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Original Research Article

DTT 2022; 1(1): 51-58

Published online July 31, 2022 https://doi.org/10.58502/DTT.22.004

Copyright © The Pharmaceutical Society of Korea.

The Different Safety Signals on Influenza Vaccine in Adults and the Elderly: A Nationwide Post-Marketing Surveillance Study from 2005 to 2019

Bin Hong1*, Hyesung Lee1,2*, Haeun Rhee1, Ju Hwan Kim1,2, Ha-Lim Jeon3, SangHee Kim1, Nam-Kyong Choi4,5, Sun-Young Jung6,7, Ju-Young Shin1,2,8

1School of Pharmacy, Sungkyunkwan University, Suwon, Korea
2Department of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, Korea
3School of Pharmacy, Jeonbuk National University, Jeonju, Korea
4Department of Health Convergence, Ewha Womans University, Seoul, Korea
5Graduate School of Industrial Pharmaceutical Science, Ewha Womans University, Seoul, Korea
6College of Pharmacy, Chung-Ang University, Seoul, Korea
7Department of Global Innovative Drugs, Graduate School of Chung-Ang University, Seoul, Korea
8Department of Clinical Research Design & Evaluation, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea

Correspondence to:Ju-Young Shin, shin.jy@skku.edu
*These authors contributed equally to this work.

Received: May 6, 2022; Revised: June 8, 2022; Accepted: June 15, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ((http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

The safety profiles of influenza vaccine among different age groups are still limited. We aimed to identify the difference of adverse event (AE) distribution between adults and the elderly. We conducted a post-marketing surveillance study of influenza vaccines between 2005 and 2019 using the Korea Adverse Event Reporting System Database. Safety signals were detected based on two age groups (19-64 and ≥ 65 years). We used three data mining methods: a) proportional reporting ratio, b) reporting odds ratio, and c) information component. Among 18,117 AEs following influenza vaccine administration, 15,986 and 2,131 AEs were reported in adults and elderly, respectively. Serious AEs following administration of the influenza vaccine in the elderly were significantly higher than in adults, accounting for 11.98% and 2.85%, respectively. The proportion of central & peripheral nervous system disorders and gastro-intestinal system disorders in the elderly was much higher than that in adults. Neuritis, pharyngitis, asthenia, and arthralgia were only detected in the elderly group. We found different safety profiles and a differing distribution of AEs following influenza vaccination. AEs were more serious in the elderly than in adults. Our detected signals require careful monitoring in the elderly. Further studies are required to investigate this causal relationship.

Keywordsinfluenza vaccine, vaccine safety, data mining, signal detection, KIDS KAERS database

Influenza is an infectious disease associated with high global morbidity and mortality (Simonsen et al. 2013). In Korea, influenza vaccines are distributed as part of the National Immunization Program, which has steadily expanded its eligible population since its inception in 1997 (Korea Disease Control and Prevention Agency 2017). Influenza vaccination considerably reduces the likelihood of influenza infection, with consequent reductions in incidences of death and serious disease, particularly among vulnerable and older populations (World Health Organization 2012). However, questions have been raised regarding the safety of the influenza vaccine, especially among different age groups. Some previous randomized phase 3 trials have shown that adverse event (AE) rates following influenza vaccine administration in patients ≥ 65 years old were higher than those in patients 18-64 years old (Ward et al. 2020). To the best of our knowledge, there are few studies that focused on the post-marketing monitoring of influenza vaccine safety among different age groups using a large-scale database.

Various data-mining algorithms for signal detection have been developed and are currently widely used for the post-marketing safety surveillance of drugs (Arnaud et al. 2017). As a common quantitative method for signal detection, disproportionality analysis (DA) has been broadly applied in adverse event reporting systems to search for signals by generating a score that evaluates the degree of disproportionality of a specific drug-AE pair compared with all other analyzed pairs from the database (Sakaeda et al. 2013). Proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC) analyses are examples of some widely used DA techniques (van Puijenbroek et al. 2002; Duggirala et al. 2016). However, owing to the different calculation methods and criteria used to define AEs as the signals of each algorithm, inconsistent signal detection results are often obtained (U.S. Food and Drug Administration 2018).

In this study, we aimed to identify potential safety signals of the influenza vaccine using the three aforementioned DA methods (PRR, ROR, and IC) and the difference in AE distribution according to two age groups: (1) adults aged between 19 and 64 years and (2) the elderly aged 65 years old or older.

Data sources

We used data from the Korea Institute of Drug Safety & Risk Management-Korea Adverse Event Reporting System Database (KIDS-KD) reported between 2005 and 2019. This database includes all spontaneous AE reports in South Korea and contains information on demographics, vaccination, AEs, causality assessment, and clinical information (Korea Institute of Drug Safety & Risk Management 2020). All drugs and AEs were coded according to the Anatomical Therapeutic Chemical Classification (ATC) system and the World Health Organization-Adverse Reaction Terminology (WHO-ART) dictionary (Sills 1989). WHO-ART branches into a stepped hierarchy, including system organ class (SOC), high-level terms (HLT), preferred terms (PT), and included terms (IT) from top to bottom; signals were determined at the PT level in this study.

Study vaccine

J07 was used as the ATC code for the vaccines. Among them, J07BB, J07BB01, J07BB02, and J07BB03 were used for the identification of the influenza vaccine, while the others were classified as all other vaccines and used as a comparator for signal detection.

Selection of AE reports

From all the AEs following vaccination collected in KIDS-KD between 1988 and 2019, we excluded the following: (1) those reported prior to 2005; (2) those reported as a concomitant vaccine, not a suspected vaccine; (3) those that were not final reports; (4) those that were invalid reports (missing or unspecified drugs or AE codes); (5) those with report errors (logical errors); (6) those aged less than 19 years; and (7) those reported by subtype simultaneously.

Statistical analyses

1) Descriptive analyses

We calculated the frequency and proportion of demographic characteristics, including sex, and report characteristics, such as report type and source. Chi-squared tests were performed to compare the frequency and proportion of the influenza vaccine with all other vaccines. These analyses were repeated in two age groups (adults aged between 19 and 64 years and the elderly aged 65 years old or older).

2) Algorithms for signal detection

Signal suggests a potential relationship between an AE and a vaccine or drug (Chakraborty 2015). To detect signals for the influenza vaccine by age group, three signal detection algorithms were used: PRR, ROR, and IC.

PRR, ROR, and IC are used by the Medicines and Healthcare Products Regulatory Agency (MHRA) in the United Kingdom, Netherlands Pharmacovigilance Centre, and World Health Organization (WHO), respectively (Sakaeda et al. 2013). The thresholds of signals for each algorithm were defined as follows: PRR ≥ 2, ROR ≥ 2, both chi-squared test ≥ 4 and number of reported AE ≥ 3, IC with a lower limit of 95% confidence interval ≥ 0. In this study, AEs were defined as signals detected using any of the three methods. All statistical analyses were performed using SAS software (version 9.4; SAS Institute, Inc., Cary, NC, USA). This study was approved by the Institutional Review Board of Chung-Ang University in South Korea (1041078-202008-ZZ-209-01).

General characteristics

From a total of 42,216 cases of AEs following vaccination reported in KIDS-KD between 1988 and 2019, 14,636 reports were included in this study. Among them, 12,635 (86.33%) reports were regarding adults, of which 7,995 (63.28%) were related to the influenza vaccine, and 2,001 (13.67%) were reported to be elderly, of which 1,010 (50.47%) were related to the influenza vaccine. The flowchart of this study is presented in Fig. 1.

Figure 1.Flowchart of selection for spontaneous reports of adverse events. AE, adverse event; KIDS-KD, Korea Institute of Drug Safety & Risk Management-Korea Adverse Event Reporting System Database.

The baseline characteristics of influenza vaccine-related AEs compared with those of other vaccines are provided in Table 1. More AEs were reported in women than in men in both groups, accounting for 77.64% and 61.07% of the samples, respectively. Additionally, most characteristics were similar between the two age groups, but there were slight differences in report sources by affiliation. In the elderly group, the majority of reports originated from the pharmaceutical company for influenza vaccine (70.10%), while in the adult group, most came from pharmaceutical companies as well as regional drug safety centers (52.51% and 44.47%, respectively). Furthermore, the percentage of serious AEs was higher in the elderly for both the influenza vaccine and all other vaccines (11.98% and 11.91%, respectively), while the percentage of serious AEs in adults was 2.85% and 9.31%, respectively.

