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. 2025 Feb 25;20(2):e0318597. doi: 10.1371/journal.pone.0318597

Epidemiology of reported serious adverse drug reactions due to anti-infectives using nationwide database of Thailand

Sopit Sittiphan 1,2, Apiradee Lim 1,*, Haris Khurram 3,1,*, Nurin Dureh 1, Kwankamon Dittakan 4
Editor: Obed Kwabena Offe Amponsah5
PMCID: PMC11856502  PMID: 39999099

Abstract

Serious Adverse Drug Reactions (ADRs) can cause a longer stay, which can result in fatal outcomes. Understanding the prognostic factors for the serious ADRs play a vital role in developing appropriate serious ADR prevention strategies. This study aimed to analyze nationwide database in Thailand to identify predisposing factors associated with the serious ADRs, explore drug exposure, distribution of serious ADRs, types of ADRs, and classify the determinants of serious ADR due to anti-infective in Thailand. The national database of anti-infective-induced ADRs from January 2012 to December 2021 in Thailand’s 77 provinces, Thai Vigibase at the Health Product Vigilance Center (HPVC), was considered. After pre-processing, frequencies and percentages were used to investigate the distribution of ADR seriousness. To determine the significance of the independent variables on the seriousness of anti-infective-induced ADRs, logistic regression and the Classification and Regression Tree (CART) model were performed. A p-value < 0.05 was considered statistically significant. A total of 82,333 ADR cases, of which 20,692 were serious ADRs (25.13%). Serious ADRs is statistically associated with region, gender, ethnicity, age, type of patient, history of drug allergy, chronic disease and dose frequency (p-value < 0.001). The most commonly reported serious ADRs were in the South region of Thailand (OR = 1.92, 95% CI = 1.88–1.97), followed by the North region (OR = 1.68, 95% CI = 1.64–1.71) of Thailand. Gender and history of drug allergy were also statistically associated with the seriousness of ADRs (p-value = 0.001). Reported ADRs revealed that patients were males (OR =  1.11, 95% CI = 1.11–1.13) and those with a prior history of drug allergy (OR = 1.22, 95% CI = 1.20–1.24) were more likely to experience serious ADRs. The risk of having an ADR reported as serious was significantly higher in patients aged 60 and over (OR = 1.42, 95% CI = 1.39–1.46) and patients aged 40–59 years (OR = 1.34, 95% CI = 1.31–1.37) compared to patients aged 0–19 years. IPD patients most commonly associated with serious ADRs. The results of this study will enable healthcare professionals to use caution when prescribing to those groups. Furthermore, developing a reporting system to reduce serious ADR evidence, such as software with electronic prescribing databases or applications that enable efficient detection of ADRs in high-risk groups, was critical in order to closely monitor and improve patient safety.

Introduction

Adverse Drug Reactions (ADRs), which can occur in any drug class and cause global morbidity and hospitalization, will be a public health issue. [1–4]. According to the study’s findings, the ADR admissions incidence ranged from 0.60% to 7.0%, with the median length of hospital stay varying from 3 to 8.7 days [5]. ADRs cause not only unnecessary morbidity but also mortality. According to other studies, fatal adverse drug reactions accounted for 3% of all deaths in the population [6], and more than 80% of reported drug-drug interactions-adverse drug reactions (DDI- ADRs) were serious, with 7% being fatal [7]. Serious ADRs can cause a longer stay, which can result in fatal outcomes [8]. A serious ADR is defined as any event or reaction that results in death or life threatening, requires hospital admission or prolongation of an existing hospital stay, result in persistent or significant disability/incapacity, or is cancers, congenital anomalies, birth defects, or other medically important conditions [9].

Anti-infective drugs, including antibiotics, antifungals, antivirals, and antiprotozoals, have saved countless lives and alleviated suffering [10,11]. However, anti-infective drugs are the leading cause of adverse drug reactions (ADRs) worldwide [6,12–15]. In particular, antibiotics are the most common cause of life-threatening off-target immune-mediated drug reactions, including severe cutaneous adverse reactions [16]. Antibiotics are the most prescribed drugs worldwide and are growing in use. Moreover, antibiotic overuse increases ADRs and antimicrobial resistance [17,18]. The study in Saudi Arabia also found that vancomycin and ceftriaxone, which are anti-infective drugs, were the most commonly associated with serious adverse drug reactions [15].

Understanding the prognostic factors for the seriousness of adverse drug reactions due to anti-infectives plays a vital role in developing appropriate serious ADR prevention strategies [8] and improving the survival rate of patients. The majority of studies have focused on factors influencing the occurrence of ADRs [19–26]. However, only a few studies explore the related risk factors for the seriousness of ADRs [8,27,28] and analyze data in Thailand [29]. Thai Vigibase, the HPVC-regulated national spontaneous reporting database, began in 1984. Health professionals and marketing authorization holders in the public and private sectors must report nationwide ADRs [30]. The previous research [29] used Thai Vigibase to study the factors associated with serious outcomes of ADRs caused only by Dimenhydrinate, which are of limited scope. Therefore, the purpose of this study was to analyze a large-scale nationwide database in Thailand to investigate the predisposing factors associated with serious ADRs and explore drug exposure to ADRs and their pattern. Also, identify the distribution of serious ADRs. Moreover, explores the types of ADRs, and classifies the determinants of serious ADRs due to anti-infectives in Thailand.

Materials and methods

Data source and study population

The Health Product Vigilance Center’s retrospective anti-infective-induced ADR data from Thailand’s 77 provinces from January 2012 to December 2021 were utilized. The Thai Food and Drug Administration (FDA) approved database access with patient anonymity. This study included a total of 82,333 ADR cases.

Inclusion and exclusion criteria

The study included reported cases with at least one anti-infective ADR case report as suspected, causality assessment of ADRs using Naranjo’s algorithm, WHO’s criteria, and Thai algorithm, and anti-infective-induced ADR reports classified as “certain”, “probable”, or “possible”. The study excluded reports that did not identify the seriousness of ADRs, drugs, or were classified as “unlikely”. Furthermore, cases identified as non-anti-infective drugs were excluded from the analysis.

Data description and pre-processing

The data include patient characteristics (gender, age, ethnicity, type of patient, history of drug allergy, and chronic disease), medication records (disease, ATC class, dosage form, dose frequency, anti-infective drug group), and adverse event information (the seriousness of ADRs, onset of ADRs, province, and response to ADRs). We divided the participants into four age groups: 0 to 19, 20 to 39, 40 to 59, and 60 and older. We separated the participants’ ethnicities into two categories: Thai and non-Thai. We classified the type of patient into two groups: inpatient (IPD) and outpatient (OPD). We classified the history of drug allergy as either yes or no. Moreover, diabetes mellitus (DM), hypertension (HT), dyslipidemia, ischemic heart disease, hepatic function abnormalities, and renal efficiency are among the various chronic diseases.

