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International Journal of Clinical Pharmacy

, Volume 40, Issue 4, pp 903–910 | Cite as

Comparison of different methods for causality assessment of adverse drug reactions

  • Sapan Kumar Behera
  • Saibal Das
  • Alphienes Stanley Xavier
  • Srinivas Velupula
  • Selvarajan SandhiyaEmail author
Research Article

Abstract

Background The causality assessment of adverse drug reactions (ADRs) remains a challenge, and none of the different available method of causality assessment used for assessing adverse reactions has been universally accepted as the gold standard. Objective To examine the agreement and correlation among three broad approaches for causality assessment of ADRs viz. World Health Organization-Uppsala Monitoring Centre (WHO-UMC) system, Naranjo algorithm, and updated Logistic method. Setting ADR monitoring centre (AMC) of a tertiary care teaching hospital in India. Method A total of 230 cases of ADR from April 2017 to August 2017 were retrospectively analyzed by each of these three methods. The agreement among the different methods was calculated by Cohen’s kappa (κ), and Spearman’s correlation was used to find the correlation among these methods. Main outcome measures Cohen’s kappa value and Spearman’s correlation coefficient for comparison among the different methods. Results The Cohen’s κ used for analyzing the agreement between WHO-UMC system and Naranjo algorithm was 0.45, between WHO-UMC system and updated Logistic method was 0.405, and between Naranjo algorithm and updated Logistic method was 0.606. The Spearman’s correlation coefficient was 0.793 for Naranjo algorithm vs. updated Logistic method, 0.735 for WHO-UMC system vs. Naranjo algorithm, and 0.696 for WHO-UMC system vs. updated Logistic method. Conclusion Causality assessment based on objective measurements (scores and probabilities) like updated Logistic method and Naranjo algorithm are less prone to subjective variations compared to the WHO-UMC system which is based on expert judgement.

Keywords

Adverse drug reaction ADRs Causality assessment Naranjo algorithm Updated Logistic method WHO-UMC system 

Notes

Acknowledgement

We are grateful to the physicians, surgeons, and heads of the respective departments for reporting the ADR cases to the AMC, JIPMER, Puducherry.

Funding

No funding was obtained for this work.

Conflicts of interest

The author(s) declared no potential conflicts of interest concerning the research, authorship, and publication of this article.

