Data Mining in Pharmacoepidemiological Databases

BackgroundAlthough filgotinib, a selective Janus kinase 1 inhibitor, has been increasingly applied in the treatment of inflammatory diseases, its comprehensive safety profile remains insufficiently characterized. Using data from the FAERS database covering Q1 2014 to Q2 2024, this study attempts to analyze adverse event signals linked to filgotinib and provide guidance for the safe and sensible clinical usage of filgotinib.MethodsFrom Q1 2014 to Q2 2024, information on adverse drug events (ADEs) associated with filgotinib was gathered. The reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) were among the signal detection methods that were employed for analysis following data normalization.ResultsFilgotinib was shown to be the main suspected medication in ADE reports, exposing 103 preferred terms (PTs) in 17 system organ classes (SOCs). Infections, gastrointestinal disorders, and musculoskeletal and connective tissue disorders were the most commonly reported adverse effects. Additionally, atrial fibrillation, alopecia, elevated serum creatinine, blood creatinine increased, pulmonary embolism, epididymitis, respiratory failure, and osteopenia were identified as potential disproportionate reporting signals for filgotinib, although these were not listed in the official drug label. Notable significant signals included large intestine erosion (ROR 2186.05, 95%CI(ROR): 1015.94–4703.86, PRR 2176.18, 95%CI(PRR): 1014.64–4667.42), mesenteric arterial occlusion (ROR 1832.17, 95%CI(ROR): 897.68–3739.48, PRR 1822.71, 95%CI(PRR): 896.17–3707.20), repetitive strain injury (ROR 1149.27, 95%CI(ROR): 363.16–3637.01, PRR 1147.05, 95%CI(PRR): 363.24–3622.15), oligoarthritis (ROR 755.02, 95%CI(ROR): 310.74–1834.54, PRR 752.59, 95%CI(PRR): 310.60–1823.51), and periostitis (ROR 676.03, 95%CI(ROR): 319.36–1431.06, PRR 672.98, 95%CI(PRR): 318.97–1419.87). The subgroup analysis identified obvious sex and age-specific trends in filgotinib-related adverse reactions, emphasizing a higher risk of renal disorders in females, a preponderance of gastrointestinal events in males, and age-dependent trends involving mesenteric occlusion, increased serum creatinine, and immunoglobulin reduction.ConclusionWhile filgotinib demonstrates therapeutic efficacy, it is associated with a range of potential adverse events, underscoring the need for vigilant clinical monitoring. Particular attention should be given to gastrointestinal, cardiovascular, respiratory, and metabolic complications.

