Multi-item Gamma Poisson Shrinker Research Articles

Vitreoretinal Traction Syndrome, Nitrituria and Human Epidermal Growth Factor Receptor Negative Might Occur in the Aromatase-Inhibitor Anastrozole Treatment

Background. Anastrozole has been approved for treatment of hormone receptor-positive advanced or metastatic breast cancer by FDA. This study was to assess Anastrozole-related adverse events (AEs) of real-world through data mining of the US Food and drug administration adverse event reporting system (FAERS). Methods. Four different disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN) and the multiitem gamma Poisson shrinker (MGPS) algorithms were employed to quantify the signals of Anastrozole-associated AEs. Results. A total 25 system organ class (SOCs) and 300 significant disproportionality Preferred Terms (PTs) were found in this study. The top 5 most significant SOCs were Eye disorders, renal and urinary disorders, respiratory, thoracic and mediastinal disorders, investigations, and cardiac disorders. Unexpected significant AEs was vitreoretinal traction syndrome (ROR = 1108.22, PRR = 1103.98, IC025 = 9.51, EBGM05 = 389.98), nitrituria (ROR = 3561.82, PRR = 3557.28, IC025 = 10.38, EBGM05 = 318.83) and human epidermal growth factor receptor negative (ROR = 675.04, PRR = 674.01, IC025 = 9, EBGM05 = 204.57). Conclusion. The Unexpected significant AEs associated with anastrozole were identified in this study, warrants urgent clarification through additional prospective studies.

Assessing the safety of bedaquiline: insight from adverse event reporting system analysis

BackgroundThe development and marketing of Bedaquiline (BDQ) represent significant advancements in treating tuberculosis, particularly multidrug-resistant forms. However, comprehensive research into BDQ’s real-world safety remains limited.PurposeWe obtained BDQ related adverse event (AE) information from the US Food and Drug Administration’s Adverse Event Reporting System (FAERS) to assess its safety and inform drug usage.MethodsThe AE data for BDQ from 2012 Q4 to 2023 Q3 was collected and standardized. Disproportionality analysis, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Multi-item Gamma Poisson Shrinker (MGPS), and Bayesian Confidence Propagation Neural Network (BCPNN) was used to quantify signals of BDQ-related AEs. Logistic regression was used to analyze the individual data of hepatotoxicity and drug-induced liver injury, and multiple linear regression models were established. Additionally, network pharmacology was employed to identify the potential biological mechanisms of BDQ-induced liver injury.ResultsWe identified 2017 case reports directly related to BDQ. Our analysis identified 341 Preferred Terms (PTs) characterizing these AEs across 27 System Organ Classes (SOC). An important discovery was the identification of AEs associated with ear and labyrinth disorders, which had not been documented in the drug’s official leaflet before. Subgroup analysis revealed a negative correlation between BDQ-related liver injury and females (OR: 0.4, 95%CI: 0.3–0.6). In addition, via network pharmacology approach, a total of 76 potential targets for BDQ related liver injury were predicted, and 11 core target genes were selected based on the characterization of protein-protein interactions. The pathway linked to BDQ-induced liver injury was identified, and it was determined that the PI3K-Akt signaling pathway contained the highest number of associated genes.ConclusionThe analysis of the FAERS database revealed adverse events linked to BDQ, prompting the use of a network pharmacology approach to study the potential molecular mechanism of BDQ-induced liver injury. These findings emphasized the significance of drug safety and offered understanding into the mechanisms behind BDQ-induced liver injury. BDQ demonstrated distinct advantages, including reduced incidence of certain adverse events compared to traditional treatments such as injectable agents and second-line drugs. However, it is important to acknowledge the limitations of this analysis, including potential underreporting and confounding factors. This study provides valuable insights into the safety of BDQ and its role in the management of MDR-TB, emphasizing the need for continued surveillance and monitoring to ensure its safe and effective use.

