Skip to main content

Advertisement

SpringerLink
Log in

A case–control study on the clinical characteristics of granisetron-related arrhythmias and the development of a predictive nomogram

  • Research Article
  • Published:
International Journal of Clinical Pharmacy Aims and scope Submit manuscript

Abstract

Background

Automatic monitoring and assessment are increasingly employed in drug safety evaluations using hospital information system data. The increasing concern about granisetron-related arrhythmias requires real-world studies to improve our understanding of its safety.

Aim

This study aimed to analyze the incidence, clinical characteristics, and risk factors of granisetron-related arrhythmias in hospitalized patients using real-world data obtained from the Adverse Drug Event Active Surveillance and Assessment System-II (ADE-ASAS-II) and concurrently aimed to develop and validate a nomogram to predict the occurrence of arrhythmias.

Method

Retrospective automatic monitoring of inpatients using granisetron was conducted in a Chinese hospital from January 1, 2017, to December 31, 2021, to determine the incidence of arrhythmias using ADE-ASAS- II. Propensity score matching was used to balance confounders and analyze clinical characteristics. Based on risk factors identified through logistic regression analysis, a prediction nomogram was established and internally validated using the Bootstrap method.

Results

Arrhythmias occurred in 178 of 72,508 cases taking granisetron with an incidence of 0.3%. Independent risk factors for granisetron-related arrhythmias included medication duration, comorbid cardiovascular disease, concomitant use of other 5-hydroxytryptamine 3 receptor antagonists, alanine aminotransferase > 40 U/L, and blood urea nitrogen > 7.5 mmol/L. The nomogram demonstrated good differentiation and calibration, with enhanced clinical benefit observed when the risk threshold ranged from 0.10 to 0.82.

Conclusion

The nomogram, based on the five identified independent risk factors, may be valuable in predicting the risk of granisetron-related arrhythmias in the administered population, offering significant clinical applications.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Frommeyer G, Eckardt L. Drug-induced proarrhythmia: risk factors and electrophysiological mechanisms. Nat Rev Cardiol. 2016;13(1):36–47.

    Article  CAS  PubMed  Google Scholar 

  2. Tisdale JE, Chung MK, Campbell KB, et al. Drug-induced arrhythmias: a scientific statement from the American heart association. Circulation. 2020;142(15):e214–33.

    Article  PubMed  Google Scholar 

  3. Shah RR. Drugs, QTc interval prolongation and final ICH E14 guideline: an important milestone with challenges ahead. Drug Saf. 2005;28(11):1009–28.

    Article  CAS  PubMed  Google Scholar 

  4. Shah RR. If a drug deemed “safe” in nonclinical tests subsequently prolongs QT in phase 1 studies, how can its sponsor convince regulators to allow development to proceed? Pharmacol Ther. 2008;119(2):215–21.

    Article  CAS  PubMed  Google Scholar 

  5. Weibel S, Rücker G, Eberhart LH, et al. Drugs for preventing postoperative nausea and vomiting in adults after general anaesthesia: a network meta-analysis. Cochrane Database Syst Rev. 2020;10(10):Cd012859.

    PubMed  Google Scholar 

  6. Kienbaum P, Schaefer MS, Weibel S, et al. Update on PONV-What is new in prophylaxis and treatment of postoperative nausea and vomiting?: summary of recent consensus recommendations and cochrane reviews on prophylaxis and treatment of postoperative nausea and vomiting. Anaesthesist. 2022;71(2):123–8.

    Article  CAS  PubMed  Google Scholar 

  7. Brygger L, Herrstedt J. 5-Hydroxytryptamine3 receptor antagonists and cardiac side effects. Expert Opin Drug Saf. 2014;13(10):1407–22.

    Article  CAS  PubMed  Google Scholar 

  8. Buyukavci M, Olgun H, Ceviz N. The effects of ondansetron and granisetron on electrocardiography in children receiving chemotherapy for acute leukemia. Am J Clin Oncol. 2005;28(2):201–4.

