BETWEEN-CENTRE VARIATION IN THE PROPORTIONS OF ADVERSE DRUG REACTIONS GRADED BY CAUSALITY, SEVERITY AND PREVENTABILITY IN INDIAN TERTIARY CARE CENTRES
Main Article Content
Keywords
Preventability, WHO-UMC causality assessment, Adverse drug reactions, Indian Adverse Drug Reaction Monitoring Centres.
Abstract
Background. Most Indian ADR monitoring centres (AMCs) publish audits that grade reports with the WHO-UMC causality system, the Hartwig-Siegel severity scale and the modified Schumock-Thornton preventability criteria. Their headline proportions differ widely and have not been synthesised.
Methods. This is a pilot analysis of a convenience sample, run before a logged systematic search; all criteria were set after the included papers had been read. Observational studies from Indian tertiary care hospitals that graded ADRs from all drug classes with WHO-UMC causality were eligible. Raw counts were extracted by one reviewer. Proportions were pooled on the logit scale with DerSimonian-Laird τ² and Hartung-Knapp-Sidik-Jonkman (HKSJ) confidence intervals; REML, Paule-Mandel and a binomial-normal GLMM were sensitivity analyses. Preventability was summarised descriptively.
Results. Eleven of 21 unique reports were included, covering 2,001 reports. The share graded probable ranged from 22.5% to 91.4% between centres (I² 96%, τ² 0.77; prediction interval 23.3 to 95.1); the pooled value was 70.9% (54.1 to 83.4). Across eight studies grading severity, the severe share ranged from 1.8% to 18.4% (pooled 8.2% (4.2 to 15.4)). The six centres reporting preventability judged between 0% and 97% of reactions not preventable. The lowest probable share came from the only active surveillance study. There was no evidence that region, inpatient setting or year explained the causality variation, although with 11 studies these analyses had little power.
Conclusions. Published Indian AMC audits differ widely in how their reports are distributed across causality, severity and preventability grades, so no single pooled figure represents them. Because each centre graded different reports, this design cannot separate case mix from grading practice. A logged systematic search, a second reviewer and a multicentre regrading study are needed before firm conclusions.
References
2.Lazarou J, Pomeranz BH, Corey PN. Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies. JAMA. 1998;279(15):1200–5.
3.Pirmohamed M, James S, Meakin S, et al. Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients. BMJ. 2004;329(7456):15–9.
4.Kalaiselvan V, Thota P, Singh GN. Pharmacovigilance Programme of India: recent developments and future perspectives. Indian J Pharmacol. 2016;48(6):624–8.
5.Hazell L, Shakir SA. Under-reporting of adverse drug reactions: a systematic review. Drug Saf. 2006;29(5):385–96.
6.World Health Organization, Uppsala Monitoring Centre. The use of the WHO-UMC system for standardised case causality assessment. Geneva: WHO; 2013. Available from: https://www.who.int/publications/m/item/WHO-causality-assessment
7.Hartwig SC, Siegel J, Schneider PJ. Preventability and severity assessment in reporting adverse drug reactions. Am J Hosp Pharm. 1992;49(9):2229–32.
8.Schumock GT, Thornton JP. Focusing on the preventability of adverse drug reactions. Hosp Pharm. 1992;27(6):538.
9.Lau PM, Stewart K, Dooley MJ. Comment: hospital admissions resulting from preventable adverse drug reactions. Ann Pharmacother. 2003;37(2):303–4.
10.Hakkarainen KM, Hedna K, Petzold M, Hägg S. Percentage of patients with preventable adverse drug reactions and preventability of adverse drug reactions: a meta-analysis. PLoS One. 2012;7(3):e33236.
11.Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.
12.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.
13.Jindal A, Kumar R, Kumar S, Kaur A, Kiranjit, Raj RT. Pattern of adverse drug reactions reported at the adverse drug reaction monitoring centre at tertiary care teaching hospital in North India. Int J Basic Clin Pharmacol. 2023;12(3):375–8.
14.Baby M, Anand RG, Mathew AE, Shajahan J. An analysis of the pattern and the risk factors of adverse drug reactions at a tertiary care hospital. Asian J Pharm Clin Res. 2022;15(9):41–6.