Post-marketing safety concerns with elagolix: a disproportionality analysis of the FDA adverse event reporting system

ABSTRACT Objective Elagolix is approved for the treatment of moderate-to-severe pain associated with endometriosis. However, the long-term safety of elagolix in a large sample of real-world patients is unknown. Methods The U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) reports were collected and analyzed for the first quarter of 2019 through the second quarter of 2023. Disproportionality analyses, including 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, were employed in data mining to quantify the signals of elagolix-related adverse events (AEs). Results A total of 112 elagolix-induced AE signals were detected in 17 system organ classes (SOCs) that simultaneously met the thresholds of 4 algorithms. After removing the non-drug-related AE signals, we detected several AE signals such as hot flushes, bone pain, suicidal ideation, depression, and increased liver enzymes, which were known during the clinical trial phase. In addition to this, we detected several unexpected important adverse events that were not mentioned in the drug insert, including cystitis interstitial, parosmia, and epiploic appendagitis. The median onset time of elagolix-associated AEs was 28.5 days. The majority of cases occurred within 1 month after initiation of elagolix treatment. Conclusion Our study provides a comprehensive picture of the safety of elagolix in the post-marketing setting, while also identifying potential new AE signals. These findings emphasize the importance of continued monitoring of the potential risks of elagolix.

A real-world pharmacovigilance analysis of the FDA adverse event reporting system events for polatuzumab vedotin

ABSTRACT Background Polatuzumab vedotin is the first antibody-drug conjugate approved by the US Food and Drug Administration (FDA) for patients with diffuse large B-cell lymphoma. This study evaluated adverse events (AEs) associated with polatuzumab vedotin by data mining of the FDA Adverse Event Reporting System (FAERS). Methods This study included AEs registered in FAERS between 2019 Q2 and 2023 Q2. Four algorithms were used to quantify the signals of polatuzumab vedotin-associated AEs, including reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker. Results A total of 7,609,450 reports were collected from the FAERS database, and 1,388 reports of polatuzumab vedotin were identified as primary suspected AEs. Polatuzumab vedotin-associated AEs involved 26 organ systems. According to the four algorithms, 108 significant disproportionality AEs were retained simultaneously. Unexpected significant AEs included gastrointestinal hemorrhage, ileus, gastrointestinal perforation, cholecystitis, hypogammaglobulinemia, hepatitis B reactivation, hypercalcemia, hydronephrosis, cystitis hemorrhagic, interstitial lung disease, and thrombophlebitis. The median time to onset of polatuzumab vedotin-associated AEs was 20 (interquartile range 4–56) days. Conclusions Our study identified significant new AE signals for polatuzumab vedotin through real-world disproportionality analysis data and may provide additional evidence for risk identification of polatuzumab vedotin.

Unveiling potential adverse events associated with escitalopram oxalate: A real-world analysis based FDA adverse event reporting system database.

The study aimed to conduct a multidimensional evaluation of potential adverse events (AEs) of escitalopram oxalate based on the FDA adverse event reporting system (FAERS) database. This study utilized the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma-poisson shrinker (MGPS) to mine and analyze data from the FAERS database from the first quarter of 2004 to the second quarter of 2023. There was a total of 19,854 AE reports related to escitalopram oxalate, extracting 625 preferred terms (PTs), and covering 27 system organ classes (SOCs). The results showed that the number of reports by females was significantly higher than males, accounting for 57.68%. The reporting number was higher in 2018 and 2019, accounting for 9.50% and 10.18% of the total reports, respectively. The main reporters were consumers and other health professionals, accounting for 26.99% and 26.75% respectively. The majority of the reports were primarily from the United States. Newly emerging AE signals such as intentional overdose (n = 691, ROR 8.51, PRR 8.45, IC 3.05, Empirical Bayesian Geometric Mean (EBGM) 8.35), suicide attempt (n = 665, ROR 8.58, PRR 8.52, IC 3.06, EBGM 8.42), serum serotonin (n = 5, ROR 1044.78, PRR 1044.71, IC 2.56, EBGM 392.39), anti-actin antibody positive (n = 5, ROR 626.87, PRR 626.83, IC 2.56, EBGM 313.91), among others, were not mentioned in the drug's label. While escitalopram oxalate has clear benefits in the treatment of depression and other mental health disorders, the presence of AEs also suggests risks associated with its use. Particularly concerning are risks of suicide and changes in serum serotonin levels.