Table 1 Demographic characteristics of vaccine-related adverse event reports in adults between 2005 and 2019

Characteristics19-64 years65 years or older
TotalInfluenza vaccineAll other vaccinesTotalInfluenza vaccineAll other vaccines
N = 12,635 (%)N = 7,995 (%)N = 4,640 (%)N = 2,001 (%)N = 1,010 (%)N = 991 (%)
Gender
Male2,727 (21.58)1,801 (22.53)926 (19.96)749 (37.43)383 (37.92)366 (36.93)
Female9,810 (77.64)6,169 (77.16)3,641 (78.47)1,222 (61.07)622 (61.58)600 (60.54)
Missing98 (0.78)25 (0.31)73 (1.57)30 (1.50)5 (0.50)25 (2.52)
Report type
Spontaneous report6,938 (54.91)3,992 (49.93)2,946 (63.49)1,165 (58.22)319 (31.58)846 (85.37)
Research5,525 (43.73)3,929 (49.14)1,596 (34.40)780 (38.98)661 (65.45)119 (12.01)
Literature58 (0.46)18 (0.23)40 (0.86)27 (1.35)8 (0.79)19 (1.92)
Other114 (0.90)56 (0.70)58 (1.25)29 (1.45)22 (2.18)7 (0.71)
Report source by professions
Medical worker*8,672 (68.64)5,320 (66.54)3,352 (72.24)950 (47.48)473 (46.84)477 (48.13)
Consumer1,389 (10.99)888 (11.11)501 (10.80)74 (3.70)13 (1.29)61 (6.16)
Others**1,548 (12.25)971 (12.15)577 (12.44)735 (36.73)299 (29.60)436 (43.99)
Missing1,026 (8.12)816 (10.21)210 (4.53)242 (12.09)225 (22.28)17 (1.72)
Report source by affiliation
Regional drug safety center4,259 (33.71)3,555 (44.47)704 (15.17)308 (15.39)103 (10.20)205 (20.69)
Pharmaceutical company7,496 (59.33)4,198 (52.51)3,298 (71.08)1,116 (55.77)708 (70.1)408 (41.17)
Medical institution194 (1.54)104 (1.30)90 (1.94)9 (0.45)2 (0.20)7 (0.71)
Pharmacy1 (0.01)0 (0.00)1 (0.02)0 (0.00)0 (0.00)1 (0.00)
Health center0 (0.00)0 (0.00)0 (0.00)1 (0.05)0 (0.00)1 (0.10)
Customer183 (1.45)7 (0.09)176 (3.79)33 (1.65)8 (0.79)25 (2.52)
Others502 (3.97)131 (1.64)371 (8.00)534 (26.69)189 (18.71)345 (34.81)
Serious adverse events
Yes660 (5.22)228 (2.85)432 (9.31)239 (11.94)121 (11.98)118 (11.91)
No11,975 (94.78)7,767 (97.15)4,208 (90.69)1,762 (88.06)889 (88.02)873 (88.09)

*Medical workers included doctors, pharmacists, and nurses.

**Others included lawyers and other healthcare professionals.


Distribution of adverse events (WHO-ART SOC level)

We found 18,117 AE pairs for the influenza vaccine, of which 40.08% were application site disorders in the overall population (Table 2). The proportion of body as a whole-general disorders (22.67%), musculo-skeletal system disorders (13.79%), and respiratory system disorders (5.41%) were higher following influenza vaccine administration compared with administration of all other vaccines. When divided into two age groups, we found 15,986 and 2,131 AE pairs for the influenza vaccine in adults and the elderly, respectively, with application site disorders being predominant in both groups (41.04% and 32.85% respectively). The proportion of AE pairs in whole body, psychiatric, and musculo-skeletal system disorders was higher in adults, while that of respiratory system, central & peripheral nervous system, skin and appendages, and gastro-intestinal disorders was higher in the elderly.

Table 2 The frequency of adverse events attributed to the influenza vaccine and all other vaccines in adults between 2005 and 2019

Adverse eventTotal19-64 years65 years or older
(WHO-ART SOC code)Influenza vaccineAll other vaccinesInfluenza vaccineAll other vaccinesInfluenza vaccineAll other vaccines
N = 18,117N = 13,252N = 15,986N = 11,254N = 2,131N = 1,998
AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)
Application site disorders7,261 (40.08)5,174 (39.05)6,561 (41.04)4,494 (39.94)700 (32.85)680 (34.03)
Body as a whole - general disorders4,106 (22.67)2,217 (16.73)3,680 (23.02)1,771 (15.74)426 (19.99)446 (22.32)
Musculo-skeletal system disorders2,499 (13.79)958 (7.23)2,229 (13.94)781 (6.94)270 (12.67)177 (8.86)
Central & peripheral nervous system disorders1,491 (8.23)1,266 (9.55)1,210 (7.57)1,130 (10.04)281 (13.19)136 (6.81)
Respiratory system disorders980 (5.41)391 (2.95)841 (5.26)307 (2.73)139 (6.52)84 (4.20)
Skin and appendages disorders684 (3.78)1,088 (8.21)566 (3.54)921 (8.18)118 (5.54)167 (8.36)
Gastro-intestinal system disorders508 (2.80)629 (4.75)419 (2.62)556 (4.94)89 (4.18)73 (3.65)
Psychiatric disorders216 (1.19)161 (1.22)202 (1.26)128 (1.14)14 (0.66)33 (1.65)
Metabolic and nutritional disorders49 (0.27)32 (0.24)44 (0.28)28 (0.25)5 (0.23)4 (0.20)
Vision disorders45 (0.25)55 (0.42)33 (0.21)49 (0.44)12 (0.56)6 (0.30)
Cardiovascular disorders, general34 (0.19)68 (0.51)23 (0.14)45 (0.40)11 (0.52)23 (1.15)
Resistance mechanism disorders29 (0.16)282 (2.13)25 (0.16)210 (1.87)4 (0.19)72 (3.60)
Urinary system disorders25 (0.14)86 (0.65)19 (0.12)60 (0.53)6 (0.28)26 (1.30)
Hearing and vestibular disorders24 (0.13)27 (0.20)14 (0.09)22 (0.20)10 (0.47)5 (0.25)
Secondary terms - events24 (0.13)366 (2.76)18 (0.11)336 (2.99)6 (0.28)30 (1.50)
Heart rate and rhythm disorders24 (0.13)19 (0.14)20 (0.13)18 (0.16)4 (0.19)1 (0.05)
Vascular (extracardiac) disorders22 (0.12)39 (0.29)8 (0.05)30 (0.27)14 (0.66)9 (0.45)
Platelet, bleeding & clotting disorders16 (0.09)28 (0.21)11 (0.07)17 (0.15)5 (0.23)11 (0.55)
Foetal disorders15 (0.08)51 (0.38)15 (0.09)51 (0.45)0 (0.00)0 (0.00)
Reproductive disorders, female14 (0.08)170 (1.28)14 (0.09)170 (1.51)0 (0.00)0 (0.00)
Liver and biliary system disorders11 (0.06)25 (0.19)6 (0.04)20 (0.18)5 (0.23)5 (0.25)
White cell and RES* disorders13 (0.07)37 (0.28)11 (0.07)35 (0.31)2 (0.09)2 (0.10)
Myo-, endo-, pericardial & valve disorders7 (0.04)2 (0.02)2 (0.01)1 (0.01)5 (0.23)1 (0.05)
Neoplasms5 (0.03)26 (0.20)1 (0.01)25 (0.22)4 (0.19)1 (0.05)
Collagen disorders4 (0.02)27 (0.20)4 (0.03)24 (0.21)0 (0.00)3 (0.15)
Poison specific terms4 (0.02)3 (0.02)4 (0.03)3 (0.03)0 (0.00)0 (0.00)
Neonatal and infancy disorders3 (0.02)3 (0.02)3 (0.02)3 (0.03)0 (0.00)0 (0.00)
Red blood cell disorders2 (0.01)1 (0.01)1 (0.01)0 (0.00)1 (0.05)1 (0.05)
Endocrine disorders1 (0.01)8 (0.06)1 (0.01)8 (0.07)0 (0.00)0 (0.00)
Special senses other, disorders0 (0.00)2 (0.02)0 (0.00)2 (0.02)0 (0.00)0 (0.00)
Reproductive disorders, male0 (0.00)10 (0.08)0 (0.00)8 (0.07)0 (0.00)2 (0.10)
Missing1 (0.01)1 (0.01)1 (0.01)1 (0.01)0 (0.00)0 (0.00)

WHO-ART, World Health Organization Adverse Reactions Terminology; SOC, system organ class; AE, adverse event; RES, reticuloendothelial system.


