A COMPARISON OF CAUSALITY ASSESSMENT TOOLS FOR SUSPECTED ADVERSE DRUG REACTIONS IN HOSPITALIZED PATIENTS AT A TERTIARY CARE HOSPITAL
Objective: The objective of the study was to compare six causality assessment (CA) tools for suspected adverse drug reactions (ADRs) reported in hospitalized patients at a tertiary care hospital in India.
Methods: Intensive ADR monitoring was performed in indoor patients of two randomly selected medicine units. A detailed case report of each suspected ADR (n=120) was provided to six independent experts for CA using either visual analog scale (VAS) or WHO-UMC scale. Investigator assessed causality using Naranjo’s scale, Koh et al. scale, the French method, and Karch and Lasagna scale. Similar causality categories from these scales were coded for correlation. Agreement among experts and that between various CA tools were analyzed using Cohen’s kappa and Fleiss kappa. Reasons for disagreements among different scales were evaluated.
Results: A variation was observed in the total number of drugs suspected to cause ADR by experts and investigator. “Likely” and “Plausible” causality were suggested frequently by experts using VAS whereas “Possible” causal association was frequent according to experts using the WHO-UMC scale and also by the investigator using algorithms except Koh et al. scale. None to the slight agreement was observed among experts who used VAS (k=0.117), whereas a substantial agreement was observed among experts using the WHO-UMC scale (k=0.707). A substantial agreement was observed between Karch and Lasagna scale and the French method (k=0.740). Both scales demonstrated moderate agreement with Naranjo’s scale. Disagreement among the WHO-UMC scale, the French method, and Karch and Lasagna scale were associated with polypharmacy, serious ADRs, non-availability of laboratory data, and skin and subcutaneous tissue ADRs.
Conclusion: A higher inter-rater agreement with the WHO-UMC scale suggests its utility for CA of suspected ADRs in indoor patients. The French method and Karch and Lasagna scale can be used for CA in hospitalized patients as an adjunct to Naranjo’s scale. Factors associated with disagreement should be considered at the time of reporting ADRs and evaluating causality.
2. Leape LL, Bates DW, Cullen DJ, Cooper J, Demonaco HJ, Gallivan T. Systems analysis of adverse drug events. ADE prevention study group. J Am Med Assoc 1995;274:35-43.
3. Arimone Y, Miremont-Salamé G, Haramburu F, Molimard M, Moore N, Fourrier-Réglat A, et al. Inter-expert agreement of seven criteria in causality assessment of adverse drug reactions. Br J Clin Pharmacol 2007;64:482-8.
4. World Health Organization, Uppsala Monitoring Centre. The Use of the WHO-UMC System for Standardized Case Causality Assessment. Geneva: World Health Organization; 2005. p. 2-7. Available from: http://www.who-umc.org/Graphics/24734.pdf.
5. Arimone Y, Bégaud B, Miremont-Salamé G, Fourrier-Réglat A, Moore N, Molimard M, et al. Agreement of expert judgment in causality assessment of adverse drug reactions. Eur J Clin Pharmacol 2005;61:169-73.
6. 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.
7. 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.
8. Koh Y, Li SC. A new algorithm to identify the causality of adverse drug reactions. Drug Saf 2005;28:1159-61.
9. Karch FE, Lasagna L. Toward the operational identification of adverse drug reactions. Clin Pharmacol Ther 1977;21:247-54.
10. Begaud B. Standardized assessment of adverse drug reactions: The method used in France. Special workshop--clinical. Drug Inf J 1984;18:275-81.
11. 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.
12. Koh Y, Yap CW, Li SC. A quantitative approach of using genetic algorithm in designing a probability scoring system of an adverse drug reaction assessment system. Int J Med Inform 2008;77:421-30.
13. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;2:307-10.
14. Liao JJ. Sample size calculation for an agreement study. Pharm Stat 2010;9:125-32.
15. Rotondi MA, Donner A. A confidence interval approach to sample size estimation for interobserver agreement studies with multiple raters and outcomes. J Clin Epidemiol 2012;65:778-84.
16. Hartwig SC, Siegel J, Schneider PJ. Preventability and severity assessment in reporting adverse drug reactions. Am J Hosp Pharm 1992;49:2229-32.
17. Schumock GT, Thornton JP. Focusing on the preventability of adverse drug reactions. Hosp Pharm 1992;27:538.
18. Cohen J. A coefficient of agreement for nominal scales. Educ Psychol Meas 1960;20:37-46.
19. Fleiss JL. Measuring nominal scale agreement among many raters. Psychol Bull 1971;76:378-82.
20. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159-74.
21. McHugh ML. Interrater reliability: The kappa statistic. Biochem Med (Zagreb) 2012;22:276-82.
22. Doshi MS, Patel PP, Shah SP. Intensive monitoring of adverse drug reactions in hospitalized patients of two medical units at a tertiary care teaching hospital. J Pharmacol Pharmacother 2012;3:308-13.
23. Rajpara AJ, Kanani NJ. An intensive monitoring of adverse drug reactions in indoor patients of medicine department at tertiary care teaching hospital: A single center, prospective, multisource observational study. Natl J Physiol Pharm Pharmacol 2019;9:1-8.
24. Hilmer SN, McLachlan AJ, Le Couteur DG. Clinical pharmacology in the geriatric patient. Fundam Clin Pharmacol 2007;21:217-30.
25. Rajakannan T, Mallayasamy S, Guddattu V, Kamath A, Vilakkthala R, Rao PG, et al. Cost of adverse drug reactions in a South Indian tertiary care teaching hospital. J Clin Pharmacol 2012;52:559-65.
26. 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.
27. 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.
This work is licensed under a Creative Commons Attribution 4.0 International License.
The publication is licensed under CC By and is open access. Copyright is with author and allowed to retain publishing rights without restrictions.