Central nervous system adverse events (AEs) occur when oxycodone is used in combination with benzodiazepines, antidepressants and anticonvulsants. There have been no reports of central nervous system AEs with oxycodone alone or in combination with oxycodone. Based on USA Food and Drug Administration Adverse Event Reporting System (FAERS) data, this study aims to explore the risk signals of central nervous system AEs with oxycodone alone or in combination with benzodiazepines, antidepressants and anticonvulsants, and to provide a reference for the safe and rational use of this drug. Extracted AEs data from the FAERS for oxycodone alone and in combination with benzodiazepines, antidepressants, and anticonvulsants from Q1 2004 to Q2 2021. The risk signal mining analysis of AEs was performed using the proportional imbalance method and Bayesian method. Number of reports ≥3 and lower 95% CI limit of reporting odds ratio (ROR)>1; number of reports ≥3, proportional reporting ratio (PRR)≥2 and χ2≥4; lower information components (IC) lower 95% CI limit (IC025)>0; empirical Bayes geometric mean (EBGM) lower 95% CI limit (EBGM05)>2, and N>0 were defined as positive signals. A total of 5 793 reports of central nervous system AEs with oxycodone alone were tapped, and 366, 622, and 740 reports of combined benzodiazepines, antidepressants, and anticonvulsants, respectively. Consumers and physicians were the main reporting population. The age distribution of oxycodone alone was mainly from 61 to 80 years old. The age distribution of oxycodone in combination with related drugs was mainly from 46 to 60 years old. The risk of AEs was greater in women than in men, and the United States was the predominant reporting country. Oxycodone alone was strongly associated with myoclonus [ROR=2.92, 95% CI 2.28 to 3.76); PRR=2.92, χ2(77.49); IC=1.52, IC025(0.65); EBGM=2.89, EBGM05(2.33)], delirium [ROR=4.69, 95% CI 4.24 to 5.21; PRR=4.66, χ2(1 052.64); IC=2.17, IC025(1.81); EBGM=4.50, EBGM05 (4.13)], mental disorder [ROR=2.95, 95% CI 2.53 to 3.44; PRR=2.94, χ2(206.93); IC=1.56, IC025(0.96); EBGM=2.95, EBGM05(2.58)], and acute central respiratory depression [ROR=2.87, 95% CI 2.68 to 3.08); PRR=2.82, χ2(971.62); IC=1.52, IC025(1.33), EBGM=2.87, EBGM05 (2.76)]. Combination of benzodiazepines was most strongly associated with mental disorder [ROR=10.08, 95% CI 9.38 to 10.78; PRR=9.90, χ2(64.06); IC=3.33, IC025 (1.65); EBGM=10.08, EBGM05(5.61)], and tremor [ROR=3.09, 95% CI 2.76 to 3.42); PRR=3.08, χ2(48.93); IC=1.63, IC025 (1.17); EBGM=3.09, EBGM05(2.34)]. Combination of antidepressants was most strongly associated with delirium [ROR=13.23, 95% CI 12.23 to 14.23; PRR=12.87, χ2(43.86); IC=3.69, IC025(1.36); EBGM=12.23, EBGM05 (5.32)] and somnolence [ROR=6.74, 95% CI 6.15 to 7.33); PRR=6.73, χ2(53.42); IC=2.75, IC025(1.52); EBGM=6.73, EBGM05(4.10)]. Combination of anticonvulsants was most strongly associated with myoclonus [ROR=17.89, 95% CI 17.46 to 18.32; PRR=17.72, χ2(971.39); IC=4.16, IC025(2.70); EBGM=17.89, EBGM05(12.46)] and delirium [ROR=4.86, 95% CI 4.45 to 5.27); PRR=4.82, χ2(69.49); IC=2.28, IC025 (1.51); EBGM=4.86, EBGM05(3.44)]. Based on pharmacovigilance studies of the FAERS database, clinical medication monitoring of oxycodone alone and in combination with benzodiazepines, antidepressants, and anticonvulsants should be strengthened to be alert to the occurrence of central nervous system-related AEs.

BackgroundAn increasing number of clinical studies have highlighted the use of atezolizumab in tumor immunotherapy. However, There is still a lack of comprehensive research on its associated adverse events (AEs). To improve our understanding of its toxicological profile and to provide valuable clinical insights regarding into the effectiveness of immunotherapy, this study utilized data from the US Food and Drug Administration Adverse Event Reporting System (FAERS) to conduct a retrospective analysis of AEs linked to atezolizumab.MethodsWe extracted the reports of AEs related to atezolizumab from the FAERS database from the first quarter of 2004 to the first quarter of 2024. We quantified them using the reporting odds ratio (ROR) and proportional reporting ratio (PRR), along with chi-square value (χ²), and conducted systematic classification of the AE signal mining results through SAS 9.4 software.ResultsA total of 19,563 valid reports were incorporated, involving 20 distinct system organ class categories. The AEs related to atezolizumab, reported at the preferred term level, mainly encompassed anemia [ROR 2.33, 95% confidence interval (CI) lower limit 2.09, PRR 2.31, χ² 255.977], febrile neutropenia (ROR 2.81, 95% CI lower limit 2.50, PRR 2.79, χ² 333.586), neutrophil count decreased (ROR 2.14, 95% CI lower limit 1.89, PRR 2.13, χ² 150.688), white blood cell count decreased (ROR 2.35, 95% CI lower limit 2.03, PRR 2.34, χ² 136.673), sepsis (ROR 2.21, 95% CI lower limit 1.91, PRR 2.20, χ² 117.741), alanine aminotransferase increased (ALT) (ROR 2.86, 95% CI lower limit 2.44, PRR 2.85, χ² 180.031), and aspartate aminotransferase increased (AST) (ROR 2.79, 95% CI lower limit 2.38, PRR 2.78, χ² 170.955).ConclusionsApart from various degrees of hepatotoxicity, such as increased ALT and AST, the immune-related hematological toxicity of atezolizumab should also be noted. In clinical practice, healthcare providers should always be vigilant for the occurrence of such medication-related AEs and take measures to enhance the safety of clinical medication use.