Signal detection

Compared with all other vaccines in adults aged > 18 years, we identified a total of 18 AEs as signals by at least one data mining method (Table 3). We noted a different distribution of AEs between the two age groups (Table 4). We identified 11 signals in the elderly and 14 in adults. Among them, arthralgia, neuritis, pharyngitis, asthenia, and death were only detected in the elderly; while myalgia, dysphonia, somnolence, pleural pain, rhinitis, malaise, rigors, and tenderness were only found in adults. In addition, we detected sweating increased, injection site inflammation, and headache in both age groups, but higher values of PRR, ROR, and IC were observed in the elderly population. Fatigue was also found in both groups, however, adults generated a higher index.

Table 3 Signal detection of influenza vaccine received at greater than 18 years of age compared to all other vaccines between 2005 and 2019

Adverse events (WHO-ART PT Level)No. of AE-PairsPRRRORICSignal detection
PRRRORIC
Total
Sweating increased1383.263.270.18YYY
Injection site inflammation9203.033.140.36YYY
Injection site pain4,0101.251.320.07Y
Myalgia2,2082.352.540.32YYY
Dysphonia1410.2410.25−0.32YY
Headache8161.731.760.15Y
Neuritis522.932.93−0.05YY
Somnolence1212.682.690.10YYY
Coughing1332.372.380.08YYY
Pleural pain2210.52Y
Rhinitis1882.702.710.17YYY
Sputum increased243.513.51−0.24YY
Asthenia2052.002.010.09YY
Fatigue1,18510.4411.100.58YYY
Malaise5343.833.920.38YYY
Rigors5702.482.530.26YYY
Injection site pressure sensation62090.7093.880.62YYY
Tenderness nos19370.5971.340.49YYY

WHO-ART, World Health Organization-Adverse Reactions Terminology; PT, preferred term; AE, adverse event; PRR, proportional reporting ratio; ROR, reporting odds ratio; IC, information component; Y, AE was detected as a signal.


Table 4 Signal detection of influenza vaccine compared with all other vaccines based on two age groups between 2005 and 2019

Adverse events(WHO-ART PT Level)No. of AE-PairsPRRRORICSignal detection
PRRRORIC
19-64 years old
Sweating increased1032.342.350.02YYY
Injection site inflammation7042.232.290.23YYY
Injection site pain3,7031.111.140.01Y
Myalgia2,0182.072.230.27YYY
Dysphonia128.458.45−0.43YY
Headache7011.431.450.05Y
Somnolence1212.582.590.08YYY
Pleural pain2050.49Y
Rhinitis1702.352.360.11YYY
Fatigue1,1019.349.960.55YYY
Malaise5123.533.620.34YYY
Rigors5012.102.130.19YYY
Injection site pressure sensation60284.7688.040.60YYY
Tenderness nos19167.2368.030.47YYY
65+ years old
Sweating increased355.475.540.09YYY
Injection site inflammation2167.798.550.53YYY
Injection site pain3071.511.590.06Y
Arthralgia544.224.300.16YYY
Headache1153.373.500.25YYY
Neuritis180.04Y
Pharyngitis292.472.49−0.17YY
Asthenia502.762.800.02YYY
Death144.384.40−0.30YY
Fatigue847.888.160.37YYY
Injection site pressure sensation180.04Y

WHO-ART, World Health Organization-Adverse Reactions Terminology; PT, preferred term; AE, adverse event; PRR, proportional reporting ratio; ROR, reporting odds ratio; IC, information component; Y, AE was detected as a signal.

We used DA techniques to detect safety signals for influenza vaccines and the difference of AE distribution between adults and the elderly using a nationwide spontaneous reporting database and found differing safety profiles. Among the 18,117 reported AEs following influenza vaccine administration, adults and the elderly reported 15,986 and 2,131 AEs, respectively. Overall, AEs following influenza vaccination were more serious in the elderly than in adults. The prevalence of central & peripheral nervous system disorders and gastro-intestinal system disorders has been found to be much higher in the elderly than in adults. Neuritis, pharyngitis, asthenia, and arthralgia were only detected in the elderly.

We noted that application site disorders were predominant for both age groups, but the proportions of central & peripheral nervous system, respiratory system, and gastrointestinal system disorders in the elderly were much higher than that in adults. Luo et al. (2016) reported similar findings that more frequent and diverse nervous, respiratory, and gastrointestinal AEs affect the elderly population compared with the adult population, whose comorbidity, polypharmacy, and pharmacokinetics were different from that of younger adults (Davies and O'Mahony 2015). Conversely, we found that a slightly higher percentage of adult experienced musculoskeletal system disorders than did the elderly, which is inconsistent with previous studies on the subject (Luo et al. 2016).

We generated 11 signals in the elderly. Among them, neuritis, pharyngitis, asthenia, and arthralgia were only detected in the elderly group. Notably, neuritis (a preferred term for Guillain-Barre Syndrome (GBS)) was detected as a signal by both PRR and ROR analysis. Influenza vaccination has been frequently associated with GBS, although evidence for this association is controversial. GBS was first reported following administration of the influenza vaccine in the US during the influenza season of 1976-1977, with an increase in GBS observed in vaccine recipients (approximately one case per 100,000 vaccinations) (Schonberger et al. 1979). Many studies have investigated the association between influenza vaccines and GBS, and a recent meta-analysis found a slight increase in the incidence of GBS (Martín Arias et al. 2015; Sanz Fadrique et al. 2019). Whether there is a causal relationship between GBS and the influenza vaccine requires further evaluation; however, even if the influenza vaccine slightly increases the risk of GBS, avoiding vaccination and risking influenza infection may be a more dangerous decision (Poland et al. 2013). The risk of GBS after an influenza-like illness is considerably higher than that after influenza vaccination, particularly in the elderly (Stowe et al. 2009; Iqbal et al. 2015). In addition, previous studies have shown that vaccinated groups have more favorable GBS outcomes in the long run (Vellozzi et al. 2014).

Furthermore, we found that death was detected as a signal only in the elderly group; however, in previous studies using spontaneous reporting data, no concerning patterns that would suggest a causal relationship between influenza vaccination and deaths were found (Vellozzi et al. 2009; Haber et al. 2014; Vellozzi et al. 2014). In fact, 59 deaths following influenza vaccination were reported in Korea in 2020, mostly between the age of 70 and 90. Subsequently, the Korea Disease Control and Prevention Agency (KDCA) investigated 46 of these cases and did not find evidence of a causal association with influenza vaccination. All deceased individuals had serious health conditions that could account for their cause of death (Centers for Disease Control and Prevention 2020). Therefore, signal validation through an in-depth evaluation of these 14 deaths is required. We also identified arthralgia as a signal in the elderly group using all three data mining methods. Interestingly, Asakawa et al. (2005) previously reported one case of reactive arthritis following influenza vaccination in Japan. However, to the best of our knowledge, limited studies have confirmed the causal relationship between the influenza vaccine and arthralgia currently; thus our results need further epidemiological studies.

In this study, PRR, ROR, and IC methods were used to detect safety signals because inconsistent results were often encountered among previous study methods due to differences in the definition of AEs and signal score thresholds. These DA techniques have the advantage of being rapid and inexpensive and can provide information about the potential association between drugs and AEs. The PRR method involves evaluating the degree of disproportionate reporting of an AE for a product of interest compared with the reporting of this same AE for all other products in the database. Similarly, the ROR method evaluates the odds of an AE of interest being observed with a product of interest compared to the odds of the same AE being observed with all other products in the database. However, neither PRR nor ROR adjust for a small number of observed or expected AEs, and when the number of AEs is small, the results of these algorithms tend to become unstable and yield potentially high estimates with wide confidence intervals and false-positive results. In such situations, the Bayesian analysis methods of the IC algorithm may be more appropriate. The IC algorithm may also be useful when screening signals for further studies, as it generally reduces the number of false-positive values. Therefore, it is necessary to use complementary methods.

