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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Simple Summary

The safety of long-term PPI use has increasingly raised concerns. We conducted a case-control study to explore the associations of PPI use with female cancer risks in specific age groups. Overall, PPI use was significantly associated with decreased risks of breast, cervical, endometrial, and ovarian cancers. PPIs were associated with a significant decrease in breast and ovarian cancer risks in 20–64-year-old users and a reduction in cervical and endometrial cancer risks in those aged 40–64 years. We hope that our findings based on real-world big data can provide researchers and clinicians with some possible insights. Further clinical studies are needed to elucidate the effects of PPIs on female cancers.

Abstract

Background: Firm conclusions about whether long-term proton pump inhibitor (PPI) drug use impacts female cancer risk remain controversial. Objective: We aimed to investigate the associations between PPI use and female cancer risks. Methods: A nationwide population-based, nested case-control study was conducted within Taiwan’s Health and Welfare Data Science Center’s databases (2000–2016) and linked to pathologically confirmed cancer data from the Taiwan Cancer Registry (1979–2016). Individuals without any cancer diagnosis during the 17 years of the study served as controls. Case and control patients were matched 1:4 based on age, gender, and visit date. Conditional logistic regression with 95% confidence intervals (CIs) was applied to investigate the association between PPI exposure and female cancer risks by adjusting for potential confounders such as the Charlson comorbidity index and medication usage (metformin, aspirin, and statins). Results: A total of 233,173 female cancer cases were identified, consisting of 135,437 diagnosed with breast cancer, 64,382 with cervical cancer, 19,580 with endometrial cancer, and 13,774 with ovarian cancer. After matching each case with four controls, we included 932,692 control female patients. The number of controls for patients with breast cancer, cervical cancer, endometrial cancer, and ovarian cancer was 541,748, 257,528, 78,320, and 55,096, respectively. The use of PPIs was significantly associated with reduced risk of breast cancer and ovarian cancer in groups aged 20–39 years (adjusted odds ratio (aOR): 0.69, 95%CI: 0.56–0.84; p < 0.001 and aOR: 0.58, 95%CI: 0.34–0.99; p < 0.05, respectively) and 40–64 years (aOR: 0.89, 95%CI: 0.86–0.94; p < 0.0001 and aOR: 0.87, 95%CI: 0.75–0.99; p < 0.05, respectively). PPI exposure was associated with a significant decrease in cervical and endometrial cancer risks in the group aged 40–64 years (with aOR: 0.79, 95%CI: 0.73–0.86; p < 0.0001 and aOR: 0.72, 95%CI: 0.65–0.81; p < 0.0001, respectively). In contrast, in elderly women, PPI use was found to be insignificantly associated with female cancers among users. Conclusions: Our findings, based on real-world big data, can depict a comprehensive overview of PPI usage and female cancer risk. Further clinical studies are needed to elucidate the effects of PPIs on female cancers.

Details

Title
Association between Proton Pump Inhibitor Use and the Risk of Female Cancers: A Nested Case-Control Study of 23 Million Individuals
Author
Nhi Thi Hong Nguyen 1 ; Huang, Chih-Wei 2   VIAFID ORCID Logo  ; Ching-Huan, Wang 3 ; Ming-Chin, Lin 4   VIAFID ORCID Logo  ; Hsu, Jason C 5   VIAFID ORCID Logo  ; Hsu, Min-Huei 6 ; Iqbal, Usman 7 ; Phung-Anh Nguyen 8   VIAFID ORCID Logo  ; Hsuan-Chia, Yang 9   VIAFID ORCID Logo 

 Health Personnel Training Institute, University of Medicine and Pharmacy, Hue University, Hue 491-20, Vietnam; School of Health Care Administration, College of Management, Taipei Medical University, Taipei 11031, Taiwan 
 International Center for Health Information Technology (ICHIT), College of Medical Science and Technology, Taipei Medical University, Taipei 106339, Taiwan 
 Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 106339, Taiwan; Biomedical Informatics & Data Science (BIDS) Section, School of Medicine, Johns Hopkins University, 2024 E Monument St, Suite 1-200, Baltimore, MD 21205, USA 
 Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 106339, Taiwan; Department of Neurosurgery, Shuang Ho Hospital, Taipei Medical University, New Taipei City 235041, Taiwan; Taipei Neuroscience Institute, Taipei Medical University, Taipei 110301, Taiwan 
 Clinical Data Center, Office of Data Science, Taipei Medical University, Taipei 106339, Taiwan; Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei 110301, Taiwan; Research Center of Health Care Industry Data Science, College of Management, Taipei Medical University, Taipei 110301, Taiwan; International Ph.D. Program in Biotech and Healthcare Management, College of Management, Taipei Medical University, Taipei 110301, Taiwan 
 Office of Data Science, Taipei Medical University, Taipei 110301, Taiwan; Graduate Institute of Data Science, College of Management, Taipei Medical University, Taipei 110301, Taiwan 
 Health ICT, Department of Health, Hobart, TAS 700, Australia; Global Health and Health Security Department, College of Public Health, Taipei Medical University, Taipei 11031, Taiwan 
 Clinical Data Center, Office of Data Science, Taipei Medical University, Taipei 106339, Taiwan; Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei 110301, Taiwan 
 International Center for Health Information Technology (ICHIT), College of Medical Science and Technology, Taipei Medical University, Taipei 106339, Taiwan; Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 106339, Taiwan; Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei 110301, Taiwan; Research Center of Big Data and Meta-Analysis, Wan Fang Hospital, Taipei Medical University, Taipei 116079, Taiwan 
First page
6083
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
20726694
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2756673088
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.