Comparative safety profiles of bispecific T-cell engagers and CAR-T therapies: Real-world insights from the FDA adverse event reporting system database

Safety information regarding drug use during pregnancy is insufficient. The present study aimed to establish an optimal signal detection method to identify adverse drug reactions in pregnant women and to evaluate information in the Japanese Adverse Drug Event Report (JADER) database between April 2004 and November 2014. We identified reports on pregnant women using the Standardised MedDRA Queries. We calculated the proportional reporting ratio (PRR) and reporting odds ratio (ROR) of the risk factors for the two known risks of antithyroid drugs and methimazole (MMI) embryopathy, and ritodrine and fetal/infant cardiovascular events. The PRR and ROR values differed between all reports in the JADER database and those on pregnant women, affecting whether signal detection criteria were met. Therefore we considered that reports on pregnant women should be used when risks associated with pregnancy were determined using signal detection. Analyses of MMI embryopathy revealed MMI signals [PRR, 159.7; ROR, 669.9; 95% confidence interval (CI), 282.4-1588.7] but no propylthiouracil signals (PRR, 1.98; ROR, 2.0; 95%CI, 0.3-15.4). These findings were consistent with those of reported risks. Analyses of fetal/infant cardiovascular events revealed ritodrine signals (PRR, 2.1; ROR, 2.1; 95%CI, 1.4-3.3). These findings were also consistent with reported risks. Mining the JADER database was helpful for analyzing adverse drug reactions in pregnant women.

Nifedipine, a dihydropyridine calcium channel blocker, is widely used in the management of hypertension and as a tocolytic agent to delay preterm labor, including in pregnant women. However, its safety profile, particularly in pregnant populations, remains insufficiently characterized. This study aimed to evaluate adverse event (AE) signals associated with nifedipine use, with a specific focus on pregnancy-related outcomes. Nifedipine-related AEs reported in U.S. Food and Drug Administration Adverse Event Reporting System database (Q1 2004–Q4 2024) were analyzed. Disproportionality analysis was conducted using 4 established signal detection methods: reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian Confidence Propagation Neural Network, and Multi-item Gamma Poisson Shrinker. Pregnancy-related reports were identified using Standardized MedDRA Queries, and subgroup analyses were conducted for pregnant women. In the overall population, significant signals at the System Organ Class level were observed for pregnancy-related conditions, vascular disorders, and cardiac disorders. The strongest prominent preferred term signal was gingival hypertrophy (n = 52; ROR = 100.55, PRR = 100.23, information component [IC] = 6.61, empirical Bayesian geometric mean [EBGM] = 97.42). Among pregnant women, prominent signals at the System Organ Class level included vascular disorders, respiratory disorders, and cardiac disorders. The strongest preferred term signal was acute pulmonary edema (n = 27; ROR = 67.23, PRR = 66.70, IC = 5.87, EBGM = 58.29), followed by cardiogenic shock (n = 11; ROR = 41.80, PRR = 41.67, IC = 5.26, EBGM = 38.25), pulmonary edema (n = 51; ROR = 38.57, PRR = 38.00, IC = 5.14, EBGM = 35.15), and hypoxia (n = 28; ROR = 20.62, PRR = 20.46, IC = 4.29, EBGM = 19.62). Several unexpected pregnancy-related AEs were also detected, including eclampsia, fetal distress, placental disorders, and intrauterine growth restriction. This study identified unexpected AE signals associated with nifedipine use during pregnancy. The findings offer valuable insights to guide clinical decision-making and promote safer use of nifedipine in pregnant populations.