However, this study had some limitations. Firstly, passive surveillance systems such as the KIDS-KD database have the inherent limitations of missing information, inconsistent quality of individual case safety reports, duplicated reporting, and under-reporting due to lack of awareness (Rosenthal and Chen 1995). In addition, the signals generated in this study using quantitative signal detection methods only indicate a potential relationship between the influenza vaccine and specified AEs, albeit we aimed to reflect a causal relationship between them. Therefore, our results should be interpreted with caution and should be considered only exploratory. Further pharmacoepidemiological studies are needed to confirm our findings (Varricchio et al. 2004).

In this safety surveillance study of the influenza vaccine in those older than 18 years of age using disproportionality-based data mining methods (PRR, ROR, and IC) in the KIDS-KD, we found that the safety profiles of AEs following influenza vaccination were more serious in the elderly than in adults. Four signals were detected only in the elderly group: neuritis, pharyngitis, asthenia, and arthralgia. These AEs therefore need more careful monitoring in the elderly. Further evaluations and validations are needed to investigate this causal relationship.

J-YS received grants from the Ministry of Food and Drug Safety, the Ministry of Health and Welfare, the National Research Foundation of Korea, and pharmaceutical companies, including Daiichi Sankyo, GSK, and Pfizer, outside of the submitted work. S-YJ received grants from the Ministry of Food and Drug Safety, and the Ministry of Health and Welfare. No other potential conflict of interest relevant to this article was reported.

The authors thank the Korea Institute of Drug Safety and Risk Management (KIDS) for their cooperation in providing access to the Korea Adverse Event Reporting System Database. We would like to thank Editage (www.editage.co.kr) for editing and reviewing this manuscript for English language. This work was supported by a grant (21153MFDS607) from the Ministry of Food and Drug Safety of South Korea in 2021-2025 (to J-YS) and a grant (20200509312-00) from the Ministry of Food and Drug Safety of South Korea in 2020 (to S-YJ). Moreover, this work was supported by the Bio Industry Technology Development Program (No. 20015086) By the Ministry of Trade, Industry & Energy (MOTIE, Korea). The funders had no role in the study design, data collection and analysis, interpretation of data, writing of the report, and the decision to submit the article for publication.

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Article

Original Research Article

DTT 2022; 1(1): 51-58

Published online July 31, 2022 https://doi.org/10.58502/DTT.22.004

Copyright © The Pharmaceutical Society of Korea.

The Different Safety Signals on Influenza Vaccine in Adults and the Elderly: A Nationwide Post-Marketing Surveillance Study from 2005 to 2019

Bin Hong1*, Hyesung Lee1,2*, Haeun Rhee1, Ju Hwan Kim1,2, Ha-Lim Jeon3, SangHee Kim1, Nam-Kyong Choi4,5, Sun-Young Jung6,7, Ju-Young Shin1,2,8

1School of Pharmacy, Sungkyunkwan University, Suwon, Korea
2Department of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, Korea
3School of Pharmacy, Jeonbuk National University, Jeonju, Korea
4Department of Health Convergence, Ewha Womans University, Seoul, Korea
5Graduate School of Industrial Pharmaceutical Science, Ewha Womans University, Seoul, Korea
6College of Pharmacy, Chung-Ang University, Seoul, Korea
7Department of Global Innovative Drugs, Graduate School of Chung-Ang University, Seoul, Korea
8Department of Clinical Research Design & Evaluation, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea

Correspondence to:Ju-Young Shin, shin.jy@skku.edu
*These authors contributed equally to this work.

Received: May 6, 2022; Revised: June 8, 2022; Accepted: June 15, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ((http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The safety profiles of influenza vaccine among different age groups are still limited. We aimed to identify the difference of adverse event (AE) distribution between adults and the elderly. We conducted a post-marketing surveillance study of influenza vaccines between 2005 and 2019 using the Korea Adverse Event Reporting System Database. Safety signals were detected based on two age groups (19-64 and ≥ 65 years). We used three data mining methods: a) proportional reporting ratio, b) reporting odds ratio, and c) information component. Among 18,117 AEs following influenza vaccine administration, 15,986 and 2,131 AEs were reported in adults and elderly, respectively. Serious AEs following administration of the influenza vaccine in the elderly were significantly higher than in adults, accounting for 11.98% and 2.85%, respectively. The proportion of central & peripheral nervous system disorders and gastro-intestinal system disorders in the elderly was much higher than that in adults. Neuritis, pharyngitis, asthenia, and arthralgia were only detected in the elderly group. We found different safety profiles and a differing distribution of AEs following influenza vaccination. AEs were more serious in the elderly than in adults. Our detected signals require careful monitoring in the elderly. Further studies are required to investigate this causal relationship.

Keywords: influenza vaccine, vaccine safety, data mining, signal detection, KIDS KAERS database

Introduction

Influenza is an infectious disease associated with high global morbidity and mortality (Simonsen et al. 2013). In Korea, influenza vaccines are distributed as part of the National Immunization Program, which has steadily expanded its eligible population since its inception in 1997 (Korea Disease Control and Prevention Agency 2017). Influenza vaccination considerably reduces the likelihood of influenza infection, with consequent reductions in incidences of death and serious disease, particularly among vulnerable and older populations (World Health Organization 2012). However, questions have been raised regarding the safety of the influenza vaccine, especially among different age groups. Some previous randomized phase 3 trials have shown that adverse event (AE) rates following influenza vaccine administration in patients ≥ 65 years old were higher than those in patients 18-64 years old (Ward et al. 2020). To the best of our knowledge, there are few studies that focused on the post-marketing monitoring of influenza vaccine safety among different age groups using a large-scale database.

Various data-mining algorithms for signal detection have been developed and are currently widely used for the post-marketing safety surveillance of drugs (Arnaud et al. 2017). As a common quantitative method for signal detection, disproportionality analysis (DA) has been broadly applied in adverse event reporting systems to search for signals by generating a score that evaluates the degree of disproportionality of a specific drug-AE pair compared with all other analyzed pairs from the database (Sakaeda et al. 2013). Proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC) analyses are examples of some widely used DA techniques (van Puijenbroek et al. 2002; Duggirala et al. 2016). However, owing to the different calculation methods and criteria used to define AEs as the signals of each algorithm, inconsistent signal detection results are often obtained (U.S. Food and Drug Administration 2018).

In this study, we aimed to identify potential safety signals of the influenza vaccine using the three aforementioned DA methods (PRR, ROR, and IC) and the difference in AE distribution according to two age groups: (1) adults aged between 19 and 64 years and (2) the elderly aged 65 years old or older.

Materials and Methods

Data sources

We used data from the Korea Institute of Drug Safety & Risk Management-Korea Adverse Event Reporting System Database (KIDS-KD) reported between 2005 and 2019. This database includes all spontaneous AE reports in South Korea and contains information on demographics, vaccination, AEs, causality assessment, and clinical information (Korea Institute of Drug Safety & Risk Management 2020). All drugs and AEs were coded according to the Anatomical Therapeutic Chemical Classification (ATC) system and the World Health Organization-Adverse Reaction Terminology (WHO-ART) dictionary (Sills 1989). WHO-ART branches into a stepped hierarchy, including system organ class (SOC), high-level terms (HLT), preferred terms (PT), and included terms (IT) from top to bottom; signals were determined at the PT level in this study.

Study vaccine

J07 was used as the ATC code for the vaccines. Among them, J07BB, J07BB01, J07BB02, and J07BB03 were used for the identification of the influenza vaccine, while the others were classified as all other vaccines and used as a comparator for signal detection.