Diseases or medical conditions were classified by the International Classification of Diseases and Related Health Problems 10th Revision (ICD-10) list by the World Health Organization (WHO) [31]. Anatomical Therapeutic Chemical (ATC) classified drugs into 14 classes, including alimentary tract and metabolism, blood and blood-forming organs, cardiovascular system, dermatological, genito-urinary system and sex hormones, systemic hormonal preparations (excluding insulin and sex hormones), anti-infective agents for systemic use, antineoplastic and immunomodulating agents, musculo-skeletal system, nervous system, antiparasitic products, insecticides and repellents, respiratory system, sensory organs, and various [32]. The following dosage forms were classified based on the route of administration: oral, topical, rectal, parenteral, vaginal, inhaled, liquid ophthalmic, and others. The dose frequency was divided into three categories: less than 2 times, between 2 and 5 times, and greater than 5 times. Furthermore, anti-infective drugs are classified based on the function of anti-infective agents such as anti-mycobacterial, antifungal, antiviral, antimalarial, anthelmintic, anti-tuberculosis, and antibiotic [33]. Antibiotics were sub-grouped by chemical structure.

The seriousness of ADRs is divided into serious ADRs and non-serious ADRs. Serious ADR is defined as an adverse drug reaction that caused any of the following six conditions to the patient: 1) Death, 2) A life-threatening situation, 3) Hospitalization, 4) Persistent or significant disability/incapacity, 5) Congenital anomaly/birth defect, and 6) A medically significant situation [19]. The onset of ADRs was analyzed from the first dose of the investigational drug to the first occurrence of the ADRs of interest, classified as < 5 days or > 5 days [34]. We divided Thailand’s 77 provinces where ADRs occurred into five regions: Central, East, North, North-East, and South [35]. Furthermore, responses to ADRs include redosing but changed route administration; redosing but dose increased; redosing but dose reduced; redosing and dose not changed, and stopping using the product.

Statistical analysis

Frequency distribution and cross-tabulation were used to examine the factor, exposure, and distribution of the seriousness of anti-infective-induced ADRs. Pearson Chi-square test was used to evaluate the univariate association between different factors and types of ADR. The logistic regression model was used to investigate the factors and their role in serious ADRs. Finally, to classify the determinants of serious anti-infective-induced ADRs, the Classification and Regression Tree (CART) model was used. A p-value < 0.05 was considered as statistically significant.

Ethical approval

This is an observational study based on secondary data and approved by the Research Ethics Committee for Science, Technology and Health Science, Prince of Songkla University, Thailand (number: psu.pn.1-004/66).

Results

A total of 82,333 ADR cases, of which 20,692 were serious ADRs (25.13%). The seriousness of ADRs is statistically associated with region, gender, ethnicity, age, type of patient, history of drug allergy, chronic disease; diabetes mellitus (DM), hypertension (HT), dyslipidemia, ischaemic heart disease, hepatic function abnormalities, renal insufficiency, and dose frequency (p-value < 0.001). The most commonly reported serious ADRs were in the North-East region of Thailand (29.3%), followed by Thailand’s North region (27.8%), South region (25.9%), East region (23.5%), and Central region (20.3%), respectively. The female-male rate of serious ADRs was 1.12. 24.9% of Thai patients reported serious ADRs. The proportion of serious ADRs in elderly patients (60 years and over 60 years) 28.8% was higher than the serious ADRs in adult patients. Overall, these serious ADRs were more common in IPD patients than OPD patients. A total of 27.1% of serious cases reported had a prior history of drug allergy. Furthermore, most serious ADR cases had chronic disease including, diabetes millitus (DM), hypertension (HT), dyslipidemia, ischaemic heart disease, hepatic function abnormalities, and renal insufficiency (Table 1).

Table 1. Distribution and association of demographic characteristics’s patients, dose frequency and ADRs onset with the seriousness of anti-infective-induced-ADRs; N = 82,333.

Variable Categories Non-serious N (%) Serious N (%) p-value
Region Central 19,075 (79.8%) 4,832 (20.2%) < 0.001
East 7,374 (76.5%) 2,264 (23.5%)
North 9,785 (72.2%) 3,762 (27.8%)
North East 15,068 (70.7%) 6,232 (29.3%)
South 10,075 (74.1%) 3,516 (25.9%)
Missing 264 (75.4%) 86 (24.6%)
Gender Male 25,002 (72.0%) 9,747 (28.0%) < 0.001
Female 36,452 (77.0%) 10,873 (23.0%)
Missing 187 (72.2%) 72 (27.8%)
Ethnicity Thai 58,083 (75.1%) 19,227 (24.9%) 0.031
Other 856 (78.0%) 242 (22.0%)
Missing 2,702 (68.8%) 1,223 (31.2%)
Age (year) 0–19 9,446 (80.0%) 2,365 (20.0%) < 0.001
20–39 23,677 (76.0%) 7,463 (24.0%)
40–59 16,052 (73.4%) 5,826 (26.6%)
60 and above 12,466 (71.2%) 5,038 (28.8%)
Type of patient IPD 26,225 (65.9%) 13,595 (34.1%) < 0.001
OPD 29,166 (84.2%) 5,472 (15.8%)
Missing 6,250 (79.4%) 1,625 (20.6%)
History of Drug Allergy No 44,716 (75.7%) 14,321 (24.3%) < 0.001
Yes 8,795 (72.9%) 3,273 (27.1%)
Missing 8,130 (72.4%) 3,098 (27.6%)
Chronic disease No 59,071 (75.1%) 19,629 (24.9%) < 0.001
Yes 2,570 (70.7%) 1,063 (29.3%)
Diabetes millitus (DM) No 60,605 (75.0%) 20,194 (25.0%) < 0.001
Yes 1,036 (67.5%) 498 (32.5%)
Hypertension (HT) No 59,966 (75.0%) 19,978 (25.0%) < 0.001
Yes 1,675 (70.1%) 714 (29.9%)
Dyslipidemia No 60,892 (74.9%) 20,359 (25.1%) < 0.001
Yes 749 (69.2%) 333 (30.8%)
Ischaemic Heart Disease No 61,483 (74.9%) 20,620 (25.1%) 0.031
Yes 158 (68.7%) 72 (31.3%)
Hepatic Function Abnomalities No 61,547 (74.9%) 20,629 (25.1%) < 0.001
Yes 94 (59.9%) 63 (40.1%)
Renal Insufficiency No 61,245 (75.0%) 20,428 (25.0%) < 0.001
Yes 396 (60.0%) 264 (40.0%)
Missing 25,569 (72.9%) 9,495 (27.1%)
Dose Frequency < 2 31,251 (72.8%) 11,653 (27.2%) < 0.001
> 5 14,642 (75.1%) 4,859 (24.9%)
2 to 5 15,748 (79.0%) 4,180 (21.0%)
ADRs Onset (day) < 5 days 24,641 (75.1%) 8,167 (24.9%) 0.199
> 5 days 37,000 (74.7%) 12,525 (25.3%)
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Table 2 presents a list of commonly occurring serious ADRs within the Anatomical Therapeutic Drug Class (ATC) and anti-infective drug category. The ATC classes were alimentary tract and metabolism (44.0%), followed by dermatological (39.1%) and antiparasidic products (36.4%), respectively. Antibiotics categorized by chemical structure were sulfone (66.7%), followed by betalactam (57.9%), and polymyxin (55.8%), respectively.