Comparison of Statistical Signal Detection Methods in Adverse Events Following Immunization - China, 2011-2015.

The current study aims to assess the performance of data mining techniques in detecting safety signals for adverse events following immunization (AEFI) using routinely obtained data in China. Four different methods for detecting vaccine safety signals were evaluated. The AEFI data from 2011 to 2015 was collected for our study. We analyzed the data using four different methods to detect signals: the proportional reporting ratio (PRR), reporting odds ratio (ROR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS). Each method was evaluated at 1-3 thresholds for positivity. To assess the performance of these methods, we used the published signal rates as gold standards to determine the sensitivity and specificity. The number of identified signals varied from 602 for PRR1 (with a threshold of 1) to 127 for MGPS1. When considering the common reactions as the reference standard, the sensitivity ranged from 0.9% for MGPS1/2 to 38.2% for PRR1/2, and the specificity ranged from 85.2% for PRR1 and ROR1 to 96.7% for MGPS1. When considering the rare reactions as the reference standard, PRR1, PRR2, ROR1, ROR2, and BCPNN exhibited the highest sensitivity (73.3%), while MGPS1 exhibited the highest specificity (96.9%). For common reactions, the sensitivities were modest and the specificities were high. For rare reactions, both the sensitivities and specificities were high. Our study provides valuable insights into the selection of signal detection methods and thresholds for AEFI data in China.

A real‑world pharmacovigilance study of FDA adverse event reporting system events for daratumumab

ABSTRACT Background Daratumumab, a first-in-class humanized IgG1κ monoclonal antibody that targets the CD38 epitope, has been approved for treatment of multiple myeloma by FDA. The current study was to evaluate daratumumab-related adverse events (AEs) through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS). Research design and methods Disproportionality analyses, including 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 were employed to quantify the signals of daratumumab-associated AEs. Results Out of 10,378,816 reports collected from the FAERS database, 8727 reports of daratumumab-associated AEs were identified. A total of 183 significant disproportionality preferred terms (PTs) were retained. Unexpected significant AEs such as meningitis aseptic, leukoencephalopathy, tumor lysis syndrome, disseminated intravascular coagulation, hyperviscosity syndrome, sudden hearing loss, ileus and diverticular perforation were also detected. The median onset time of daratumumab-related AEs was 11 days (interquartile range [IQR] 0–76 days), and most of the cases occurred within 30 days. Conclusion Our study found potential new and unexpected AEs signals for daratumumab, suggesting prospective clinical studies are needed to confirm these results and illustrate their relationship.

Discovering clinical drug-drug interactions with known pharmacokinetics mechanisms using spontaneous reporting systems and electronic health records

ObjectiveAlthough the mechanisms behind pharmacokinetic (PK) drug-drug interactions (DDIs) are well-documented, bridging the gap between this knowledge and clinical evidence of DDIs, especially for serious adverse drug reactions (SADRs), remains challenging. While leveraging the FDA Adverse Event Reporting System (FAERS) database along with disproportionality analysis tends to detect a vast number of DDI signals, this abundance complicates further investigation, such as validation through clinical trials. Our study proposed a framework to efficiently prioritize these signals and assessed their reliability using multi-source Electronic Health Records (EHR) to identify top candidates for further investigation. MethodsWe analyzed FAERS data spanning from January 2004 to March 2023, employing four established disproportionality methods: Proportional Reporting Ratio (PRR), Reporting Odds Ratio (ROR), Multi-item Gamma Poisson Shrinker (MGPS), and Bayesian Confidence Propagating Neural Network (BCPNN). Building upon these models, we developed four ranking models to prioritize DDI-SADR signals and cross-referenced signals with DrugBank. To validate the top-ranked signals, we employed longitudinal EHRs from Vanderbilt University Medical Center and the All of Us research program. The performance of each model was assessed by counting how many of the top-ranked signals were confirmed by EHRs and calculating the average ranking of these confirmed signals. ResultsOut of 189 DDI-SADR signals identified by all four disproportionality methods, only two were documented in the DrugBank database. By prioritizing the top 20 signals as determined by each of the four disproportionality methods and our four ranking models, 58 unique DDI-SADR signals were selected for EHR validations. Of these, five signals were confirmed. The ranking model, which integrated the MGPS and BCPNN, demonstrated superior performance by assigning the highest priority to those five EHR-confirmed signals. ConclusionThe fusion of disproportionality analysis with ranking models, validated through multi-source EHRs, presents a groundbreaking approach to pharmacovigilance. Our study's confirmation of five significant DDI-SADRs, previously unrecorded in the DrugBank database, highlights the essential role of advanced data analysis techniques in identifying ADRs.