Selection of AE reports

From all the AEs following vaccination collected in KIDS-KD between 1988 and 2019, we excluded the following: (1) those reported prior to 2005; (2) those reported as a concomitant vaccine, not a suspected vaccine; (3) those that were not final reports; (4) those that were invalid reports (missing or unspecified drugs or AE codes); (5) those with report errors (logical errors); (6) those aged less than 19 years; and (7) those reported by subtype simultaneously.

Statistical analyses

1) Descriptive analyses

We calculated the frequency and proportion of demographic characteristics, including sex, and report characteristics, such as report type and source. Chi-squared tests were performed to compare the frequency and proportion of the influenza vaccine with all other vaccines. These analyses were repeated in two age groups (adults aged between 19 and 64 years and the elderly aged 65 years old or older).

2) Algorithms for signal detection

Signal suggests a potential relationship between an AE and a vaccine or drug (Chakraborty 2015). To detect signals for the influenza vaccine by age group, three signal detection algorithms were used: PRR, ROR, and IC.

PRR, ROR, and IC are used by the Medicines and Healthcare Products Regulatory Agency (MHRA) in the United Kingdom, Netherlands Pharmacovigilance Centre, and World Health Organization (WHO), respectively (Sakaeda et al. 2013). The thresholds of signals for each algorithm were defined as follows: PRR ≥ 2, ROR ≥ 2, both chi-squared test ≥ 4 and number of reported AE ≥ 3, IC with a lower limit of 95% confidence interval ≥ 0. In this study, AEs were defined as signals detected using any of the three methods. All statistical analyses were performed using SAS software (version 9.4; SAS Institute, Inc., Cary, NC, USA). This study was approved by the Institutional Review Board of Chung-Ang University in South Korea (1041078-202008-ZZ-209-01).

Results

General characteristics

From a total of 42,216 cases of AEs following vaccination reported in KIDS-KD between 1988 and 2019, 14,636 reports were included in this study. Among them, 12,635 (86.33%) reports were regarding adults, of which 7,995 (63.28%) were related to the influenza vaccine, and 2,001 (13.67%) were reported to be elderly, of which 1,010 (50.47%) were related to the influenza vaccine. The flowchart of this study is presented in Fig. 1.

Figure 1. Flowchart of selection for spontaneous reports of adverse events. AE, adverse event; KIDS-KD, Korea Institute of Drug Safety & Risk Management-Korea Adverse Event Reporting System Database.

The baseline characteristics of influenza vaccine-related AEs compared with those of other vaccines are provided in Table 1. More AEs were reported in women than in men in both groups, accounting for 77.64% and 61.07% of the samples, respectively. Additionally, most characteristics were similar between the two age groups, but there were slight differences in report sources by affiliation. In the elderly group, the majority of reports originated from the pharmaceutical company for influenza vaccine (70.10%), while in the adult group, most came from pharmaceutical companies as well as regional drug safety centers (52.51% and 44.47%, respectively). Furthermore, the percentage of serious AEs was higher in the elderly for both the influenza vaccine and all other vaccines (11.98% and 11.91%, respectively), while the percentage of serious AEs in adults was 2.85% and 9.31%, respectively.

Table 1 . Demographic characteristics of vaccine-related adverse event reports in adults between 2005 and 2019.

Characteristics19-64 years65 years or older
TotalInfluenza vaccineAll other vaccinesTotalInfluenza vaccineAll other vaccines
N = 12,635 (%)N = 7,995 (%)N = 4,640 (%)N = 2,001 (%)N = 1,010 (%)N = 991 (%)
Gender
Male2,727 (21.58)1,801 (22.53)926 (19.96)749 (37.43)383 (37.92)366 (36.93)
Female9,810 (77.64)6,169 (77.16)3,641 (78.47)1,222 (61.07)622 (61.58)600 (60.54)
Missing98 (0.78)25 (0.31)73 (1.57)30 (1.50)5 (0.50)25 (2.52)
Report type
Spontaneous report6,938 (54.91)3,992 (49.93)2,946 (63.49)1,165 (58.22)319 (31.58)846 (85.37)
Research5,525 (43.73)3,929 (49.14)1,596 (34.40)780 (38.98)661 (65.45)119 (12.01)
Literature58 (0.46)18 (0.23)40 (0.86)27 (1.35)8 (0.79)19 (1.92)
Other114 (0.90)56 (0.70)58 (1.25)29 (1.45)22 (2.18)7 (0.71)
Report source by professions
Medical worker*8,672 (68.64)5,320 (66.54)3,352 (72.24)950 (47.48)473 (46.84)477 (48.13)
Consumer1,389 (10.99)888 (11.11)501 (10.80)74 (3.70)13 (1.29)61 (6.16)
Others**1,548 (12.25)971 (12.15)577 (12.44)735 (36.73)299 (29.60)436 (43.99)
Missing1,026 (8.12)816 (10.21)210 (4.53)242 (12.09)225 (22.28)17 (1.72)
Report source by affiliation
Regional drug safety center4,259 (33.71)3,555 (44.47)704 (15.17)308 (15.39)103 (10.20)205 (20.69)
Pharmaceutical company7,496 (59.33)4,198 (52.51)3,298 (71.08)1,116 (55.77)708 (70.1)408 (41.17)
Medical institution194 (1.54)104 (1.30)90 (1.94)9 (0.45)2 (0.20)7 (0.71)
Pharmacy1 (0.01)0 (0.00)1 (0.02)0 (0.00)0 (0.00)1 (0.00)
Health center0 (0.00)0 (0.00)0 (0.00)1 (0.05)0 (0.00)1 (0.10)
Customer183 (1.45)7 (0.09)176 (3.79)33 (1.65)8 (0.79)25 (2.52)
Others502 (3.97)131 (1.64)371 (8.00)534 (26.69)189 (18.71)345 (34.81)
Serious adverse events
Yes660 (5.22)228 (2.85)432 (9.31)239 (11.94)121 (11.98)118 (11.91)
No11,975 (94.78)7,767 (97.15)4,208 (90.69)1,762 (88.06)889 (88.02)873 (88.09)

*Medical workers included doctors, pharmacists, and nurses..

**Others included lawyers and other healthcare professionals..



Distribution of adverse events (WHO-ART SOC level)

We found 18,117 AE pairs for the influenza vaccine, of which 40.08% were application site disorders in the overall population (Table 2). The proportion of body as a whole-general disorders (22.67%), musculo-skeletal system disorders (13.79%), and respiratory system disorders (5.41%) were higher following influenza vaccine administration compared with administration of all other vaccines. When divided into two age groups, we found 15,986 and 2,131 AE pairs for the influenza vaccine in adults and the elderly, respectively, with application site disorders being predominant in both groups (41.04% and 32.85% respectively). The proportion of AE pairs in whole body, psychiatric, and musculo-skeletal system disorders was higher in adults, while that of respiratory system, central & peripheral nervous system, skin and appendages, and gastro-intestinal disorders was higher in the elderly.

Table 2 . The frequency of adverse events attributed to the influenza vaccine and all other vaccines in adults between 2005 and 2019.