References

  1. 1.
    Théophile H, André M, Miremont-Salamé G, Arimone Y, Bégaud B. Comparison of three methods (an updated logistic probabilistic method, the Naranjo and Liverpool algorithms) for the evaluation of routine pharmacovigilance case reports using consensual expert judgement as reference. Drug Saf. 2013;36:1033–44.CrossRefPubMedGoogle Scholar
  2. 2.
    Khan LM, Al-Harthi SE, Osman AM, Sattar MA, Ali AS. Dilemmas of the causality assessment tools in the diagnosis of adverse drug reactions. Saudi Pharm J SPJ Off Publ Saudi Pharm Soc. 2016;24:485–93.Google Scholar
  3. 3.
    Hire RC, Kinage PJ, Gaikward NN. Causality assessment in pharmacovigilance: a step towards quality care. Sch J App Med Sci. 2013;1:386–92.Google Scholar
  4. 4.
    Agbabiaka TB, Savovic J, Ernst E. Methods for causality assessment of adverse drug reactions: a systematic review. Drug Saf. 2008;31:21–38.CrossRefPubMedGoogle Scholar
  5. 5.
    Wiholm BE. The Swedish drug-event assessment methods. Special workshop—regulatory. Drug Inf J. 1984;18:267–9.CrossRefPubMedGoogle Scholar
  6. 6.
    Naidu RP. Causality assessment: a brief insight into practices in pharmaceutical industry. Perspect Clin Res. 2013;4(4):233–6.CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    US Food and Drug Administration; [Last accessed on 2012 Dec 30]. Safety reporting requirements for INDs and BA/BE studies. In: Guidance for industry and investigators. http://www.fda.gov/downloads/Drugs/…/Guidances/UCM227351.pdf.
  8. 8.
    European Medicines Agency and Heads of Medicines Agencies; [Last accessed on 2012 Dec 30]. Module VI—Management and reporting of adverse reactions to medicinal products (Rev 1). In: Guideline on good pharmacovigilance practices (GVP). http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2012/06/WC500129135.pdf.
  9. 9.
    Thaker SJ, Sinha RS, Gogtay NJ, Thatte UM. Evaluation of inter-rater agreement between three causality assessment methods used in pharmacovigilance. J Pharmacol Pharmacother. 2016;7:31–3.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Marante KB. The challenges of adverse drug reaction evaluation. J Pharmacovigilance. 2018;6(3):1–4 (in press).CrossRefGoogle Scholar
  11. 11.
    Lanctôt KL, Naranjo CA. Computer-assisted evaluation of adverse events using a Bayesian approach. J Clin Pharmacol. 1994;34:142–7.CrossRefPubMedGoogle Scholar
  12. 12.
    Arimone Y, Bégaud B, Miremont-Salamé G, Fourrier-Réglat A, Molimard M, Moore N, et al. A new method for assessing drug causation provided agreement with experts’ judgment. J Clin Epidemiol. 2006;59(3):308–14.CrossRefPubMedGoogle Scholar
  13. 13.
    Théophile H, André M, Arimone Y, Haramburu F, Miremont-Salamé G, Bégaud B. An updated method improved the assessment of adverse drug reaction in routine pharmacovigilance. J Clin Epidemiol. 2012;65:1069–77.CrossRefPubMedGoogle Scholar
  14. 14.
    Kyonen M, Folatre I, Lagos X, Vargas S. Comparison of two methods to assess causality of adverse drug reactions. Rev Med Chil. 2015;143:880–6.CrossRefPubMedGoogle Scholar
  15. 15.
    Kane-Gill SL, Forsberg EA, Verrico MM, Handler SM. Comparison of three pharmacovigilance algorithms in the ICU setting: a retrospective and prospective evaluation of ADRs. Drug Saf. 2012;35:645–53.CrossRefPubMedGoogle Scholar
  16. 16.
    Lucena MI, Camargo R, Andrade RJ, Perez-Sanchez CJ, Sanchez De La Cuesta F. Comparison of two clinical scales for causality assessment in hepatotoxicity. Hepatololgy. 2001;33:123–30.CrossRefGoogle Scholar
  17. 17.
    Mittal N, Gupta MC. Comparison of agreement and rational uses of the WHO and Naranjo adverse event causality assessment tools. J Pharmacol Pharmacother. 2015;6:91.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Mouton JP, Mehta U, Rossiter DP, Maartens G, Cohen K. Interrater agreement of two adverse drug reaction causality assessment methods: a randomised comparison of the Liverpool adverse drug reaction causality assessment tool and the world health organization-uppsala monitoring centre system. PLoS ONE. 2017;12:e0172830.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Son M-K, Lee Y-W, Jung H-Y, Yi S-W, Lee K-H, Kim S-U, et al. Comparison of the Naranjo and WHO-Uppsala Monitoring Centre criteria for causality assessment of adverse drug reactions. Korean J Med. 2008;74:181–7.Google Scholar