Multidimensional assessment of adverse events of bupropion: A large-scale data analysis from the FAERS database

ObjectiveBupropion, a monocyclic antidepressant, aids in smoking cessation, treats major depression, and prevents severe depression in seasonal affective disorder patients. Yet, its adverse reactions remain insufficiently studied. MethodsAll data from the raw data packages for 78 quarters from the 1st quarter of 2004 to the 2nd quarter of 2023 were extracted from the FDA Adverse Event Reporting System (FAERS) database and imported into the SAS9.4 software for data cleaning and analysis. The Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS) methods were used to analyze drug adverse events and assess their compliance with various screening criteria. ResultsThe results showed a total of 36,862 reports related to Bupropion use, identifying 364 positive reaction terms (PT) covering 23 System Organ Classes (SOCs). In addition to known side effects, some new potential adverse reactions were found, such as Stool analysis abnormal, Oculocephalogyric reflex absent, Suspected suicide, and so on. At the same time, reactions like Encephalopathy neonatal, Hyponatraemic coma, and Electrocardiogram QRS complex prolonged were prominently ranked. Notably, occurrences such as Urine amphetamine positive and Amphetamines positive were relatively high, suggesting extra caution for these potential adverse reactions during clinical use of Bupropion. ConclusionThese findings highlight the potential health risks of long-term Bupropion use, especially concerning efficacy, positive drug tests, and suicidal tendencies. Therefore, it is recommended to monitor and assess patients using Bupropion more stringently to use this therapeutically potential drug more safely and effectively.

Post-marketing safety evaluation of lurbinectedin: a pharmacovigilance analysis based on the FAERS database.

Background: On 15 June 2020, the United States Food and Drug Administration (FDA) approved lurbinectedin for treating adult patients with metastatic small-cell lung cancer whose disease has progressed despite prior platinum-based chemotherapy. Following its market approval, safety data on lurbinectedin in large populations is currently lacking. Therefore, this study aims to evaluate adverse events (AEs) associated with lurbinectedin using the FDA's Adverse Event Reporting System (FAERS)database. Methods: Data concerning lurbinectedin from the FAERS database were extracted for the period from June 2020 to September 2023. Four disproportionality analysis algorithms were utilized to assess potential AEs linked to lurbinectedin: reporting odds ratio (ROR), proportional reporting ratio, disproportionate multi-item gamma Poisson shrinker, and Bayesian confidence propagation neural network. These algorithms were applied to quantify signals of lurbinectedin-related AEs. Result: A total of 5,801,535 AE reports were retrieved from the FAERS database, with 511 related to lurbinectedin. These lurbinectedin-induced AEs were observed in 23 system organ classes (SOCs). After simultaneously applying the four algorithms, 47 lurbinectedin-induced AE signals were detected in 23 SOCs. At the SOC level, blood and lymphatic system disorders (ROR, 6.70; 95% confidence interval [CI]: 5.47-8.22) were the only SOC that met all four algorithms. Lurbinectedin's most frequent adverse event was death (ROR: 6.11%, 95% CI: 4.86-7.68), while extravasation exhibited the strongest signal intensity in the ROR algorithm (ROR: 326.37%, 95% CI: 191.66-555.75). Notably, we identified a novel signals: tumor lysis syndrome (ROR: 63.22%, 95% CI: 33.87-117.99). The mean time of onset of AEs was 66 days, the median time of onset was 25days (interquartile range: 8-64days), and most AEs occurred within the first month of lurbinectedin treatment. Conclusion: Our study provided a comprehensive evaluation of lurbinectedin's safety profile in the post-marketing setting. In addition to the adverse events consistent with the existing clinical trials and labeling information, we have also identified an unreported signal related to tumor lysis syndrome. This finding will better guide the clinical practice of lurbinectedin and provide valuable evidence for future research.