Table 2. Distribution and association of the Anatomical Therapeutic Drug Class (ATC) and anti-infective drug type with the seriousness of anti-infective-induced-ADRs; N = 82,333.

Variable Categories Non-serious N(%) Serious N(%) p-value
The Anatomical Therapeutic Drug Class (ATC) Alimentary tract and metabolism(a) 163 (56.0%) 128 (44.0%) < 0.001
Antiparasitic products(p) 35 (63.6%) 20 (36.4%)
Dermatologicals(d) 14 (60.9%) 9 (39.1%)
General antiinfectives, systemic(j) 60,766 (74.9%) 20,402 (25.1%)
Genito urinary system and sex hormones(g) 629 (83.3%) 126 (16.7%)
Sensory organs(s) 24 (88.9%) 3 (11.1%)
Anti-Infective Drug Type Anthelmintics 4 (57.1) 3 (42.9) < 0.001
Antibiotic-Aminoglycoside 453 (65.4) 240 (34.6)
Antibiotic-Aminosalicylic acid 2 (100) 0 (0)
Antibiotic-Betalactam 858 (42.1) 1,182 (57.9)
Antibiotic-Carbapenem 1,528 (72.6) 576 (27.4)
Antibiotic-Cephalosporin 18,391 (79.8) 4,652 (20.2)
Antibiotic-Chloramphenicol 59 (93.7) 4 (6.3)
Antibiotic-Fluoroquinolone 6,193 (80) 1,551 (20)
Antibiotic-Fusidic acid 8 (66.7) 4 (33.3)
Antibiotic-Glycopeptides 122 (60.1) 81 (39.9)
Antibiotic-Glycylcyclines 15 (93.8) 1 (6.2)
Antibiotic-Lincosamide 5,112 (82.7) 1,073 (17.3)
Antibiotic-Macrolide 1,602 (79.8) 405 (20.2)
Antibiotic-Monoxycarbolic acid 13 (86.7) 2 (13.3)
Antibiotic-Nitrofuran 7 (53.8) 6 (46.2)
Antibiotic-Nitroimidazole 621 (84.5) 114 (15.5)
Antibiotic-Oxazolidinone 11 (45.8) 13 (54.2)
Antibiotic-Para Aminosalicylic acid (PAS) 10 (100) 0 (0)
Antibiotic-Penicillin 14,735 (76.5) 4,516 (23.5)
Antibiotic-Phosphonic acid 141 (77) 42 (23)
Antibiotic-Polymyxin 65 (44.2) 82 (55.8)
Antibiotic-Sulfonamide 3,180 (63.7) 1,814 (36.3)
Antibiotic-Sulfone 84 (33.3) 168 (66.7)
Antibiotic-Tetracycline 2,144 (78.4) 592 (21.6)
Antifungal 526 (63.7) 300 (36.3)
Antimalarial 31 (64.6) 17 (35.4)
Antiviral 4,115 (73.2) 1,504 (26.8)
Anti-Tuberculosis 1,601 (47.8) 1,746 (52.2)
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Moreover, the anatomical therapeutic drug class (ATC) and anti-infective drug type are statistically associated with the seriousness of ADRs (p-value < 0.001). When classified by disease classification and ADRs classified by system organ class (adverse disorder), are statistically associated with a p-value < 0.001. Anti-infective use primarily caused certain infections and parasitic diseases (32.8%), followed by disease of the nervous system (31.4%) and symptoms, signs, and abnormal clinical and laboratory findings not elsewhere classified (27.3%), respectively. Infections and infestations (78.4%) were the most adverse disorders, followed by injury, poisoning, and procedural complications (74.0%) and vascular disorders (67.1%), respectively (Table 3).

Table 3. Distribution and association of diseases classification and ADRs classified by system organ class (Adverse Disorder) with the seriousness of anti-infective-induced-ADRs; N = 82,333.

Variable Categories Non-serious N(%) Serious N(%) p-value
2024 ICD-10-CM Diseases classification Certain conditions originating in the perinatal period 102 (85.0%) 18 (15.0%) < 0.001
Certain infectious and parasitic diseases 14,891 (67.2%) 7,281 (32.8%)
Congenital malformations, deformations and chromosomal abnormalities 47 (81.0%) 11 (19.0%)
Disease of Thai Traditional medicine 171 (76.7%) 52 (23.3%)
Diseases of the circulatory system 745 (76.7%) 226 (23.3%)
Diseases of the digestive system 3,239 (81.8%) 721 (18.2%)
Diseases of the eye and adnexa 933 (84.7%) 169 (15.3%)
Diseases of the genitourinary system 5,807 (81.5%) 1,314 (18.5%)
Diseases of the musculoskeletal system and connective tissue 1,291 (79.5%) 333 (20.5%)
Diseases of the nervous system 251 (68.6%) 115 (31.4%)
Diseases of the respiratory system 8,018 (78.0%) 2,258 (22.0%)
Diseases of the skin and subcutaneous tissue 4,937 (78.0%) 1,391 (22.0%)
Endocrine, nutritional and metabolic diseases 159 (74.6%) 54 (25.4%)
External causes of morbidity 365 (82.8%) 76 (17.2%)
Factors influencing health status and contact with health services 1,031 (81.4%) 236 (18.6%)
Injury, poisoning and certain other consequences of external causes 3,872 (75.3%) 1,273 (24.7%)
Mental, Behavioral and Neurodevelopmental disorders 39 (90.7%) 4 (9.3%)
Other specified postsurgical states 3 (100.0%) 0 (0%)
Pregnancy, childbirth and the puerperium 794 (84.9%) 141 (15.1%)
Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified 3,401 (72.7%) 1,275 (27.3%)
Adverse Disorder Blood and lymphatic 437 (53.8%) 375 (46.2%) < 0.001
Cardiac 1,121 (80.2%) 276 (19.8%)
Congenital, familial and genetic 29 (36.7%) 50 (63.3%)
Ear and labyrinth 29 (72.5%) 11 (27.5%)
Endocrine 64 (90.1%) 7 (9.9%)
Eye 797 (81.1%) 186 (18.9%)
Gastrointestinal 1,680 (85.1%) 295 (14.9%)
General disorders and administration 1,690 (82.8%) 352 (17.2%)
Hepatobiliary 695 (41.2%) 992 (58.8%)
Immune 11,720 (69.5%) 5,137 (30.5%)
Infections and infestations 255 (21.6%) 926 (78.4%)
Injury, poisoning and procedural complications 394 (26.0%) 1,124 (74.0%)
Investigations 235 (67.0%) 116 (33.0%)
Metabolism and nutrition disorders 611 (78.3%) 169 (21.7%)
Musculoskeletal and connective tissue 190 (79.8%) 48 (20.2%)
Neoplasms benign, malignant 3 (33.3%) 6 (66.7%)
Nervous system disorders 503 (81.3%) 116 (18.7%)
Pregnancy, puerperium and perinatal 4 (80.0%) 1 (20.0%)
Psychiatric disorders 72 (78.3%) 20 (21.7%)
Renal and urinary disorders 258 (49.4%) 264 (50.6%)
Reproductive system and breast 88 (80.7%) 21 (19.3%)
Respiratory, thoracic and mediastinal 2,831 (79.9%) 711 (20.1%)
Skin and subcutaneous tissue 36,962 (83.1%) 7,511 (16.9%)
Surgical and medical procedures 5 (83.3%) 1 (16.7%)
Vascular disorders 968 (32.9%) 1,977 (67.1%)
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Fig 1 shows the type of anti-infective ADR seriousness. 74.87% of all ADRs were found to be non-serious. Despite 25.13% being serious ADRs. That is, 21.84% was hospitalization, followed by others (3.02%), 0.24 was death, and 0.03% was disability, respectively.