Deucravacitinib, a selective inhibitor of TYK2 kinase, has been recently approved for the treatment of moderate to severe plaque psoriasis. Although the safety of deucravacitinib has been observed in clinical trials, its safety in the real world remains to be fully understood. The purpose of this study was to analyze post-marketing adverse events (AEs) associated with deucravacitinib using data from the Food and Drug Administration Adverse Event Reporting System (FAERS) to better understand its safety in real-world conditions. This study performed a retrospective analysis of AEs associated with deucravacitinib from the FAERS database, spanning from the third quarter of 2022 to the second quarter of 2024. AEs were classified according to the Medical Dictionary for Regulatory Activities (MedDRA, Version 27.0). Disproportionality analysis was conducted using several statistical methods, including the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Multi-Item Gamma Poisson Shrinker, and Bayesian Confidence Propagation Neural Network. Additionally, time-to-onset analyses and sensitivity analyses were performed to provide a comprehensive assessment. AE reports from 1573 individuals were analyzed, revealing a total of 2895 AEs. Most of these events occurred within the first month of treatment. The primary AEs were associated with skin and subcutaneous tissue disorders, as well as infections and infestations. The study confirmed several known common AEs, including acne (n = 172, ROR 75, PRR 70.61, EBGM 69.14, IC 6.11), folliculitis (n = 51, ROR 62.45, PRR 61.37, EBGM 60.25, IC 5.91), and herpes zoster (n = 18, ROR 6.46, PRR 6.43, EBGM 6.42, IC 2.68), and identified some unexpected AEs such as urticaria (n = 36, ROR, PRR 5.27, EBGM 5.27, IC 2.4), skin burning sensation (n = 42, ROR 21.84, PRR 21.54, EBGM 21.41, IC 4.42), and myalgia (n = 26, ROR 3.93, PRR 3.9, EBGM 3.9, IC 1.96). Our study confirms the known AEs associated with deucravacitinib and identifies several potential AEs. These findings provide preliminary safety data for the practical use of deucravacitinib.

Background Tazemetostat is an oral inhibitor of enhancer of zeste homolog 2 (EZH2) and is used for the treatment of epithelioid sarcoma (ES) and follicular lymphoma (FL). In this study, we investigated the adverse events (AEs) of tazemetostat based on real data from the U.S Food and Drug Administration(FDA) Adverse Event Reporting System (FAERS). Methods To quantify the signals of AEs associated with tazemetostat, we employed disproportionality analyze, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) algorithms. Results A total of 7,133,678 reports of AEs were collected from the FAERS database, of which 1,110 reports were identified with tazemetostat as the “primary suspect (PS)”. A total of 32 significant disproportionality preferred terms(PTs) conforming to the four algorithms were simultaneously retained. There were multiple unexpected AEs caused by tazemetostat that were not mentioned in the label yet, including pleural effusion (ROR = 3.84, PRR = 3.83, IC = 3.83, IBGM = 1.94), lymphadenopathy (ROR = 3.88, PRR = 3.88, IC = 3.87, IBGM = 1.95) and taste disorder(ROR = 20.48, PRR = 20.23, IC = 20.16, IBGM = 4.33). Additionally, the majority of tazemetostat-associated AEs occurred within the first month of treatment initiation (n = 126, 49.8%). Conclusion Clinicians need to monitor safety for tazemetostat during the first 30 days and pay more attention to new AE signals.

P.2.e.001 - The efficacy of vortioxetine in a major depression case and follow-up of pruritus adverse effect

The purpose of this study is to explore and analyze the FDA Adverse Event Reporting System (FAERS) database to identify drug adverse reaction signals associated with angioedema. The findings aim to provide valuable insights for clinical drug safety considerations. The Open Vigil 2.1 data platform was utilized to collect adverse event reports related to angioedema from the first quarter of 2004 to the fourth quarter of 2023. The reporting odds ratio (ROR) and proportional reporting ratio (PRR) were employed as disproportionality measures to detect adverse reaction signals Sof drugs associated with angioedema. A total of 38,921 reports were retrieved, with the majority being reported by healthcare professionals. The analysis included predominantly adult patients (≥18years of age), with slightly higher representation of females compared to males. Among the top 30 drugs associated with the occurrence of angioedema, 24 drugs showed positive signals in the risk analysis. Based on the individual drug reporting odds ratio (95% confidence interval) as a measure of risk signal strength, the top five drugs are as follows: lisinopril [ROR (95% CI): 46.43 (42.59-50.62)], enalapril [ROR (95% CI): 43.51 (39.88-47.46)], perindopril [ROR (95% CI): 31.17 (27.5-35.32)], alteplase [ROR (95% CI): 29.3 (26.95-31.85)], ramipril [ROR (95% CI): 20.93 (19.66-22.28)]. After categorizing the drugs, the strongest positive signal was observed in the antithrombotic agents [ROR (95% CI): 22.53 (21.16-23.99)], following that, cardiovascular drugs [ROR (95% CI): 9.17 (8.87-9.48)], antibiotics [ROR (95% CI): 6.42 (5.91-6.96)], immunosuppressors [ROR (95% CI): 5.95 (5.55-6.39)], anti-inflammatory analgesics [ROR (95% CI): 4.65 (4.45-4.86)], antiallergic drugs [ROR (95% CI): 4.47 (3.99-5)], antiasthmatics [ROR (95% CI): 2.49 (2.14-2.89)], blood sugar control drugs [ROR (95% CI): 1.65 (1.38-1.97)], and digestive system drugs [ROR (95% CI): 1.59 (1.45-1.74)] exhibited progressively decreasing ROR values. Many medications are associated with a high risk of angioedema. These medications play a crucial and potentially preventable role in controlling the occurrence of angioedema. It is essential to consider the risk level of drug-induced angioedema in clinical practice to optimize medication therapy.