Electrolyte disorders induced by six multikinase inhibitors therapy for renal cell carcinoma: a large-scale pharmacovigilance analysis

To provide evidence for optimization of multi-kinase inhibitors (MKIs) use in the clinic, we use the public database to describe and evaluate electrolyte disorders (EDs) related to various MKIs treated for renal cell carcinoma. We analyzed spontaneous reports submitted to the Food and Drug Administration Adverse Events Reporting System (FAERS) in an observational and retrospective manner. Selecting electrolyte disorders' adverse events to multikinase inhibitors (axitinib, cabozantinib, lenvatinib, pazopanib, sunitinib, and sorafenib). We used Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) algorithms to analyze suspected adverse reactions of electrolyte disorders induced by MKIs (which were treated for renal cell carcinoma) between January 2004 and December 2022. As of December 2022, 2772 MKIs (which were treated for renal cell carcinoma) ICSRs were related to electrolyte disorders AEs. In general, there were more AEs cases in males, except lenvatinib and 71.8% of the cases were submitted from North America. ICSRs in this study, the age group most frequently affected by electrolyte disorders AEs was individuals aged 45–64 years for axitinib, cabozantinib, pazopanib, and sunitinib, whereas electrolyte disorders AEs were more common in older patients (65–74 years) for sorafenib and lenvatinib. For all EDs documented in ICSRs (excluding missing data), the most common adverse outcome was hospitalization(1429/2674, 53.4%), and the most serious outcome was death/life-threat(281/2674, 10.5%). The prevalence of mortality was highest for sunitinib-related EDs (145/616, 23.5%), excluding missing data (n = 68), followed by cabozantinib-related EDs (20/237, 8.4%), excluding missing data (n = 1). The distribution of time-to-onset of Each drug-related ICSRs was not all the same, and the difference was statistically significant (P = 0.001). With the criteria of ROR, the six MKIs were all significantly associated with electrolyte disorders AEs, the strongest association was the association between cabozantinib and hypermagnesaemia. MKIs have been reported to have significant electrolyte disorders AEs. Patients and physicians need to recognize and monitor these potentially fatal adverse events.

Hepatotoxicity of newer antiseizure medications in children: an overview and disproportionality analysis of VigiBase

ABSTRACT Background We aimed to characterize newer antiseizure medications (ASMs)-induced hepatotoxicity in children and identify signals of disproportionate reporting of hepatotoxicity-related adverse drug events (ADEs). Research Design and Methods Case reports reported to VigiBase were accessed using Empirica™ Signal software. To summarize characteristics of the retrieved cases, descriptive statistics were used. A disproportionality analysis was conducted using the Multi-item Gamma Poisson Shrinker algorithm, which calculates Empirical Bayesian Geometric Mean value and its lower and upper 95% confidence limits (EB05 and EB95, respectively). EB05 > 2, N > 0 was considered a signal. Results Based on 870 analyzed cases, a higher proportion of cases was reported in girls than in boys and in patients aged 2–11 years than in other age groups. Most cases were serious. In 25 cases, hepatotoxicity resulted in death. A high proportion of patients (n = 275, 31.61%) experienced hypersensitivity reactions, mostly due to lamotrigine. The disproportionality analysis yielded 17 signals concerning felbamate, lamotrigine, levetiracetam, oxcarbazepine, stiripentol, and topiramate. Four signals were for severe liver injury and concerned felbamate, lamotrigine, levetiracetam, and topiramate. Gender-biased reporting frequency was detected for four ASM-ADE combinations. Conclusion Our results should serve to raise clinicians’ awareness about the potential association between several newer ASMs and drug-induced liver injury in children.

