Log in

Incidence of Acute Renal Failure in Patients Using Levetiracetam Versus Other Antiseizure Medications: A Voluntary Post-Authorization Safety Study

  • Original Research Article
  • Published:
Drug Safety Aims and scope Submit manuscript

Abstract

Introduction

Acute kidney injury is an expected adverse drug reaction listed in the European Union (EU) Summary of Product Characteristics (SmPC) for levetiracetam, one of the most widely used modern antiseizure medications (ASMs).

Objective

We conducted a voluntary post-authorization safety study to characterize the rate of acute renal failure (ARF) in patients exposed to levetiracetam versus other ASMs.

Methods

New users of ASMs without prior renal dysfunction were identified and followed for 30 days in the IBM® MarketScan® database (USA, January 2008–December 2017). ARF was defined as a diagnosis on inpatient or emergency department claims. We estimated adjusted incidence rates, incidence rate ratios (IRRs), and incidence rate differences (IRDs) of ARF in patients initiating levetiracetam versus other ASMs.

Results

Overall, 110,336 patients were eligible for the monotherapy cohort and 96,215 were eligible for the polytherapy cohort. The overall crude rate of ARF following a new ASM was 6.0 and 6.5 per 10,000 patients for the ‘monotherapy’ and ‘polytherapy’ cohorts, respectively, in the first 30 days after the index date. In the monotherapy cohort, the IRR for ARF was 1.37 (95% confidence interval [CI] 0.80–2.34) and the corresponding IRD was 2.0 (95% CI − 1.12 to 5.12) additional ARFs per 10,000 patient-months. In the polytherapy cohort, the adjusted IRR for ARF was 0.94 (95% CI 0.51–1.74) and the corresponding IRD was − 0.42 cases per 10,000 patient-months (95% CI − 4.01 to 3.17).

Conclusions

The rate of ARFs in ASM new users was very low. In patients without prior ASMs, the estimated difference in risk of ARF associated with initiation of levetiracetam versus initiation of other ASMs was small, with 95% CIs compatible with small protective or harmful effects. In patients receiving polytherapy, the difference was compatible with the null and the 95% CI with small protective or harmful effects.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Germany)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Fisher RS, Acevedo C, Arzimanoglou A, Bogacz A, Cross JH, Elger CE, et al. ILAE official report: a practical clinical definition of epilepsy. Epilepsia. 2014;55(4):475–82.

    Article  Google Scholar 

  2. Beghi E, Giussani G, Nichols E, Abd-Allah F, Abdela J, Abdelalim A, et al. Global, regional, and national burden of epilepsy, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(4):357–75.

    Article  Google Scholar 

  3. Josephson CB, Engbers JDT, Jette N, Patten SB, Sajobi TT, Marshall D, et al. Prescription trends and psychiatric symptoms following first receipt of one of seven common antiepileptic drugs in general practice. Epilepsy Behav. 2018;84:49–55.

    Article  Google Scholar 

  4. Powell G, Logan J, Kiri V, Borghs S. Trends in antiepileptic drug treatment and effectiveness in clinical practice in England from 2003 to 2016: a retrospective cohort study using electronic medical records. BMJ Open. 2019;9(12): e032551.

    Article  Google Scholar 

  5. Thurman DJ, Faught E, Helmers S, Kim H, Kalilani L. New-onset lesional and nonlesional epilepsy in the US population: patient characteristics and patterns of antiepileptic drug use. Epilepsy Res. 2019;157: 106210.

    Article  Google Scholar 

  6. Spengler DC, Montouris GD, Hohler AD. Levetiracetam as a possible contributor to acute kidney injury. Clin Ther. 2014;36(8):1303–6.

    Article  CAS  Google Scholar 

  7. Choonara I, Star K. Levetiracetam and impaired renal function. WHO Pharm Newsl. 2016;2:18–23.

    Google Scholar 

  8. Vlasschaert MEO, Bejaimal SAD, Hackam DG, Quinn R, Cuerden MS, Oliver MJ, et al. Validity of administrative database coding for kidney disease: a systematic review. Am J Kidney Dis. 2011;57(1):29–43.

    Article  Google Scholar 

  9. Patel U, Hardy N, Smith D, Gurwitz J, Hsu C-Y, Parikh C, et al. Validation of acute kidney injury cases in the mini-sentinel distributed database. 2013. https://www.sentinelinitiative.org/sites/default/files/Drugs/Assessments/Mini-Sentinel_Validation-of-Acute-Kidney-Injury-Cases.pdf. Accessed 14 Apr 2022.