Fig 1. Type of Anti-Infective-Induced.

Fig 1

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The most responses to non-serious ADRs were reducing and dose increasing (100%), followed by reducing but changing route administration (83.2%) and redosing but dose not changing (80.5%), respectively. On the other hand, the most common responses to serious ADRs were redosing but reducing the dose (44.8%), followed by stopping the drug (25.3%) and redosing but not changing the dose (19.5%), respectively as Fig 2.

Fig 2. Serious ADRs in responses to Anti-Infective-Induced ADRs.

Fig 2

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When non-serious ADRs occurred, all responses were used, such as, stop using the drug, redosing and does not change, redosing but dose increased, redosing but dose reduced, and redosing but changed route administration. Conversely, a different approach was taken when serious ADRs emerged. Redosing but dose increased was not used for all serious cases, stop using the drug that was used for all serious ADRs. Particularly in cases of disability and death (Fig 3).

Fig 3. Association between Redosing and type of Anti-Infective-Induced-ADRs.

Fig 3

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Table 4 presents risk factors associated with the seriousness of anti-infective-induced ADRs, after adjusting for potential confounding variables. The region was statistically associated with the seriousness of ADRs (p-value < 0.001). The most commonly reported serious ADRs were in the South region of Thailand (OR = 1.92, 95% CI = 1.88–1.97), followed by the North region (OR = 1.68, 95% CI = 1.64–1.71), the North-East region (OR = 1.58, 95% CI = 1.55–1.61), and the East region (OR = 1.17, 95% CI = 1.13–1.20), compared to the Central region of Thailand. Gender and history of drug allergy were also statistically associated with the seriousness of ADRs (p-value = 0.001). From the reported ADRs, males (OR = 1.11, 95% CI = 1.11–1.13) and those with a prior history of drug allergy (OR = 1.22, 95% CI = 1.20–1.24) experienced more serious ADRs compared to females and those without a history of drug allergy, respectively. The risk of having an ADR reported as serious was significantly higher in patients aged 60 and over (OR = 1.42, 95% CI = 1.39–1.46) and patients aged 40–59 years (OR = 1.34, 95% CI = 1.31–1.37) compared to patients aged 0–19 years. IPD patients most commonly associated with serious ADRs. Conversely, the risk of having an ADR reported as serious was significantly higher in dermatologists (OR = 4.01, 95% CI = 2.58–6.24) compared to alimentary tract and metabolism. Although anti-infective drug type was significantly associated with the seriousness of ADRs, the impact varied by sub-group.

Table 4. Multiple logistic regression analysis of factors associated with serious adverse drug reactions due to anti-infectives.

Variable Categories Coefficient +  Crude OR [95% CI] Adjusted OR [95% CI]
Region Central Ref.
East 0.15 1.21 [1.19–1.24]*** 1.17 [1.13–1.20]***
North 0.52 1.52 [1.49–1.54]*** 1.68 [1.64–1.71]***
Northeast 0.46 1.63 [1.61–1.66]*** 1.58 [1.55–1.61]***
South 0.65 1.38 [1.35–1.40]*** 1.92 [1.88–1.97]***
Gender Female Ref.
Male 0.11 1.31 [1.29–1.32]*** 1.11 [1.10–1.13]***
Ethnicity Other Ref.
Thai 0.22 1.17 [1.11–1.23]** 1.25 [1.17–1.33]**
Age 0–19 Ref.
20–39 0.23 1.26 [1.24–1.28]*** 1.26 [1.24–1.29]***
40–59 0.29 1.45 [1.42–1.48]*** 1.34 [1.31–1.37]***
60 and above 0.35 1.61 [1.58–1.65]*** 1.42 [1.39–1.46]***
Type of Patient IPD Ref.
OPD −1.42 0.36 [0.36–0.37]*** 0.24 [0.24–0.25]***
History of Drug Allergy No Ref.
Yes 0.20 1.16 [1.14–1.18]*** 1.22 [1.20–1.24]***
Dose Frequency < 2 Ref.
> 5 −0.06 0.89 [0.88–0.90]*** 0.94 [0.92–0.96]**
2 to 5 −0.31 0.71 [0.70–0.72]*** 0.73 [0.72–0.75]***
ADRs onset < 5 days Ref.
> 5 days 0.03 1.02 [1.01–1.03] 1.03 [1.02–1.05]
The Anatomical Therapeutic Drug Class (ATC) Alimentary tract and metabolism(a) Ref.
Antiparasitic products(p) −0.96 0.73 [0.59–0.89] 0.38 [0.22–0.67]
Dermatologicals(d) 1.39 0.82 [0.61–1.10] 4.01 [2.58–6.24]**
General antiinfectives, systemic(j) 0.28 0.43 [0.39–0.46]*** 1.32 [1.06–1.65]
Genito urinary system and sex hormones(g) 0.73 0.26 [0.23–0.28]*** 2.08 [1.39–3.12]
Sensory organs(s) −0.01 0.16 [0.10–0.24]*** 0.99 [0.60–1.61]
Anti-infective Drug Type Anthelmintics Ref.
Antibiotic-Aminoglycoside −1.15 0.71 [0.42–1.19] 0.32 [0.29–0.34]***
Antibiotic-Aminosalicylic acid −12.21 – 0.00 [0.00–9.21E + 61]
Antibiotic-Beta lactam 0.24 1.84 [1.10–3.08] 1.27 [1.22–1.33]***
Antibiotic-Carbapenem −1.54 0.50 [0.30–0.84] 0.21 [0.20–0.23]***
Antibiotic-Cephalosporin −1.93 0.34 [0.20–0.57] 0.15 [0.14–0.15]***
Antibiotic-Chloramphenicol −2.23 0.09 [0.05–0.17]*** 0.11 [0.07–0.16]***
Antibiotic-Fluoroquinolone −1.47 0.33 [0.20–0.56] 0.23 [0.22–0.24]***
Antibiotic-Fusidic acid −0.44 0.67 [0.34–1.29] 0.65 [0.41–1.02]
Antibiotic-Glycopeptides −0.68 0.89 [0.52–1.50] 0.51 [0.40–0.64] * 
Antibiotic-Glycylcyclines −13.28 0.09 [0.04–0.21] *  0.00 [0.00–2.73E + 20]
Antibiotic-Lincosamide −1.72 0.28 [0.17–0.47] *  0.18 [0.17–0.19]***
Antibiotic-Macrolide −1.21 0.34 [0.20–0.57] 0.30 [0.28–0.31]***
Antibiotic-Monoxycarbolic acid −1.71 0.21 [0.10–0.42] 0.18 [0.10–0.34] * 
Antibiotic-Nitrofuran 0.04 1.14 [0.60–2.16] 1.04 [0.57–1.89]
Antibiotic-Nitroimidazole −2.46 0.25 [0.15–0.41] *  0.09 [0.06–0.12]***
Antibiotic-Oxazolidinone −0.82 1.58 [0.88–2.83] 0.44 [0.27–0.71]
Antibiotic-Para Aminosalicylic acid (PAS) −11.71 – –
Antibiotic-Penicillin −1.04 0.41 [0.24–0.68] 0.35 [0.34–0.36]***
Antibiotic-Phosphonic acid −1.85 0.40 [0.23–0.67] 0.16 [0.14–0.18]***
Antibiotic-Polymyxin −0.34 1.68 [0.99–2.85] 0.71 [0.59–0.85]
Antibiotic-Sulfonamide −0.54 0.76 [0.45–1.27] 0.58 [0.56–0.61]***
Antibiotic-Sulfone 0.20 2.67 [1.58–4.50] 1.22 [1.09–1.37]
Antibiotic-Tetracycline −1.11 0.37 [0.22–0.62] 0.33 [0.31–0.34]***
Antifungal −0.63 0.76 [0.45–1.28] 0.53 [0.50–0.57]***
Antimalarial 0.10 0.73 [0.42–1.27] 1.11 [0.63–1.94]
Antiretroviral −0.89 0.49 [0.29–0.82] 0.41 [0.39–0.43]***
AntiTB 0.00 1.45 [0.87–2.44] 0.00 [0.00–0.00]***
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 +

