Adverse effects of proton pump inhibitors (PPIs) on the renal system using data mining algorithms (DMAs)

ABSTRACT

Background

Various adverse drug reactions (ADRs) are associated with proton pump inhibitors (PPIs). However, the effects of PPIs on the renal system are unclear so far. Thus, the main objective of the current study was to identify the possible signals of PPIs in the renal system.

Materials and Methods

Data mining algorithms such as proportional reporting ratio i.e. PRR (≥2) with associated chi-squared value (>4), reporting odds ratio i.e. ROR (≥2) with 95% confidence interval and case count (≥3) were calculated to identify a possible signal.

Results

The calculated PRR and ROR have indicated a positive signal of PPIs with suspected chronic kidney disease, acute kidney injury, renal failure, renal injury, and end-stage renal disease. The subgroup analysis results have shown a greater number of cases in the age group (18–64 years) as compared to other age groups whereas the number of cases in the female was found to be more as compared to males. The sensitivity analysis results have also shown no significant impact of concomitantly administered drugs on the outcome.

Conclusion

PPIs may be associated with various ADRs on the renal system.

Plain Language Summary

We have examined the adverse effects of proton pump inhibitors (PPIs) on the renal system using data from FDA Adverse Event Reporting System of the USA between 1 January 2004 and 30 September 2021. After doing the subgroup as well as sensitivity analysis, we have identified a positive signal of suspected chronic kidney disease, acute kidney injury, renal failure, renal injury, and end-stage renal disease with selected PPIs. Therefore, the adverse effects of selected PPIs on the renal system should be considered and further causality assessment should be performed to confirm the association.

KEYWORDS:

• Proton pump inhibitors
• signal detection
• renal system
• data mining algorithms (DMAs)

Acknowledgments

The authors are thankful to Vice-Chancellor Professor (Dr.) R.K. Goyal, Delhi Pharmaceutical Sciences & Research University (DPSRU), New Delhi 110017, India, for his continuous support, motivation and providing necessary facilities to carry out this work.

Declaration of interests

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Authors’ contributions

D Jain has conducted study, analysis and compilation of data; G Sharma has cross-checked the data and first draft of manuscript; A Kumar has designed the final draft and review of manuscript. All authors reviewed the manuscript.

Additional information

Funding

This paper was not funded.