Adverse eventTotal19-64 years65 years or older
(WHO-ART SOC code)Influenza vaccineAll other vaccinesInfluenza vaccineAll other vaccinesInfluenza vaccineAll other vaccines
N = 18,117N = 13,252N = 15,986N = 11,254N = 2,131N = 1,998
AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)
Application site disorders7,261 (40.08)5,174 (39.05)6,561 (41.04)4,494 (39.94)700 (32.85)680 (34.03)
Body as a whole - general disorders4,106 (22.67)2,217 (16.73)3,680 (23.02)1,771 (15.74)426 (19.99)446 (22.32)
Musculo-skeletal system disorders2,499 (13.79)958 (7.23)2,229 (13.94)781 (6.94)270 (12.67)177 (8.86)
Central & peripheral nervous system disorders1,491 (8.23)1,266 (9.55)1,210 (7.57)1,130 (10.04)281 (13.19)136 (6.81)
Respiratory system disorders980 (5.41)391 (2.95)841 (5.26)307 (2.73)139 (6.52)84 (4.20)
Skin and appendages disorders684 (3.78)1,088 (8.21)566 (3.54)921 (8.18)118 (5.54)167 (8.36)
Gastro-intestinal system disorders508 (2.80)629 (4.75)419 (2.62)556 (4.94)89 (4.18)73 (3.65)
Psychiatric disorders216 (1.19)161 (1.22)202 (1.26)128 (1.14)14 (0.66)33 (1.65)
Metabolic and nutritional disorders49 (0.27)32 (0.24)44 (0.28)28 (0.25)5 (0.23)4 (0.20)
Vision disorders45 (0.25)55 (0.42)33 (0.21)49 (0.44)12 (0.56)6 (0.30)
Cardiovascular disorders, general34 (0.19)68 (0.51)23 (0.14)45 (0.40)11 (0.52)23 (1.15)
Resistance mechanism disorders29 (0.16)282 (2.13)25 (0.16)210 (1.87)4 (0.19)72 (3.60)
Urinary system disorders25 (0.14)86 (0.65)19 (0.12)60 (0.53)6 (0.28)26 (1.30)
Hearing and vestibular disorders24 (0.13)27 (0.20)14 (0.09)22 (0.20)10 (0.47)5 (0.25)
Secondary terms - events24 (0.13)366 (2.76)18 (0.11)336 (2.99)6 (0.28)30 (1.50)
Heart rate and rhythm disorders24 (0.13)19 (0.14)20 (0.13)18 (0.16)4 (0.19)1 (0.05)
Vascular (extracardiac) disorders22 (0.12)39 (0.29)8 (0.05)30 (0.27)14 (0.66)9 (0.45)
Platelet, bleeding & clotting disorders16 (0.09)28 (0.21)11 (0.07)17 (0.15)5 (0.23)11 (0.55)
Foetal disorders15 (0.08)51 (0.38)15 (0.09)51 (0.45)0 (0.00)0 (0.00)
Reproductive disorders, female14 (0.08)170 (1.28)14 (0.09)170 (1.51)0 (0.00)0 (0.00)
Liver and biliary system disorders11 (0.06)25 (0.19)6 (0.04)20 (0.18)5 (0.23)5 (0.25)
White cell and RES* disorders13 (0.07)37 (0.28)11 (0.07)35 (0.31)2 (0.09)2 (0.10)
Myo-, endo-, pericardial & valve disorders7 (0.04)2 (0.02)2 (0.01)1 (0.01)5 (0.23)1 (0.05)
Neoplasms5 (0.03)26 (0.20)1 (0.01)25 (0.22)4 (0.19)1 (0.05)
Collagen disorders4 (0.02)27 (0.20)4 (0.03)24 (0.21)0 (0.00)3 (0.15)
Poison specific terms4 (0.02)3 (0.02)4 (0.03)3 (0.03)0 (0.00)0 (0.00)
Neonatal and infancy disorders3 (0.02)3 (0.02)3 (0.02)3 (0.03)0 (0.00)0 (0.00)
Red blood cell disorders2 (0.01)1 (0.01)1 (0.01)0 (0.00)1 (0.05)1 (0.05)
Endocrine disorders1 (0.01)8 (0.06)1 (0.01)8 (0.07)0 (0.00)0 (0.00)
Special senses other, disorders0 (0.00)2 (0.02)0 (0.00)2 (0.02)0 (0.00)0 (0.00)
Reproductive disorders, male0 (0.00)10 (0.08)0 (0.00)8 (0.07)0 (0.00)2 (0.10)
Missing1 (0.01)1 (0.01)1 (0.01)1 (0.01)0 (0.00)0 (0.00)

WHO-ART, World Health Organization Adverse Reactions Terminology; SOC, system organ class; AE, adverse event; RES, reticuloendothelial system..



Signal detection

Compared with all other vaccines in adults aged > 18 years, we identified a total of 18 AEs as signals by at least one data mining method (Table 3). We noted a different distribution of AEs between the two age groups (Table 4). We identified 11 signals in the elderly and 14 in adults. Among them, arthralgia, neuritis, pharyngitis, asthenia, and death were only detected in the elderly; while myalgia, dysphonia, somnolence, pleural pain, rhinitis, malaise, rigors, and tenderness were only found in adults. In addition, we detected sweating increased, injection site inflammation, and headache in both age groups, but higher values of PRR, ROR, and IC were observed in the elderly population. Fatigue was also found in both groups, however, adults generated a higher index.

Table 3 . Signal detection of influenza vaccine received at greater than 18 years of age compared to all other vaccines between 2005 and 2019.

Adverse events (WHO-ART PT Level)No. of AE-PairsPRRRORICSignal detection
PRRRORIC
Total
Sweating increased1383.263.270.18YYY
Injection site inflammation9203.033.140.36YYY
Injection site pain4,0101.251.320.07Y
Myalgia2,2082.352.540.32YYY
Dysphonia1410.2410.25−0.32YY
Headache8161.731.760.15Y
Neuritis522.932.93−0.05YY
Somnolence1212.682.690.10YYY
Coughing1332.372.380.08YYY
Pleural pain2210.52Y
Rhinitis1882.702.710.17YYY
Sputum increased243.513.51−0.24YY
Asthenia2052.002.010.09YY
Fatigue1,18510.4411.100.58YYY
Malaise5343.833.920.38YYY
Rigors5702.482.530.26YYY
Injection site pressure sensation62090.7093.880.62YYY
Tenderness nos19370.5971.340.49YYY

WHO-ART, World Health Organization-Adverse Reactions Terminology; PT, preferred term; AE, adverse event; PRR, proportional reporting ratio; ROR, reporting odds ratio; IC, information component; Y, AE was detected as a signal..



Table 4 . Signal detection of influenza vaccine compared with all other vaccines based on two age groups between 2005 and 2019.

Adverse events(WHO-ART PT Level)No. of AE-PairsPRRRORICSignal detection
PRRRORIC
19-64 years old
Sweating increased1032.342.350.02YYY
Injection site inflammation7042.232.290.23YYY
Injection site pain3,7031.111.140.01Y
Myalgia2,0182.072.230.27YYY
Dysphonia128.458.45−0.43YY
Headache7011.431.450.05Y
Somnolence1212.582.590.08YYY
Pleural pain2050.49Y
Rhinitis1702.352.360.11YYY
Fatigue1,1019.349.960.55YYY
Malaise5123.533.620.34YYY
Rigors5012.102.130.19YYY
Injection site pressure sensation60284.7688.040.60YYY
Tenderness nos19167.2368.030.47YYY
65+ years old
Sweating increased355.475.540.09YYY
Injection site inflammation2167.798.550.53YYY
Injection site pain3071.511.590.06Y
Arthralgia544.224.300.16YYY
Headache1153.373.500.25YYY
Neuritis180.04Y
Pharyngitis292.472.49−0.17YY
Asthenia502.762.800.02YYY
Death144.384.40−0.30YY
Fatigue847.888.160.37YYY
Injection site pressure sensation180.04Y

WHO-ART, World Health Organization-Adverse Reactions Terminology; PT, preferred term; AE, adverse event; PRR, proportional reporting ratio; ROR, reporting odds ratio; IC, information component; Y, AE was detected as a signal..


Discussion

We used DA techniques to detect safety signals for influenza vaccines and the difference of AE distribution between adults and the elderly using a nationwide spontaneous reporting database and found differing safety profiles. Among the 18,117 reported AEs following influenza vaccine administration, adults and the elderly reported 15,986 and 2,131 AEs, respectively. Overall, AEs following influenza vaccination were more serious in the elderly than in adults. The prevalence of central & peripheral nervous system disorders and gastro-intestinal system disorders has been found to be much higher in the elderly than in adults. Neuritis, pharyngitis, asthenia, and arthralgia were only detected in the elderly.

We noted that application site disorders were predominant for both age groups, but the proportions of central & peripheral nervous system, respiratory system, and gastrointestinal system disorders in the elderly were much higher than that in adults. Luo et al. (2016) reported similar findings that more frequent and diverse nervous, respiratory, and gastrointestinal AEs affect the elderly population compared with the adult population, whose comorbidity, polypharmacy, and pharmacokinetics were different from that of younger adults (Davies and O'Mahony 2015). Conversely, we found that a slightly higher percentage of adult experienced musculoskeletal system disorders than did the elderly, which is inconsistent with previous studies on the subject (Luo et al. 2016).