Coefficients were calculated using adjusted model; OR: Odds Ratio; CI: Confidence Intervel; * p-value < 0.1; **p-value < 0.05; ***p-value < 0.01.

The antibiotic group had the largest impact of drug type on serious ADRs. The antibiotic group with the highest impact on serious ADRs was betalactam (OR = 1.27, 95% CI = 1.22–1.33). On the other hand, the risk of having an ADR reported as serious was significantly lower in penicillin and sulfonamide compared to the anthelmintics group (OR = 0.35, 95% CI = 0.34–0.36) and (OR = 0.58, 95% CI = 0.56–0.61), whereas, the non-antibiotic group was antiviral (OR = 0.41, 95% CI = 0.39–0.43) and antifungal (OR = 0.53, 95% CI = 0.50–0.57) compared to the anthelmintics group. The seriousness of ADRs was found to be associated with the type of patient, the type of anti-infective drug, and the region, as shown in Fig 4 (the total subjects).

Fig 4. Classification and regression tree (CART) model to determine the role of anti-infective-induced ADRs in the classification of serious ADRs.

Fig 4

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Specifically, ADRs reveal that patients with IPD (Node 1) who received antifungal, anti-TB, or antibiotics like sulfone, betalactam, or monoxycarbolic acid (Node 8), as well as those reported in all five regions of Thailand (Nodes 15 and 16), were most at risk of experiencing serious ADRs. Meanwhile, those who were OPD patients (Node 2) and received anti-TB, anti-malaria, or oxaolidinone (Node 5), also reported in the North-East region of Thailand, were likely to experience serious ADR (Node 12) when compared with ADR reports in other regions (Node 11). Fig 5–6 show the CART model’s seriousness in anti-infective-induced ADR prediction.

Fig 5. Classification and Regression Tree (CART) Model to determine the role of demographic factors in the classification of serious ADRs.

Fig 5

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Fig 6. Classification and Regression Tree (CART) Model to determine the role of demographic factors in the classification of the type of ADR.

Fig 6

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We found that factors such as patient type, region, dose frequency, age, and gender significantly influence serious ADRs. The CART model in Fig 5 shows that the reported ADRs in IPD patients and males were most commonly associated with serious ADRs. Reported ADRs showed that people with IPD (Node 1), people who lived in the North-East, North, and South regions of Thailand (Node 4), and people who got doses less than twice a week (Node 9) were more likely associated with serious ADRs. Additionally, individuals aged 60 years and above, 20–39 years, and 40–59 years (Node 12), as well as males (Node 14), were more likely to experience serious ADRs compared to their female counterparts (Node 13). Conversely, OPD patients (Node 2) from the North-East, East, and South regions of Thailand reported more serious ADRs (Node 5) than those from the Central and North regions of Thailand (Node 6). The details of the serious classification and the non-serious are shown in Fig 6.

Discussion

In the present analysis, a total of 82,333 ADR cases, of which 20,692 were serious ADRs (25.13%). The lower rate of serious ADRs may indicate better quality and safety in the patients evaluated or under-reporting of serious ADRs from the pharmacovigilance spontaneous reporting system [36]. A few studies explore the related risk factors for the seriousness of ADRs. The study conducted in South Korea [8] revealed that polypharmacy and liver function tests (AST/ALT ratio) must be monitored carefully within high-risk groups for serious ADRs. Moreover, the study conducted in China [28] found that age, number of medications and illnesses, level of medical institution, history of adverse reactions, seasons, and type and method of medication were all factors that affected serious ADRs. On the other hand, the present study’s finding shows that serious ADRs are statistically associated with region, gender, ethnicity, age, type of patient, history of drug allergy, chronic disease, and dose frequency (p-value < 0.001). This study shows a correlation between the risk of serious ADRs and regions that were statistically associated with the seriousness of ADRs (p-value < 0.001). The most commonly reported serious ADRs were in the south region of Thailand (OR = 1.92, 95% CI = 1.88–1.97) compared to the central region of Thailand. The possible reasons may be due to the longer rainy season in the South of Thailand which causes a higher risk of sickness, which is consistent with the study indicating that season is a factor associated with serious ADRs [28]. The present result shows significant risk factors in the logistic regression analysis, and they were present in the terminal node of the CART model that included gender and history of drug allergy and was also statistically associated with the seriousness of ADRs (p-value = 0.001). ADR reports that patients were males (OR = 1.11, 95% CI = 1.11–1.13) and those with a prior history of drug allergy (OR = 1.22, 95% CI = 1.20–1.24) were more likely to experience serious ADRs compared to females and those without a history of drug allergy, respectively. In contrast with some studies [29], females and those with a prior history of drug allergies are more likely to experience serious ADRs, especially type A adverse drug reactions, and the majority of females weigh less than males [21]. On the other hand, a study [36] revealed that gender did not influence the risk of having an ADR reported as serious. This study has addressed that the risk of having an ADR reported as serious was significantly higher in patients aged 60 and over (OR = 1.42, 95% CI = 1.39–1.46) and patients aged 40–59 years (OR = 1.34, 95% CI = 1.31–1.37) compared to patients aged 0–19 years, which is consistent with several studies [8,27–29,36] indicating that elderly people are at high risk for serious ADRs because of age-related physiological changes and multiple drug regimens for various comorbidities, affecting the pharmacokinetics and pharmacodynamics of many drugs [8,36]. IPD patients most commonly associated with serious ADRs. This finding is in agreement with the result from the CART model shows that ADR reports that IPD patients and males most commonly associated with serious ADRs. The possible reasons may be that the medical characteristics of IPD patients differ from those of OPD patients in terms of disease complications, drug prescriptions, and patient compliance [24]. Furthermore, the risk of having an ADR reported as serious was significantly higher in dermatological (OR = 4.01, 95% CI = 2.58–6.24) compared to alimentary tract and metabolism. The antibiotic group had the largest impact of drug type on serious ADRs. The antibiotic group with the highest impact on serious ADRs was beta-lactam (OR = 1.27, 95% CI = 1.22–1.33), in accordance with the previous studies [8,37,38]. Beta-lactams are the most commonly used antibiotics in clinical practice around the world as first-line treatment for many bacterial infections. However, beta-lactams can cause a variety of hypersensitivity reactions, including anaphylaxis, a life-threatening adverse drug reaction (ADR) [39]. Moreover, reports indicate that these are the primary causes of cutaneous adverse drug reactions, which can vary in severity from mild urticaria and maculopapular exanthema (MPE) to life-threatening severe cutaneous adverse reactions (SCARs) such as Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), drug reaction with eosinophilia and systemic symptoms (DRESS), and acute generalized exanthematous pustulosis [16,40].