PDG97 VEMURAFENIB INDUCED DRUG REACTION WITH EOSINOPHILIA AND SYSTEMIC SYMPTOMS (DRESS): A DISPROPORTIONALITY ANALYSIS IN USFDA ADVERSE EVENT REPORTING SYSTEM DATABASE

BackgroundThis study aims to investigate adverse drug reaction signals associated with coagulopathies through data mining using the Adverse Event Reporting System (FAERS) of the US Food and Drug Administration. Prompt identification of high-risk drugs provides a valuable basis for enhancing clinical drug safety.MethodsThe adverse event reports related to coagulopathies from Q1 2004 to Q2 2024 were extracted from the ASCII data packages in FAERS. The reporting odds ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN) were used to identify adverse drug reaction signals associated with coagulopathies.ResultsDuring the reporting period, 40,545 reports were retrieved, with a slightly higher proportion of females than males. Among the top 30 drugs associated with the occurrence of coagulopathies, 24 drugs exhibited positive signals in risk analysis. Based on the individual drug reporting odds ratio (95% confidence interval) as a measure of risk signal strength, the top five drugs are as follows: gemcitabine [ROR (95% CI):16.87 (15.83–17.98)], busulfan [ROR (95% CI):15.51 (13.69–17.58)], anti-thymocyte globulin [ROR (95% CI):15.49 (13.49–17.78)], tacrolimus [ROR (95% CI):12.7 (11.57–13.95)], etonogestrel and ethinylestradiol vaginal ring [ROR (95% CI):11.88 (10.95–12.89)]. After categorizing the drugs, the strongest risk signal is sex hormones and modulators of the genital system [ROR (95% CI):11.88 (10.95–12.89)], followed by analgesics [ROR (95%CI): 6.73 (6.38–7.1)], immunosuppressants [ROR (95% CI):3.91 (3.76–4.05)], antineoplastic agents [ROR (95% CI):3.33 (3.22–3.45)], corticosteroids for systemic use [ROR (95% CI): 2.94 (2.73–3.18)], antiepileptics [ROR (95% CI):1.93 (1.71–2.18)], drugs used in diabetes [ROR (95% CI):1.5 (1.34–1.67)], antibacterials for systemic use [ROR (95% CI):1.46 (1.28–1.68)].ConclusionOur findings indicate that multiple drugs are associated with an increased risk of coagulopathies. From the pharmacovigilance perspective, proactive analysis of these drugs aids in clinical monitoring and enhances risk identification of coagulopathies.

To describe and compare the reporting patterns and signal strengths of male sexual dysfunction associated with six commonly prescribed SSRIs in the FDA Adverse Event Reporting System. Adverse event data for six representative SSRIs, fluoxetine, paroxetine, sertraline, fluvoxamine, citalopram, and escitalopram, were retrieved from the FAERS database, spanning from the first quarter of 2004 to the first quarter of 2025. Disproportionality analysis was conducted using both the reporting odds ratio (ROR) and proportional reporting ratio (PRR) to identify potential signals of adverse drug events associated with these medications. We analyzed 6,631,746 adverse drug event reports associated with SSRIs and detected significant disproportionality signals indicative of male sexual dysfunction in patients with depression. Across all SSRIs, erectile dysfunction was the most commonly reported adverse event [fluoxetine (ROR: 4.97, 95%CI: 4.25-5.82), paroxetine (ROR: 3.99, 95%CI: 3.53-4.5), sertraline (ROR: 6.11, 95%CI: 5.53-6.75), fluvoxamine (ROR: 1.08, 95%CI: 0.35-3.36), citalopram (ROR: 7.7, 95%CI: 6.81-8.69), and escitalopram (ROR: 7.93, 95%CI: 6.99-8.99)], followed by sexual dysfunction [fluoxetine (ROR: 11.94, 95%CI: 10.01-14.23), paroxetine (ROR: 11.39, 95%CI: 10.05-12.91), sertraline (ROR: 13.34, 95%CI: 11.86-15.01), fluvoxamine (ROR: 9.64, 95%CI: 5.01-18.56), citalopram (ROR: 15.09, 95%CI: 12.98-17.54), and escitalopram (ROR: 16.42, 95%CI: 14.11-19.12)]. This FAERS analysis detected significant disproportionality signals for male sexual dysfunction across SSRIs. Signal variation reflects reporting differences, not comparative risk, due to database limitations. These findings highlight the need for clinical vigilance and further investigation.

