诊断的患者中随机选择对照患者。病例和对照患者根据年龄、性别和就诊日期按1:4进行匹配。使用条件逻辑回归通过调整潜在混杂因素(如药物和合并症)来估计药物暴露与癌症风险之间的关联。

结果

本研究纳入了79,245例癌症病例和316,980例匹配对照。在45,368个关联中,分别有2419、1302、662和366个关联在P <.05、P <.01、P <.001和P <.0001水平上具有统计学意义。苯二氮䓬衍生物与脑癌风险增加相关(调整后的优势比[AOR]为1.379,95%置信区间为1.138 - 1.670;P = 0.001)。他汀类药物与肝癌风险降低相关(AOR为0.470,95%置信区间为0.426 - 0.517;P <.0001)和胃癌风险降低相关(AOR为0.781,95%置信区间为0.678 - 0.900;P <.001)。我们基于网络的系统收集了关联的综合数据,包含2个领域:(1)药物与癌症关联页面和(2)概述页面。

结论

我们基于网络的系统提供了药物 - 癌症关联的综合量化数据概述。随着所有量化数据的可视化,该系统有望促进对癌症风险和预防的进一步研究,有可能成为咨询和探索长期用药与癌症风险之间关联的垫脚石。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc98/7920756/169cefbc8843/publichealth_v7i2e21401_fig1.jpg

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