The present study has several points of strength. Firstly, this study conducts a retrospective analysis to evaluate serious adverse drug reactions (ADRs) caused by anti-infectives over an extended period in Thailand. Furthermore, this study analyzed a large-scale nationwide database in Thailand using LR and CART analysis methods to investigate risk factors associated with serious ADRs that have an impact on health outcomes and the cost of patient hospital care. Policy makers have the influence and opportunity to use the research evidence to alter or develop effective policies in order to prevent serious ADRs and the health authorities can make decisions more quickly to restrict a drug’s use or pay close attention to high risk group for patient safety.

However, this study is not without limitations. The necessary data in the ADR reports, such as common chronic diseases, were typically reported voluntarily, resulting in many missing values in the demographic data. Moreover, some variables, such as variables related to the behavior of the patient (smoking, alcohol intake, etc.) were not available in the database. These parameters increase oxidative stress (OS), as measured by the Oxidative Stress Index (OSI) [19]. Moreover, various laboratory data on renal function and liver function, which are new risk factors for serious ADRs and play a major role in drug metabolism and also number of concomitant drugs [8], could not be included in this study because they were not available in the database. The spontaneous reporting system for ADRs likely contributes to under-reporting, which may not be the true representative of population. Furthermore, missing data is a limitation due to retrospective studies. Therefore, a prospective study can be conducted in the future to validate the results.

Conclusions

Anti-infective drugs are widely used and cause the most commonly reported serious ADRs in males, elderly patients, and those with a history of drug allergy. They have also spread to almost every region of Thailand. The beta-lactam antibiotics subgroup had a higher percentage of reported serious ADRs due to the anti-infective drug. Serious ADRs have an impact on healthcare outcomes and patient care costs, which poses a challenge for the healthcare system. The findings from this study could contribute to the appropriate use of antibiotics in clinical practice, as well as knowledge for better communication between healthcare practitioners in developing countries where antibiotic resistance is a major national public health issue. Furthermore, developing a reporting system to reduce serious ADR evidence, such as software with electronic prescribing databases or applications that enable efficient detection of ADRs in high-risk groups using CART model, was critical in order to closely monitor and improve patient safety.

Supporting information

S1 Data Set. Data set used in this study.

(CSV)

pone.0318597.s001.csv (20.2MB, csv)

Acknowledgments

The authors graciously acknowledge the Health Product Vigilance Center (HPVC), and the Food and Drug Administration of Thailand (Thai FDA) for providing the data.

Data Availability

The data that support the findings of this study are available as Supporting information.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

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PONE-D-24-43299Epidemiology of Serious Adverse Drug Reactions Due to Anti-Infectives in ThailandPLOS ONE

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for the opportunity to review the manuscript ‘Epidemiology of Serious Adverse Drug Reactions Due to Anti-Infectives in Thailand' submitted for publication in the PlosOne

This is an interesting study analysing ADR reports from the national pharmacovigilance database of Thailand. Logistic regression model and CART model were used to compare serious and non-serious reported ADRs related to anti-infective drugs. The manuscript is clear and well written.

With this stated, I want to make some critical comments with the purpose of stimulating important improvements.

The main comment relates to the representativeness of the data. The author mentioned under-reporting, but an important source of bias is the lack of representativeness due to spontaneous reporting. In general, reported data do not allow conclusions to be drawn about the frequency of ADRs, but about the frequency of reporting, since reporting is not representative of the occurrence in population. This limitation needs to be discussed and all claims such as "males... were more likely to experience serious ADRs", "serious ADRs are more commun..." need to be modified. The title is also not adapted, as this is not a study on the frequency of ADRs in the population.

Authors should explain important differences between regions.

The difference between IPD and OPD patients may be due to differences in reporting in hospital versus community practice. Did ADRs occur in IPD patients during hospitalization or were patients hospitalised due to ADRs?

The authors concluded that “The beta-lactam antibiotics subgroup had a higher proportion of serious ADRs due to the anti-infective drug. The results of this study will enable healthcare professionals to use caution when prescribing to those groups” but such a conclusion should be qualified by the high proportion of beta-lactam prescriptions. Serious ADRs are generally rare, i.e. less than 1 in 10000. Then such reports only occurred with highly used drugs such as beta-lactam. If serious ADRs were proportionally less reported with other antibiotics, this could be due to differences in exposure.

The main originality of this study is the use of the CART model with multivariate logistic regression. The value of the CART model over the regression model or disproportionality analysis should be emphasised.

A minor comment concerns redosing. It is presented as a response to ADRs and not as a cause of ADRs. It is not clear to me why redosing is a response to death (Figure 3).

Reviewer #2: -Title: The title is concise and appropriately conveys the focus of the study. However, adding "A Nationwide Study" might clarify the scope.

- Abstract: The abstract effectively summarizes the study's background, methods, results, and conclusions. Consider rephrasing some sections for clarity, e.g., changing "may be fatal" to "can result in fatal outcomes."

Introduction

- The introduction provides an adequate background on adverse drug reactions (ADRs), their impact, and the importance of studying serious ADRs in Thailand.

- Suggestions: Highlight the gap in research specific to anti-infectives in Thailand earlier to emphasize the study's importance.

Results

- Clarity: Some results could be simplified, as too much numerical detail might overwhelm readers. For example, summarizing the age and region-based findings with more focus on the higher-risk groups could improve readability.

- Figures: Figures 1-6 and tables are informative but would benefit from more descriptive legends, especially in the CART model (Figures 4-6) to help interpret nodes and branches.

Discussion

- Interpretation: The discussion effectively interprets the findings and contextualizes them with existing literature. Expanding further comparison with other ADR studies globally and regionally will strengthen the analysis.

- Limitation: The manuscript mentions missing data and the potential for under-reporting in the ADR reporting system. Consider expanding on these limitations and suggesting specific improvements to address them.

- Practical Implications: Highlighting the implications for healthcare policy and the importance of ADR tracking in Thailand adds value.

This manuscript offers significant insights into ADR epidemiology, particularly for high-risk groups in Thailand. Addressing the minor clarity and structural issues will enhance its impact on readers.