    Article  CAS  PubMed  Google Scholar 

  9. Tricco AC, Blondal E, Veroniki AA, et al. Comparative safety and effectiveness of serotonin receptor antagonists in patients undergoing chemotherapy: a systematic review and network meta-analysis. BMC Med. 2016;14(1):216.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Bennett K, Cahir C, Sorensen J. Costs associated with adverse drug reactions in an older population admitted to hospital: a prospective cohort study. Eur J Clin Pharmacol. 2023;79(10):1417–24.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Rochoy M, Auffret M, BéNé J, et al. Antiemetics and cardiac effects potentially linked to prolongation of the QT interval: case/non-case analysis in the national pharmacovigilance database. Rev Epidemiol Sante Publique. 2017;65(1):1–8.

    Article  CAS  PubMed  Google Scholar 

  12. Ritchie HE, Huss IB, Webster WS. The effect of anti-emetic drugs on rat embryonic heart activity. Reprod Toxicol. 2019;87:140–5.

    Article  CAS  PubMed  Google Scholar 

  13. de Lorenzi FG, Bridal TR, Spinelli W. Block of the delayed rectifier current (IK) by the 5-HT3 antagonists ondansetron and granisetron in feline ventricular myocytes. Br J Pharmacol. 1994;113(2):527–35.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Cakir FB, Yapar O, Canpolat C, et al. Cardiac effects of granisetron in a prospective crossover randomized dose comparison trial. Support Care Cancer. 2012;20(10):2451–7.

    Article  CAS  PubMed  Google Scholar 

  15. Iasonos A, Schrag D, Raj GV, et al. How to build and interpret a nomogram for cancer prognosis. J Clin Oncol. 2008;26(8):1364–70.

    Article  PubMed  Google Scholar 

  16. Wang L, Yang L, Li T, et al. Development and validation of nomogram for the prediction of malignant ventricular arrhythmia including circulating inflammatory cells in patients with acute ST-segment elevation myocardial infarction. J Inflamm Res. 2023;16:3185–96.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Guo H, Guo D, Gao A, et al. Establishment and validation of automatic monitoring module for drug-induced arrhythmia based on data of HIS. Chin J Drug Appl Monit. 2022;19(3):176–81.

    Google Scholar 

  18. Mavroudis C, Stulak JM, Ad N, et al. Prophylactic atrial arrhythmia surgical procedures with congenital heart operations: review and recommendations. Ann Thorac Surg. 2015;99(1):352–9.

    Article  PubMed  Google Scholar 

  19. Naranjo CA, Busto U, Sellers EM, et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther. 1981;30(2):239–45.

    Article  CAS  PubMed  Google Scholar 

  20. Peduzzi P, Concato J, Kemper E, et al. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49(12):1373–9.

    Article  CAS  PubMed  Google Scholar 

  21. Chen C, Jia W, Guo D, et al. Development of a computer-assisted adverse drug events alarm and assessment system for hospital inpatients in China. Ther Innov Regul Sci. 2020;54(1):32–41.

    Article  PubMed  Google Scholar 

  22. Costa C, Abeijon P, Rodrigues DA, et al. Factors associated with underreporting of adverse drug reactions by patients: a systematic review. Int J Clin Pharm. 2023;45(6):1349–58.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Reiffel JA. Propensity score matching: the “devil is in the details” where more may be hidden than you know. Am J Med. 2020;133(2):178–81.

    Article  PubMed  Google Scholar 

  24. Tricco AC, Soobiah C, Blondal E, et al. Comparative safety of serotonin (5-HT3) receptor antagonists in patients undergoing surgery: a systematic review and network meta-analysis. BMC Med. 2015;13:142.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Mason JW, Selness DS, Moon TE, et al. Pharmacokinetics and repolarization effects of intravenous and transdermal granisetron. Clin Cancer Res. 2012;18(10):2913–21.

    Article  CAS  PubMed  Google Scholar 

  26. Raftopoulos H, Cooper W, O’Boyle E, et al. Comparison of an extended-release formulation of granisetron (APF530) versus palonosetron for the prevention of chemotherapy-induced nausea and vomiting associated with moderately or highly emetogenic chemotherapy: results of a prospective, randomized, double-blind, noninferiority phase 3 trial. Support Care Cancer. 2015;23(3):723–32.