  20. 20.
    Rehan HS, Chopra D, Kakkar AK. Causality assessment of spontaneously reported adverse drug events: comparison of WHO-UMC criteria and Naranjo probability scale. Int J Risk Saf Med. 2007;19:223–7.Google Scholar
  21. 21.
    Sharma S, Gupta AK, Reddy GJ. Inter-rater and intra-rater agreement in causality assessment of adverse drug reactions: a comparative study of WHO-UMC versus Naranjo scale. Int J Res Med Sci. 2017;5:4389–94.CrossRefGoogle Scholar
  22. 22.
    Belhekar MN, Taur SR, Munshi RP. A study of agreement between the Naranjo algorithm and WHO-UMC criteria for causality assessment of adverse drug reactions. Indian J Pharmacol. 2014;46:117.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Varallo FR, Planeta CS, Herdeiro MT, Mastroianni PdeC. Imputation of adverse drug reactions: causality assessment in hospitals. PLoS ONE. 2017;12:e0171470.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Théophile H, Arimone Y, Miremont-Salamé G, Moore N, Fourrier-Réglat A, Haramburu F, et al. Comparison of three methods (consensual expert judgement, algorithmic and probabilistic approaches) of causality assessment of adverse drug reactions: an assessment using reports made to a French pharmacovigilance centre. Drug Saf. 2010;33:1045–54.CrossRefPubMedGoogle Scholar
  25. 25.
    The use of the WHO-UMC system for standardised case causality assessment. https://www.WHO-UMC.org/media/2768/standardised-case-causality-assessment.pdf. Accessed 27 Oct 2017.
  26. 26.
    Naranjo CA, Busto U, Sellers EM, Sandor P, Ruiz I, Roberts EA, et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther. 1981;30:239–45.CrossRefPubMedGoogle Scholar
  27. 27.
    Pharmacovigilance programme of India. http://www.ipc.gov.in/PvPI/pv_home.html. Accessed 30 Oct 2017.
  28. 28.
    Ganesan S, Sandhiya S, Reddy KC, Subrahmanyam DK, Adithan C. The impact of the educational intervention on knowledge, attitude, and practice of pharmacovigilance toward adverse drug reactions reporting among health-care professionals in a tertiary care hospital in South India. J Nat Sci Biol Med. 2017;8:203–9.CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Palaniappan M, Selvarajan S, George M, Subramaniyan G, Dkhar SA, Pillai AA, et al. Pattern of adverse drug reactions reported with cardiovascular drugs in a tertiary care teaching hospital. J Clin Diagn Res. 2015;9:FC01-04.Google Scholar
  30. 30.
    Behera SK, Kishtapati CR, Gunaseelan V, Dubashi B, Chandrasekaran A, Selvarajan S. Chemotherapy induced adverse drug reactions in cancer patients in a tertiary care hospital in South India. J Young Pharm. 2017;9:593–7.CrossRefGoogle Scholar
  31. 31.
    Davies EC, Rowe PH, James S, Nickless G, Ganguli A, Danjuma M, et al. An investigation of disagreement in causality assessment of adverse drug reactions. Pharm Med. 2011;25:17–24.CrossRefGoogle Scholar
  32. 32.
    Cantor AB. Sample-size calculations for Cohen’s Kappa. Psychol Methods. 1996;1:350–3.CrossRefGoogle Scholar
  33. 33.
    Byrt T. Sample-size calculations for Cohen’s kappa. Epidemiology. 1996;7:561.CrossRefPubMedGoogle Scholar
  34. 34.
    Macedo AF, Marques FB, Ribeiro CF, Teixeira F. Causality assessment of adverse drug reactions: comparison of the results obtained from published decisional algorithms and from the evaluations of an expert panel, according to different levels of imputability. J Clin Pharm Ther. 2003;28:137–43.CrossRefPubMedGoogle Scholar
  35. 35.
    Lei H, Rehman A, Haq A. Adverse drug reaction reports in Malaysia: comparison of causality assessments. Malays J Pharm Sci. 2007;5:7–17.Google Scholar
  36. 36.
    Safety of medicines—a guide to detecting and reporting adverse drug reactions—why health professionals need to take action. http://apps.who.int/medicinedocs/en/d/Jh2992e/. Accessed 26 Oct 2017.

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Sapan Kumar Behera
    • 1
  • Saibal Das
    • 1
  • Alphienes Stanley Xavier
    • 1
  • Srinivas Velupula
    • 1
    • 2
  • Selvarajan Sandhiya
    • 1
    Email author
  1. 1.Department of Clinical PharmacologyJawaharlal Institute of Postgraduate Medical Education and Research (JIPMER)PuducherryIndia
  2. 2.Department of PharmacologyKakatiya Medical College/MGM HospitalWarangalIndia

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