Reviewer #3: 1. When writing the results in the abstract section, it is better to put the lower bound of the confidence interval first instead of vise versa, as a result it will be clearly understandable for readers. For example see the following statement "The most commonly reported serious ADRs were in the South region of Thailand (OR=1.92, 95% CI=1.97-1.88), followed by the North region (OR=1.68, 95% CI= 1.71-1.64) of Thailand."

2. Your introduction section lacks clear justification for why you did the study, in the presence of many other similar studies. Make it more clear and better to emphasize what is the novelty of your study.

3. What was your base line to classify age groups in that way?

4. In your table four, There are variables which are significant as per the confidence interval but are missed in your significant variables list. please check and include it.

5. You mentioned in the discussion section that you used retrospective study which a "strength" of your study. However with the possible attrition rates and missed data related to retrospective study, I recommend if you could mention it as a "limitation" to further recommend prospective studies.

**********

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Reviewer #1: Yes:  Patrick MAISON

Reviewer #2: No

Reviewer #3: No

**********

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PLoS One. 2025 Feb 25;20(2):e0318597. doi: 10.1371/journal.pone.0318597.r003

Author response to Decision Letter 1

26 Dec 2024

Response to Reviewer

Dear Editor,

We appreciate you and the reviewers taking the time to review our paper and provide valuable feedback. Your valuable and insightful comments prompted possible improvements to the current version. The authors carefully considered the comments and did our best to address each one. We hope that the manuscript, after careful revisions, meets your high standards. The authors welcome any additional constructive feedback.

The responses are listed below, point by point. All modifications to the manuscript have been highlighted in yellow.

Sincerely,

Dr. Khurram,

Response to Reviewer 1

Reviewer #1: Thank you for the opportunity to review the manuscript ‘Epidemiology of Serious Adverse Drug Reactions Due to Anti-Infectives in Thailand' submitted for publication in the PlosOne.

This is an interesting study analyzing ADR reports from the national pharmacovigilance database of Thailand. Logistic regression model and CART model were used to compare serious and non-serious reported ADRs related to anti-infective drugs. The manuscript is clear and well written.

With this stated, I want to make some critical comments with the purpose of stimulating important improvements.

Thank you very much for giving a positive and constructive response. We try our best to resolve the concerns and suggestions to improve the quality of our manuscript.

The main comment relates to the representativeness of the data. The author mentioned under-reporting, but an important source of bias is the lack of representativeness due to spontaneous reporting. In general, reported data do not allow conclusions to be drawn about the frequency of ADRs, but about the frequency of reporting, since reporting is not representative of the occurrence in population. This limitation needs to be discussed and all claims such as "males... were more likely to experience serious ADRs", "serious ADRs are more common..." need to be modified. The title is also not adapted, as this is not a study on the frequency of ADRs in the population.

Thank you very much for pointing this out. We revised the whole manuscript and changed the tone of many sentences. A few of these are as follows:

> [Results, Page 7, Line 168-171], [Discussion, Page 9, Lines 216-218]:

“From the reported ADRs, males (OR = 1.11, 95% CI = 1.11-1.13) and those with a prior history of drug allergy (OR = 1.22, 95% CI = 1.20-1.24) experienced more serious ADRs compared to females and those without a history of drug allergy, respectively.”.

>[Abstract, Page2, Line 40-42]: “Reported ADRs revealed that patients were males (OR = 1.11, 95% CI = 1.11-1.13) and those with a prior history of drug allergy (OR = 1.22, 95% CI = 1.20-1.24) were more likely to experience serious ADRs.”

> [Results, Page 8, Lines 189-190]: “The CART model shows that reported ADRs in IPD patients and males were most commonly associated with serious ADRs.”

We have added the limitations at the end of the discussion as follows.

“The spontaneous reporting system for ADRs likely contributes to under-reporting, which may not be the true representative of the population. Furthermore, missing data is a limitation due to retrospective studies. Therefore, a prospective study can be conducted in the future to validate the results.”

We have revised the title as follows.

“Epidemiology of Reported Serious Adverse Drug Reactions Due to Anti-Infectives using Nationwide Database of Thailand”

Authors should explain important differences between regions.

We have revised the manuscript by adding the explanation of important differences between regions as follows:

Thailand is divided into different regions based on geographical locations by local administration. Many researchers used five regions grouping as they have different environments and cultural behaviors for example:

Chokngamwong, R., & Chiu, L. S. (2008). Thailand daily rainfall and comparison with TRMM products. Journal of hydrometeorology, 9(2), 256-266.

Hitokoto, H., Takahashi, Y., & Kaewpijit, J. (2014). Happiness in Thailand: Variation between urban and rural regions. Psychologia, 57(4), 229-244.

Waqas, M., Naseem, A., Humphries, U. W., Hlaing, P. T., Shoaib, M., & Hashim, S. (2024). A comprehensive review of the impacts of climate change on agriculture in Thailand. Farming System, 100114.

[Discussion, Page 8-9, Lines 209-213]:

“The most commonly reported serious ADRs were in the south region of Thailand (OR = 1.92, 95% CI = 1.88-1.97) compared to the central region of Thailand. The possible reasons may be due to the longer rainy season in the South of Thailand which causes a higher risk of sickness, which is consistent with the study indicating that season is a factor associated with serious ADRs [28].”

The difference between IPD and OPD patients may be due to differences in reporting in hospital versus community practice. Did ADRs occur in IPD patients during hospitalization or were patients hospitalized due to ADRs?

Thank you for pointing out this concern. We already added the word “reported ADRs” and also mentioned the limitations to justify your concern.

We deleted the sentence that serious ADRs are more common in IPD patients than OPD patients.

The authors concluded that “The beta-lactam antibiotics subgroup had a higher proportion of serious ADRs due to the anti-infective drug. The results of this study will enable healthcare professionals to use caution when prescribing to those groups” but such a conclusion should be qualified by the high proportion of beta-lactam prescriptions. Serious ADRs are generally rare, i.e. less than 1 in 10000. Then such reports only occurred with highly used drugs such as beta-lactam. If serious ADRs were proportionally less reported with other antibiotics, this could be due to differences in exposure.

We agree with the reviewer that beta-lactam antibiotics were highly prescribed and that’s why reported ADRs were higher. Your suggestion is valuable if we said that the ADRs were higher due to beta-lactam but instead, we compared serious with non-serious ADRs. We can see that the percentage of serious ADRs was higher than that of non-serious ADRs. So it is not just about the number of users but the percentage of people who had serious ADRs in all reported ADRs. It can be seen from Table 2 that from all reported ADRs 42.1% ADRs were non-serious while 57.9% ADRs were serious. Complementary, Cephalosporin had 79.8% reported non-serious ADRs as compared to serious ADRs. So we can say that from reported ADRs related to Cephalosporin, the percentage of non-serious ADRs is much higher than serious ADRs.

To moderate the concern due to reported ADRs, we have written it as:

“The beta-lactam antibiotics subgroup had a higher percentage of reported serious ADRs due to the anti-infective drug.”

Instead of “The beta-lactam antibiotics subgroup had a higher proportion of serious ADRs due to the anti-infective drug. The results of this study will enable healthcare professionals to use caution when prescribing to those groups”.

The main originality of this study is the use of the CART model with multivariate logistic regression. The value of the CART model over the regression model or disproportionality analysis should be emphasized.