    Article  PubMed  Google Scholar 

  27. Savant K, Khandeparker RV, Berwal V, et al. Comparison of ondansetron and granisetron for antiemetic prophylaxis in maxillofacial surgery patients receiving general anesthesia: a prospective, randomised, and double blind study. J Korean Assoc Oral Maxillofac Surg. 2016;42(2):84–9.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Kleiber N, Gariépy-Assal L, Coulombe J, et al. Off-label use and safety of drug use in vascular anomalies. Dermatology. 2021;237(4):649–57.

    Article  CAS  PubMed  Google Scholar 

  29. Tisdale JE, Jaynes HA, Kingery JR, et al. Development and validation of a risk score to predict QT interval prolongation in hospitalized patients. Circ Cardiovasc Qual Outcomes. 2013;6(4):479–87.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Ma M, Zhi H, Yang S, et al. Body mass index and the risk of atrial fibrillation: a mendelian randomization study. Nutrients. 2022;14(9):1878.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Jupiter DC. Propensity score matching: retrospective randomization? J Foot Ankle Surg. 2017;56(2):417–20.

    Article  PubMed  Google Scholar 

  32. Zeltser D, Justo D, Halkin A, et al. Torsade de pointes due to noncardiac drugs: most patients have easily identifiable risk factors. Medicine. 2003;82(4):282–90.

    Article  PubMed  Google Scholar 

  33. FDA Drug Safety Communication: Updated information on 32 mg intravenous ondansetron (Zofran) dose and pre-mixed ondansetron products. 2012.

  34. Prasad M, Shashidar VK, Chakraborty A. Palonosetron-induced ventricular tachycardia in a patient receiving cancer chemotherapy. Cureus. 2017;9(7):e1480.

    Google Scholar 

  35. Wolf H. Preclinical and clinical pharmacology of the 5-HT3 receptor antagonists. Scand J Rheumatol Suppl. 2000;113:37–45.

    Article  CAS  PubMed  Google Scholar 

  36. Geurts S, van der Burgh AC, Bos MM, et al. Disentangling the association between kidney function and atrial fibrillation: a bidirectional mendelian randomization study. Int J Cardiol. 2022;355:15–22.

    Article  PubMed  Google Scholar 

  37. Liu EQ, Zeng CL. Blood urea nitrogen and in-hospital mortality in critically Ill patients with cardiogenic shock: analysis of the MIMIC-III database. Biomed Res Int. 2021;2021:5948636.

    PubMed  PubMed Central  Google Scholar 

  38. Yu C, Guo D, Yao C, et al. Development and validation of a nomogram for predicting drug-induced acute kidney injury in hospitalized patients: a case-control study based on propensity-score matching. Front Pharmacol. 2021;12:657853.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This study was supported by the Key Project Medical Innovation Project in 2017 (No. 17CXZ010) and “The Project of Monitoring and Evaluation of the Use of Key Clinical Drugs” commissioned by the Chinese Association of Research Hospitals (No. Y2023FH-YWPJ03).

Author information

Authors and Affiliations

  1. Chinese People’s Liberation Army Medical School, Beijing, 100853, China

    Peng Li, Haili Guo, An Fu & Anqi Zhao

  2. Department of Pharmacy, Medical Supplies Center, Chinese People’s Liberation Army General Hospital, Beijing, 100853, China

    Peng Li, Man Zhu, Ao Gao, Haili Guo, An Fu, Anqi Zhao & Daihong Guo

Authors
  1. Peng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Man Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ao Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Haili Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. An Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Anqi Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Daihong Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Daihong Guo.

Ethics declarations

Conflicts of interest

The authors declare no conflicts of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, P., Zhu, M., Gao, A. et al. A case–control study on the clinical characteristics of granisetron-related arrhythmias and the development of a predictive nomogram. Int J Clin Pharm 46, 684–693 (2024). https://doi.org/10.1007/s11096-024-01703-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11096-024-01703-3

Keywords

Search

Navigation