We generated 11 signals in the elderly. Among them, neuritis, pharyngitis, asthenia, and arthralgia were only detected in the elderly group. Notably, neuritis (a preferred term for Guillain-Barre Syndrome (GBS)) was detected as a signal by both PRR and ROR analysis. Influenza vaccination has been frequently associated with GBS, although evidence for this association is controversial. GBS was first reported following administration of the influenza vaccine in the US during the influenza season of 1976-1977, with an increase in GBS observed in vaccine recipients (approximately one case per 100,000 vaccinations) (Schonberger et al. 1979). Many studies have investigated the association between influenza vaccines and GBS, and a recent meta-analysis found a slight increase in the incidence of GBS (Martín Arias et al. 2015; Sanz Fadrique et al. 2019). Whether there is a causal relationship between GBS and the influenza vaccine requires further evaluation; however, even if the influenza vaccine slightly increases the risk of GBS, avoiding vaccination and risking influenza infection may be a more dangerous decision (Poland et al. 2013). The risk of GBS after an influenza-like illness is considerably higher than that after influenza vaccination, particularly in the elderly (Stowe et al. 2009; Iqbal et al. 2015). In addition, previous studies have shown that vaccinated groups have more favorable GBS outcomes in the long run (Vellozzi et al. 2014).

Furthermore, we found that death was detected as a signal only in the elderly group; however, in previous studies using spontaneous reporting data, no concerning patterns that would suggest a causal relationship between influenza vaccination and deaths were found (Vellozzi et al. 2009; Haber et al. 2014; Vellozzi et al. 2014). In fact, 59 deaths following influenza vaccination were reported in Korea in 2020, mostly between the age of 70 and 90. Subsequently, the Korea Disease Control and Prevention Agency (KDCA) investigated 46 of these cases and did not find evidence of a causal association with influenza vaccination. All deceased individuals had serious health conditions that could account for their cause of death (Centers for Disease Control and Prevention 2020). Therefore, signal validation through an in-depth evaluation of these 14 deaths is required. We also identified arthralgia as a signal in the elderly group using all three data mining methods. Interestingly, Asakawa et al. (2005) previously reported one case of reactive arthritis following influenza vaccination in Japan. However, to the best of our knowledge, limited studies have confirmed the causal relationship between the influenza vaccine and arthralgia currently; thus our results need further epidemiological studies.

In this study, PRR, ROR, and IC methods were used to detect safety signals because inconsistent results were often encountered among previous study methods due to differences in the definition of AEs and signal score thresholds. These DA techniques have the advantage of being rapid and inexpensive and can provide information about the potential association between drugs and AEs. The PRR method involves evaluating the degree of disproportionate reporting of an AE for a product of interest compared with the reporting of this same AE for all other products in the database. Similarly, the ROR method evaluates the odds of an AE of interest being observed with a product of interest compared to the odds of the same AE being observed with all other products in the database. However, neither PRR nor ROR adjust for a small number of observed or expected AEs, and when the number of AEs is small, the results of these algorithms tend to become unstable and yield potentially high estimates with wide confidence intervals and false-positive results. In such situations, the Bayesian analysis methods of the IC algorithm may be more appropriate. The IC algorithm may also be useful when screening signals for further studies, as it generally reduces the number of false-positive values. Therefore, it is necessary to use complementary methods.

However, this study had some limitations. Firstly, passive surveillance systems such as the KIDS-KD database have the inherent limitations of missing information, inconsistent quality of individual case safety reports, duplicated reporting, and under-reporting due to lack of awareness (Rosenthal and Chen 1995). In addition, the signals generated in this study using quantitative signal detection methods only indicate a potential relationship between the influenza vaccine and specified AEs, albeit we aimed to reflect a causal relationship between them. Therefore, our results should be interpreted with caution and should be considered only exploratory. Further pharmacoepidemiological studies are needed to confirm our findings (Varricchio et al. 2004).

In this safety surveillance study of the influenza vaccine in those older than 18 years of age using disproportionality-based data mining methods (PRR, ROR, and IC) in the KIDS-KD, we found that the safety profiles of AEs following influenza vaccination were more serious in the elderly than in adults. Four signals were detected only in the elderly group: neuritis, pharyngitis, asthenia, and arthralgia. These AEs therefore need more careful monitoring in the elderly. Further evaluations and validations are needed to investigate this causal relationship.

Conflict of interest

J-YS received grants from the Ministry of Food and Drug Safety, the Ministry of Health and Welfare, the National Research Foundation of Korea, and pharmaceutical companies, including Daiichi Sankyo, GSK, and Pfizer, outside of the submitted work. S-YJ received grants from the Ministry of Food and Drug Safety, and the Ministry of Health and Welfare. No other potential conflict of interest relevant to this article was reported.

Acknowledgements

The authors thank the Korea Institute of Drug Safety and Risk Management (KIDS) for their cooperation in providing access to the Korea Adverse Event Reporting System Database. We would like to thank Editage (www.editage.co.kr) for editing and reviewing this manuscript for English language. This work was supported by a grant (21153MFDS607) from the Ministry of Food and Drug Safety of South Korea in 2021-2025 (to J-YS) and a grant (20200509312-00) from the Ministry of Food and Drug Safety of South Korea in 2020 (to S-YJ). Moreover, this work was supported by the Bio Industry Technology Development Program (No. 20015086) By the Ministry of Trade, Industry & Energy (MOTIE, Korea). The funders had no role in the study design, data collection and analysis, interpretation of data, writing of the report, and the decision to submit the article for publication.

Fig 1.

Figure 1.Flowchart of selection for spontaneous reports of adverse events. AE, adverse event; KIDS-KD, Korea Institute of Drug Safety & Risk Management-Korea Adverse Event Reporting System Database.
Drug Targets and Therapeutics 2022; 1: 51-58https://doi.org/10.58502/DTT.22.004

Table 1 Demographic characteristics of vaccine-related adverse event reports in adults between 2005 and 2019

Characteristics19-64 years65 years or older
TotalInfluenza vaccineAll other vaccinesTotalInfluenza vaccineAll other vaccines
N = 12,635 (%)N = 7,995 (%)N = 4,640 (%)N = 2,001 (%)N = 1,010 (%)N = 991 (%)
Gender
Male2,727 (21.58)1,801 (22.53)926 (19.96)749 (37.43)383 (37.92)366 (36.93)
Female9,810 (77.64)6,169 (77.16)3,641 (78.47)1,222 (61.07)622 (61.58)600 (60.54)
Missing98 (0.78)25 (0.31)73 (1.57)30 (1.50)5 (0.50)25 (2.52)
Report type
Spontaneous report6,938 (54.91)3,992 (49.93)2,946 (63.49)1,165 (58.22)319 (31.58)846 (85.37)
Research5,525 (43.73)3,929 (49.14)1,596 (34.40)780 (38.98)661 (65.45)119 (12.01)
Literature58 (0.46)18 (0.23)40 (0.86)27 (1.35)8 (0.79)19 (1.92)
Other114 (0.90)56 (0.70)58 (1.25)29 (1.45)22 (2.18)7 (0.71)
Report source by professions
Medical worker*8,672 (68.64)5,320 (66.54)3,352 (72.24)950 (47.48)473 (46.84)477 (48.13)
Consumer1,389 (10.99)888 (11.11)501 (10.80)74 (3.70)13 (1.29)61 (6.16)
Others**1,548 (12.25)971 (12.15)577 (12.44)735 (36.73)299 (29.60)436 (43.99)
Missing1,026 (8.12)816 (10.21)210 (4.53)242 (12.09)225 (22.28)17 (1.72)
Report source by affiliation
Regional drug safety center4,259 (33.71)3,555 (44.47)704 (15.17)308 (15.39)103 (10.20)205 (20.69)
Pharmaceutical company7,496 (59.33)4,198 (52.51)3,298 (71.08)1,116 (55.77)708 (70.1)408 (41.17)
Medical institution194 (1.54)104 (1.30)90 (1.94)9 (0.45)2 (0.20)7 (0.71)
Pharmacy1 (0.01)0 (0.00)1 (0.02)0 (0.00)0 (0.00)1 (0.00)
Health center0 (0.00)0 (0.00)0 (0.00)1 (0.05)0 (0.00)1 (0.10)
Customer183 (1.45)7 (0.09)176 (3.79)33 (1.65)8 (0.79)25 (2.52)
Others502 (3.97)131 (1.64)371 (8.00)534 (26.69)189 (18.71)345 (34.81)
Serious adverse events
Yes660 (5.22)228 (2.85)432 (9.31)239 (11.94)121 (11.98)118 (11.91)
No11,975 (94.78)7,767 (97.15)4,208 (90.69)1,762 (88.06)889 (88.02)873 (88.09)

*Medical workers included doctors, pharmacists, and nurses.