We are grateful for the reviewer's concern. We have focused on the values of the CART model as suggested by revising the explanation of results. We have added the following line in the conclusion.

“Furthermore, developing a reporting system to reduce serious ADR evidence, such as software with electronic prescribing databases or applications that enable efficient detection of ADRs in high-risk groups using CART model, was critical in order to closely monitor and improve patient safety.”

A minor comment concerns redosing. It is presented as a response to ADRs and not as a cause of ADRs. It is not clear to me why redosing is a response to death (Figure 3).

Redosing might be a factor that affects the result of ADRs in a worse situation like death. To make the caption of each figure to be clearer, we have revised it accordingly as follows.

[Page 22, Lines 410]: “Fig 3. Association between Redosing and Type of Anti-Infective-Induced-ADRs”

[Page 15, Lines 381]: “S3 Fig. Association between Redosing and Type of Anti-Infective-Induced-ADRs”

Response to Reviewer 2

Reviewer #2: -Title: The title is concise and appropriately conveys the focus of the study. However, adding "A Nationwide Study" might clarify the scope.

We have revised the title as follows.

“Epidemiology of Reported Serious Adverse Drug Reactions Due to Anti-Infectives using Nationwide Database of Thailand”

- Abstract: The abstract effectively summarizes the study's background, methods, results, and conclusions. Consider rephrasing some sections for clarity, e.g., changing "may be fatal" to "can result in fatal outcomes."

The term “may be fatal” is altered to “can result in fatal outcomes” as follows:

[Page 2, Lines 26]: “Serious Adverse Drug Reactions (ADRs) can cause a longer stay, which can result in fatal outcomes”

[Introduction, Page 3, Lines 57-58]: “Serious ADRs can cause a longer stay, which can result in fatal outcomes”

Introduction

- The introduction provides an adequate background on adverse drug reactions (ADRs), their impact, and the importance of studying serious ADRs in Thailand.

We thank you for the positive response.

- Suggestions: Highlight the gap in research specific to anti-infectives in Thailand earlier to emphasize the study's importance.

We presented a gap in research that the previous research applied a nationwide database in Thailand to investigate the factors associated with serious ADRs due to the Dimenhydrinate drug, but anti-infective drugs have been limited. [Page 3, Line 93-96]

[Introduction, Page 3-4, Lines 74-77]: “The previous research used Thai Vigibase to study the factors associated with serious outcomes of ADRs caused only by Dimenhydrinate, which are of limited scope. Therefore, the purpose of this study was to analyze a large-scale nationwide database in Thailand to investigate the predisposing factors associated with serious ADRs and explore drug exposure to ADRs and their pattern.”

Results

- Clarity: Some results could be simplified, as too much numerical detail might overwhelm readers. For example, summarizing the age and region-based findings with more focus on the higher-risk groups could improve readability.

In the result section, explaining other important variables, such as the Anatomical Therapeutic Drug Class (ATC) and anti-infective drug type, is considered important information to explain the culprit drug, helping to explain drug causes of serious ADRs. Moreover, this result links to the CART model result, and connections to other research are explained in the discussion section.

- Figures: Figures 1-6 and tables are informative but would benefit from more descriptive legends, especially in the CART model (Figures 4-6) to help interpret nodes and branches.

Thank you for the suggestion. If we add more details in the legend, then the legend will be unnecessary larger and make confusion for the reader and occupy more space. To address your concern, we have added the details of nodes and branches in the results section.

Discussion

- Interpretation: The discussion effectively interprets the findings and contextualizes them with existing literature. Expanding further comparison with other ADR studies globally and regionally will strengthen the analysis.

We explained further comparisons with other ADR studies globally and regionally as follows: [Page 7, Lines 219-226]

[Discussion, Page 8, Lines 201-208]: “A few studies explore the related risk factors for the seriousness of ADRs. The study conducted in South Korea [8] revealed that polypharmacy and liver function tests (AST/ALT ratio) must be monitored carefully within high-risk groups for serious ADRs. Moreover, the study conducted in China [28] found that age, number of medications and illnesses, level of medical institution, history of adverse reactions, seasons, and type and method of medication were all factors that affected serious ADRs. On the other hand, the present study's finding shows that serious ADRs are statistically associated with region, gender, ethnicity, age, type of patient, history of drug allergy, chronic disease, and dose frequency (p-value < 0.001).”

- Limitation: The manuscript mentions missing data and the potential for under-reporting in the ADR reporting system. Consider expanding on these limitations and suggesting specific improvements to address them.

We explained more on under-reporting and suggestions as follows: [Page 8, Lines 260-263]

[Discussion, Page 10, Lines 254-256]: “The spontaneous reporting system for ADRs likely contributes to under-reporting, which may not be the true representative of population. Furthermore, missing data is a limitation due to retrospective studies. Therefore, a prospective study can be conducted in the future to validate the results.”

- Practical Implications: Highlighting the implications for healthcare policy and the importance of ADR tracking in Thailand adds value.

We explained more on practical implications as follows:

[Discussion, Page 10, Lines 243-247]: “Furthermore, this study analyzed a large-scale nationwide database in Thailand using LR and CART analysis methods to investigate risk factors associated with serious ADRs that have an impact on health outcomes and the cost of patient hospital care. Policy makers have the influence and opportunity to use the research evidence to alter or develop effective policies in order to prevent serious ADRs and the health authorities can make decisions more quickly to restrict a drug’s use or pay close attention to high risk group for patient safety.”

This manuscript offers significant insights into ADR epidemiology, particularly for high-risk groups in Thailand. Addressing the minor clarity and structural issues will enhance its impact on readers.

Thank you very much for your positive comments.

Response to Reviewer 3

Reviewer #3: 1. When writing the results in the abstract section, it is better to put the lower bound of the confidence interval first instead of vise versa, as a result it will be clearly understandable for readers. For example see the following statement "The most commonly reported serious ADRs were in the South region of Thailand (OR=1.92, 95% CI=1.97-1.88), followed by the North region (OR=1.68, 95% CI= 1.71-1.64) of Thailand."

We have revised all of the 95%CI values in the manuscript by putting lower bound first as suggested.

2. Your introduction section lacks clear justification for why you did the study, in the presence of many other similar studies. Make it more clear and better to emphasize what is the novelty of your study.

We presented a gap in research that the previous resear

Attachment

Submitted filename: Response to Reviewers.docx

pone.0318597.s003.docx (33.9KB, docx)

Decision Letter 1

Obed Kwabena Offe Amponsah

20 Jan 2025

<p>Epidemiology of Reported Serious Adverse Drug Reactions Due to Anti-Infectives Using Nationwide Database of Thailand

PONE-D-24-43299R1

Dear Dr. Khuram,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Obed Kwabena Offe Amponsah, PharmD, Ph.D.

Academic Editor

PLOS ONE

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Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #2: (No Response)

Reviewer #3: (No Response)

**********

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If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .

Reviewer #1: Yes:  Patrick Maison

Reviewer #2: No

Reviewer #3: No

**********

Acceptance letter

Obed Amponsah

PONE-D-24-43299R1

PLOS ONE

Dear Dr. Khurram,

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