Individualized prevention of proton pump inhibitor related adverse events by risk stratification

Bin Xia, Qiangsheng He, Fang Gao Smith, V. Georgios Gkoutos, Krishnarajah Nirantharakumar, Zi Chong Kuo, Danni Wang, Qi Feng, Eddie C. Cheung, Lunzhi Dai, Junjie Huang, Yuanyuan Yu, Wenbo Meng (), Xiwen Qin () and Jinqiu Yuan ()
Additional contact information
Bin Xia: Sun Yat-sen University
Qiangsheng He: Sun Yat-sen University
Fang Gao Smith: University of Birmingham
V. Georgios Gkoutos: University Hospitals Birmingham NHS Foundation Trust
Krishnarajah Nirantharakumar: University of Birmingham, Edgbaston
Zi Chong Kuo: Sun Yat-sen University
Danni Wang: Sun Yat-sen University
Qi Feng: University of Oxford
Eddie C. Cheung: Sun Yat-sen University
Lunzhi Dai: Sichuan University
Junjie Huang: The Chinese University of Hong Kong, Sha Tin
Yuanyuan Yu: The Chinese University of Hong Kong, Sha Tin
Wenbo Meng: The First Hospital of Lanzhou University
Xiwen Qin: University of Western Australia
Jinqiu Yuan: Sun Yat-sen University

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract Proton pump inhibitors (PPIs) are commonly used for gastric acid-related disorders, but their safety profile and risk stratification for high-burden diseases need further investigation. Analyzing over 2 million participants from five prospective cohorts from the US, the UK, and China, we found that PPI use correlated with increased risk of 15 leading global diseases, such as ischemic heart disease, diabetes, respiratory infections, and chronic kidney disease. These associations showed dose-response relationships and consistency across different PPI types. PPI-related absolute risks increased with baseline risks, with approximately 82% of cases occurring in those at the upper 40% of the baseline predicted risk, and only 11.5% of cases occurring in individuals at the lower 50% of the baseline risk. While statistical association does not necessarily imply causation, its potential safety concerns suggest that personalized use of PPIs through risk stratification might guide appropriate decision-making for patients, clinicians, and the public.

Date: 2024
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DOI: 10.1038/s41467-024-48007-8

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