A well-known problem in pharmacotherapy is an increased risk of adverse drug reactions (ADRs) in older as compared to younger patients. The Russian pharmacovigilance database includes a significant number of spontaneous reports of suspected ADRs in patients aged 65 and older. An increase in ADRs reporting makes it difficult to identify potential safety signals based on qualitative approaches only, which necessitates the use of statistical methods for signal detection based on disproportionality. The aim of the study was to assess the applicability of quantitative methods for signal detection and analysis of ADR risks in the elderly using the Russian spontaneous report database. Materials and methods: the study covered the reports on patients 65 years of age and older, which were submitted to the spontaneous report database from January 2008 until June 2018. The procedure recommended by the European Medicines Agency was used to identify potential statistical safety signals which were determined based on the following criteria: Reporting Odds Ratio, ROR—lower bound of the 95% confidence interval >1, number of cases ≥2; Proportional Reporting Ratio, PRR ≥ 2, Chi-square value χ 2 ≥ 4, number of cases ≥3, lower bound of the 95% confidence interval >1, number of cases ≥3. Results: 2231 potential statistical signals were identified. Of these, the vast majority of combinations of suspected drugs and ADRs were associated with known drug risks, and were not new safety signals for these drugs. The largest proportion of statistical signals was attributed to the following pharmacological groups: antiplatelet agents, cephalosporins, non-steroidal anti-inflammatory drugs, fluoroquinolones, angiotensin-converting enzyme inhibitors, metabolic agents, and indirect anticoagulants. Conclusion: the results obtained indicate the applicability and effectiveness of statistical methods based on disproportionality of reporting for the analysis of the Russian spontaneous report database in order to identify potential drug safety issues.

Objective: We conducted a pharmacovigilance analysis of mesalazine-related adverse events (AEs) in the realworld using the America's FAERS and Japan's JADER databases. Methods: We extracted reports of mesalazine-associated AEs from FAERS and JADER spanning the first quarter of 2004 to the third quarter of 2024. In the disproportionality analysis, we applied the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the multi-item gamma-Poisson shrinker (MGPS) algorithms for signal detection. The time to onset of AEs was assessed using Kaplan-Meier curves and the Weibull distribution test. Results: The analysis encompassed 40,265 AEs reports from FAERS and 4,330 from JADER. Mesalazine-related preferred terms (PTs) mapped to 27 System Organ Classes (SOCs) in FAERS and 25 SOCs in JADER. Gastrointestinal disorders emerged as the most frequently reported SOC in both databases. Three SOCs demonstrated significant signal strength across both datasets: (1) gastrointestinal disorders, (2) general disorders and administration site conditions, and (3) respiratory, thoracic, and mediastinal disorders. Common AEs including diarrhœa, pancreatitis, gastroenteritis, asmyopericarditis, proctitis ulcerative, and glutamate dehydrogenase level abnormal aligned with established drug labeling. Notably, novel pharmacovigilance signals were detected for organizing pneumonia (FAERS: n = 113, ROR = 35.21, 95%CI 29.21-42.46; JADER: n = 32, ROR = 7.90, 5.56-11.22) and eosinophilic pneumonia (FAERS: n = 77, ROR = 41.25, 32.87-51.76; JADER: n = 179, ROR = 57.69, 49.26-67.56), both requiring urgent clinical attention. AEs mainly occurred within 30 days (58.36%) with a median onset of 17 days, and the median onset time of female patients (12 days) was shorter than male patients (25 days). Conclusion: This pharmacovigilance study provides clinically significant evidence regarding safety-associated adverse events (AEs) of mesalazine in real-world settings. The detection of novel safety signals, particularly organizing pneumonia and eosinophilic pneumonia, highlights the necessity for enhanced post-marketing surveillance through longitudinal AE monitoring. Our findings contribute to the evolving safety profile of mesalazine and warrant further clinical investigations to validate their clinical relevance and establish causal relationships.