15.Choudhury SK, Choudhury S, Kumar V. A prospective study on pattern of adverse drug reactions reported at pharmacovigilance centre of RIMS, Ranchi. Int J Toxicol Pharmacol Res. 2023;13(7):244–52.
16.Gupta PK, Kaur J, Devi G, Chaudhary S, Maria J. The pattern of adverse drug reaction reporting at a regional pharmacovigilance center in North India: a retrospective observational study. Cureus. 2025;17(9):e91812.
17.Singh P, Agrawal M, Hishikar R, Joshi U, Maheshwari B, Halwai A. Adverse drug reactions at adverse drug reaction monitoring center in Raipur: analysis of spontaneous reports during 1 year. Indian J Pharmacol. 2017;49(6):432–7.
18.Imran M, Bhardwaj A, Khare N, Singh A. Adverse drug reactions pattern in outpatients and inpatients of a tertiary care hospital from northern India. Asian J Pharm Clin Res. 2023;16(1):123–6.
19.Munn Z, Moola S, Lisy K, Riitano D, Tufanaru C. Methodological guidance for systematic reviews of observational epidemiological studies reporting prevalence and cumulative incidence data. Int J Evid Based Healthc. 2015;13(3):147–53.
20.Iorio A, Spencer FA, Falavigna M, et al. Use of GRADE for assessment of evidence about prognosis: rating confidence in estimates of event rates in broad categories of patients. BMJ. 2015;350:h870.
21.DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177–88.
22.Knapp G, Hartung J. Improved tests for a random effects meta-regression with a single covariate. Stat Med. 2003;22(17):2693–710.
23.Sidik K, Jonkman JN. A simple confidence interval for meta-analysis. Stat Med. 2002;21(21):3153–9.
24.IntHout J, Ioannidis JPA, Borm GF. The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method. BMC Med Res Methodol. 2014;14:25.
25.Paule RC, Mandel J. Consensus values and weighting factors. J Res Natl Bur Stand. 1982;87(5):377–85.
26.Stijnen T, Hamza TH, Özdemir P. Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data. Stat Med. 2010;29(29):3046–67.
27.Schwarzer G, Chemaitelly H, Abu-Raddad LJ, Rücker G. Seriously misleading results using inverse of Freeman-Tukey double arcsine transformation in meta-analysis of single proportions. Res Synth Methods. 2019;10(3):476–83.
28.Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–58.
29.Riley RD, Higgins JPT, Deeks JJ. Interpretation of random effects meta-analyses. BMJ. 2011;342:d549.
30.Wilson EB. Probable inference, the law of succession, and statistical inference. J Am Stat Assoc. 1927;22(158):209–12.
31.Lhamo Y, Purohit K, Singh S, et al. Pattern, severity, and preventability of adverse drug reactions from a Northern Indian tertiary care facility: a retrospective analysis. Int J Risk Saf Med. 2025;36(1):5–13.
32.Dutta SB, Beg MA, Bawa S, et al. A retrospective analysis of adverse drug reactions in a tertiary care teaching hospital at Dehradun, Uttarakhand. Int J Basic Clin Pharmacol. 2015;4(1):121–4.
33.Ram S, Nishanthi A, Manickam S, Venkatraman S. Retrospective analysis of adverse drug reactions from a teaching hospital in South India: patterns, severity, causality, and preventability. Cureus. 2026;18(7):e112854.
34.Yadav P, Rao GK, Rataboli PV, Gurav SS. Adverse drug reaction monitoring and reporting in a tertiary care teaching hospital in Goa. Med J DY Patil Vidyapeeth. 2025;18(3):463–72.
35.Chandrabhan, Jain P, Jain S. Adverse drug reaction monitoring study in hospitalized patients: support for pharmacovigilance at a tertiary care hospital. Int J Basic Clin Pharmacol. 2021;10(3):261–5.
36.Kumar R, Jindal A, Garg P, et al. Pharmacovigilance study of anticancer drugs in a tertiary care teaching hospital in North India: a retrospective study. Cureus. 2023;15(9):e44984.
Article Sidebar
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
All articles published in JPTCP are licensed under Copyright Creative Commons Attribution-NonCommercial 4.0 International License.