**Others included lawyers and other healthcare professionals.


Table 2 The frequency of adverse events attributed to the influenza vaccine and all other vaccines in adults between 2005 and 2019

Adverse eventTotal19-64 years65 years or older
(WHO-ART SOC code)Influenza vaccineAll other vaccinesInfluenza vaccineAll other vaccinesInfluenza vaccineAll other vaccines
N = 18,117N = 13,252N = 15,986N = 11,254N = 2,131N = 1,998
AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)AE-Pairs (%)
Application site disorders7,261 (40.08)5,174 (39.05)6,561 (41.04)4,494 (39.94)700 (32.85)680 (34.03)
Body as a whole - general disorders4,106 (22.67)2,217 (16.73)3,680 (23.02)1,771 (15.74)426 (19.99)446 (22.32)
Musculo-skeletal system disorders2,499 (13.79)958 (7.23)2,229 (13.94)781 (6.94)270 (12.67)177 (8.86)
Central & peripheral nervous system disorders1,491 (8.23)1,266 (9.55)1,210 (7.57)1,130 (10.04)281 (13.19)136 (6.81)
Respiratory system disorders980 (5.41)391 (2.95)841 (5.26)307 (2.73)139 (6.52)84 (4.20)
Skin and appendages disorders684 (3.78)1,088 (8.21)566 (3.54)921 (8.18)118 (5.54)167 (8.36)
Gastro-intestinal system disorders508 (2.80)629 (4.75)419 (2.62)556 (4.94)89 (4.18)73 (3.65)
Psychiatric disorders216 (1.19)161 (1.22)202 (1.26)128 (1.14)14 (0.66)33 (1.65)
Metabolic and nutritional disorders49 (0.27)32 (0.24)44 (0.28)28 (0.25)5 (0.23)4 (0.20)
Vision disorders45 (0.25)55 (0.42)33 (0.21)49 (0.44)12 (0.56)6 (0.30)
Cardiovascular disorders, general34 (0.19)68 (0.51)23 (0.14)45 (0.40)11 (0.52)23 (1.15)
Resistance mechanism disorders29 (0.16)282 (2.13)25 (0.16)210 (1.87)4 (0.19)72 (3.60)
Urinary system disorders25 (0.14)86 (0.65)19 (0.12)60 (0.53)6 (0.28)26 (1.30)
Hearing and vestibular disorders24 (0.13)27 (0.20)14 (0.09)22 (0.20)10 (0.47)5 (0.25)
Secondary terms - events24 (0.13)366 (2.76)18 (0.11)336 (2.99)6 (0.28)30 (1.50)
Heart rate and rhythm disorders24 (0.13)19 (0.14)20 (0.13)18 (0.16)4 (0.19)1 (0.05)
Vascular (extracardiac) disorders22 (0.12)39 (0.29)8 (0.05)30 (0.27)14 (0.66)9 (0.45)
Platelet, bleeding & clotting disorders16 (0.09)28 (0.21)11 (0.07)17 (0.15)5 (0.23)11 (0.55)
Foetal disorders15 (0.08)51 (0.38)15 (0.09)51 (0.45)0 (0.00)0 (0.00)
Reproductive disorders, female14 (0.08)170 (1.28)14 (0.09)170 (1.51)0 (0.00)0 (0.00)
Liver and biliary system disorders11 (0.06)25 (0.19)6 (0.04)20 (0.18)5 (0.23)5 (0.25)
White cell and RES* disorders13 (0.07)37 (0.28)11 (0.07)35 (0.31)2 (0.09)2 (0.10)
Myo-, endo-, pericardial & valve disorders7 (0.04)2 (0.02)2 (0.01)1 (0.01)5 (0.23)1 (0.05)
Neoplasms5 (0.03)26 (0.20)1 (0.01)25 (0.22)4 (0.19)1 (0.05)
Collagen disorders4 (0.02)27 (0.20)4 (0.03)24 (0.21)0 (0.00)3 (0.15)
Poison specific terms4 (0.02)3 (0.02)4 (0.03)3 (0.03)0 (0.00)0 (0.00)
Neonatal and infancy disorders3 (0.02)3 (0.02)3 (0.02)3 (0.03)0 (0.00)0 (0.00)
Red blood cell disorders2 (0.01)1 (0.01)1 (0.01)0 (0.00)1 (0.05)1 (0.05)
Endocrine disorders1 (0.01)8 (0.06)1 (0.01)8 (0.07)0 (0.00)0 (0.00)
Special senses other, disorders0 (0.00)2 (0.02)0 (0.00)2 (0.02)0 (0.00)0 (0.00)
Reproductive disorders, male0 (0.00)10 (0.08)0 (0.00)8 (0.07)0 (0.00)2 (0.10)
Missing1 (0.01)1 (0.01)1 (0.01)1 (0.01)0 (0.00)0 (0.00)

WHO-ART, World Health Organization Adverse Reactions Terminology; SOC, system organ class; AE, adverse event; RES, reticuloendothelial system.


Table 3 Signal detection of influenza vaccine received at greater than 18 years of age compared to all other vaccines between 2005 and 2019

Adverse events (WHO-ART PT Level)No. of AE-PairsPRRRORICSignal detection
PRRRORIC
Total
Sweating increased1383.263.270.18YYY
Injection site inflammation9203.033.140.36YYY
Injection site pain4,0101.251.320.07Y
Myalgia2,2082.352.540.32YYY
Dysphonia1410.2410.25−0.32YY
Headache8161.731.760.15Y
Neuritis522.932.93−0.05YY
Somnolence1212.682.690.10YYY
Coughing1332.372.380.08YYY
Pleural pain2210.52Y
Rhinitis1882.702.710.17YYY
Sputum increased243.513.51−0.24YY
Asthenia2052.002.010.09YY
Fatigue1,18510.4411.100.58YYY
Malaise5343.833.920.38YYY
Rigors5702.482.530.26YYY
Injection site pressure sensation62090.7093.880.62YYY
Tenderness nos19370.5971.340.49YYY

WHO-ART, World Health Organization-Adverse Reactions Terminology; PT, preferred term; AE, adverse event; PRR, proportional reporting ratio; ROR, reporting odds ratio; IC, information component; Y, AE was detected as a signal.


Table 4 Signal detection of influenza vaccine compared with all other vaccines based on two age groups between 2005 and 2019

Adverse events(WHO-ART PT Level)No. of AE-PairsPRRRORICSignal detection
PRRRORIC
19-64 years old
Sweating increased1032.342.350.02YYY
Injection site inflammation7042.232.290.23YYY
Injection site pain3,7031.111.140.01Y
Myalgia2,0182.072.230.27YYY
Dysphonia128.458.45−0.43YY
Headache7011.431.450.05Y
Somnolence1212.582.590.08YYY
Pleural pain2050.49Y
Rhinitis1702.352.360.11YYY
Fatigue1,1019.349.960.55YYY
Malaise5123.533.620.34YYY
Rigors5012.102.130.19YYY
Injection site pressure sensation60284.7688.040.60YYY
Tenderness nos19167.2368.030.47YYY
65+ years old
Sweating increased355.475.540.09YYY
Injection site inflammation2167.798.550.53YYY
Injection site pain3071.511.590.06Y
Arthralgia544.224.300.16YYY
Headache1153.373.500.25YYY
Neuritis180.04Y
Pharyngitis292.472.49−0.17YY
Asthenia502.762.800.02YYY
Death144.384.40−0.30YY
Fatigue847.888.160.37YYY
Injection site pressure sensation180.04Y

WHO-ART, World Health Organization-Adverse Reactions Terminology; PT, preferred term; AE, adverse event; PRR, proportional reporting ratio; ROR, reporting odds ratio; IC, information component; Y, AE was detected as a signal.


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