  10. Rewa O, Bagshaw SM. Acute kidney injury-epidemiology, outcomes and economics. Nat Rev Nephrol. 2014;10(4):193–207.

    Article  CAS  Google Scholar 

  11. Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159(7):702–6.

    Article  Google Scholar 

  12. Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart MA. High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology. 2009;20(4):512–22.

    Article  Google Scholar 

  13. Le HV, Poole C, Brookhart MA, Schoenbach VJ, Beach KJ, Layton JB, et al. Effects of aggregation of drug and diagnostic codes on the performance of the high-dimensional propensity score algorithm: an empirical example. BMC Med Res Methodol. 2013;13(1):142.

    Article  Google Scholar 

  14. Agency for Healthcare Research and Quality. HCUP CCS-services and procedures. Healthcare Cost and Utilization Project (HCUP). October 2020. Rockville: Agency for Healthcare Research and Quality; 2020.

    Google Scholar 

  15. Agency for Healthcare Research and Quality. Tools archive for clinical classifications software refined. Healthcare Cost and Utilization Project (HCUP). March 2021. Rockville: Agency for Healthcare Research and Quality; 2021.

    Google Scholar 

  16. Yau K, Burneo JG, Jandoc R, McArthur E, Muanda FT, Parikh CR, et al. Population-based study of risk of AKI with levetiracetam. Clin J Am Soc Nephrol. 2019;14(1):17–26.

    Article  Google Scholar 

  17. Faught E, Helmers S, Thurman D, Kim H, Kalilani L. Patient characteristics and treatment patterns in patients with newly diagnosed epilepsy: a US database analysis. Epilepsy Behav. 2018;85:37–44.

    Article  Google Scholar 

  18. Chubak J, Pocobelli G, Weiss NS. Tradeoffs between accuracy measures for electronic health care data algorithms. J Clin Epidemiol. 2012;65(3):343-9.e2.

    Article  Google Scholar 

  19. Greenland S, Lash T. Bias analysis. In: Rothman K, Greenland S, Lash T, editors. Modern epidemiology. 3rd ed. Philadelphia: Lippincott Williams & Wilkins; 2008. p. 345–80.

    Google Scholar 

  20. Ryan PB, Schuemie MJ, Ramcharran D, Stang PE. Atypical antipsychotics and the risks of acute kidney injury and related outcomes among older adults: a replication analysis and an evaluation of adapted confounding control strategies. Drugs Aging. 2017;34(3):211–9.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

Nada Boudiaf, David Friesen, and Kathrin Haeffs contributed to the validation of the analysis. The authors acknowledge Kathleen Richards, PhD (UCB Pharma, Smyrna, GA, USA) for publication coordination.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Raphaelle Beau-Lejdstrom.

Ethics declarations

Funding

Work on this manuscript was funded by UCB Pharma.

Conflicts of interest/competing interests

Lai San Hong was an independent contractor for UCB Pharma. Xabier Garcia de Albeniz and Susana Perez-Gutthann are employees of RTI-HS and were contracted to perform work on this study and manuscript, funded by UCB Pharma. Raphaelle Beau-Lejdstrom is a salaried employee of UCB Pharma and stockholder. Francois Bonfitto, Florin Floricel, Christian Loesch, and Isabelle Mottet are salaried UCB Pharma employees and stockholders. Linda Kalilani, Graham Luscombe, and Nadia Foskett were employees of UCB Pharma at the time this study was conducted. Johan Lorenzen has received fees for consulting and expert testimony relating to the subject matter discussed in this manuscript.

Availability of data and material

The dataset (IBM® MarketScan® Research Databases) generated and/or analyzed during the current study are not publicly available but are available from IBM® on reasonable request.

Code availability

Available from David Friesen (David.Friesen@ucb.com).

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Authors’ contributions

RBL designed the study, contributed to the analysis, interpreted the data, and revised and approved the final version to be published. LSH contributed to the design of the study, analyzed the data, revised the manuscript, and approved the final version to be published. FF, JL, FB, LK, GL, CL, SPG, IM, and NF contributed to the design of the study and revised and approved the final version to be published. XGA contributed to the analysis and interpretation of the data, drafted the manuscript, and approved the final version to be published.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Beau-Lejdstrom, R., Hong, L.S., Garcia de Albeniz, X. et al. Incidence of Acute Renal Failure in Patients Using Levetiracetam Versus Other Antiseizure Medications: A Voluntary Post-Authorization Safety Study. Drug Saf 45, 781–790 (2022). https://doi.org/10.1007/s40264-022-01193-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40264-022-01193-0

Navigation