Statistical Methodologies for Detecting Drug-Drug Interaction Using Spontaneous Reporting System

Statistical methodologies of signal detection for drug-drug interactions (DDIs) have been developed and used. In this study, we review methodologies for DDI signal detection using the spontaneous reporting system. We describe the characteristics of the additive and multiplicative risk model, logistic regression model, Multi-item Gamma-Poisson Shrinker, <i>Ω</i> shrinkage measure model, and Chi-square statistics model. We discuss the advantages and disadvantages of each methodology along with examples, providing researchers with information to choose the most appropriate methodology for their study.

A Real-World Pharmacovigilance Study of Ceftazidime/Avibactam: Data Mining of the Food and Drug Administration Adverse Event Reporting System Database.

Ceftazidime/avibactam (CAZ/AVI) is a combination of a well-known third-generation, broad-spectrum cephalosporin with a new beta-lactamase inhibitor that has been approved for the treatment of various infectious diseases (especially multidrug-resistant Gram-negative bacterial infections) by the Food and Drug Administration (FDA). The current study extensively assessed CAZ/AVI-related adverse events (AEs) in the real world through data mining of the FDA Adverse Event Reporting System (FAERS) database to better understand toxicities. The signals of CAZ/AVI-related AEs were quantified using disproportionality analyses, including the reporting odds ratio, the proportional reporting ratio, the Bayesian confidence propagation neural network, and the multi-item gamma Poisson shrinker algorithms. Out of 10,114,815 records retrieved from the FAERS database, 628 cases were identified, where CAZ/AVI was implicated as the primary suspect drug. A total of 61 preferred terms with significant disproportionality that simultaneously met the criteria of all four algorithms were retained. Several unexpected safety signals may also occur, including melena, hypernatremia, depressed level of consciousness, brain edema, petechiae, delirium, and shock hemorrhagic. The median onset time for AEs associated with CAZ/AVI was 4 days, with most cases occurring within 3 days after CAZ/AVI initiation.

Adverse drug events associated with linezolid administration: a real-world pharmacovigilance study from 2004 to 2023 using the FAERS database.

Introduction: Linezolid is an oxazolidinone antibiotic that is active against drug-resistant Gram-positive bacteria and multidrug-resistant Mycobacterium tuberculosis. Real-world studies on the safety of linezolid in large populations are lacking. This study aimed to determine the adverse events associated with linezolid in real-world settings by analyzing data from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Methods: We retrospectively extracted reports on adverse drug events (ADEs) from the FAERS database from the first quarter of 2004 to that of 2023. By using disproportionality analysis including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), along with the multi-item gamma Poisson shrinker (MGPS), we evaluated whether there was a significant association between linezolid and ADE. The time to onset of ADE was further analyzed in the general population and within each age, weight, reporting population, and weight subgroups. Results: A total of 11,176 reports of linezolid as the "primary suspected" drug and 263 significant adverse events of linezolid were identified, including some common adverse events such as thrombocytopenia (n = 1,139, ROR 21.98), anaemia (n = 704, ROR 7.39), and unexpected signals that were not listed on the drug label such as rhabdomyolysis (n = 90, ROR 4.33), and electrocardiogram QT prolonged (n = 73, ROR 4.07). Linezolid-induced adverse reactions involved 27 System Organ Class (SOC). Gender differences existed in ADE signals related to linezolid. The median onset time of all ADEs was 6 days, and most ADEs (n = 3,778) occurred within the first month of linezolid use but some may continue to occur even after a year of treatment (n = 46). Conclusion: This study reports the time to onset of adverse effects in detail at the levels of SOC and specific preferred term (PT). The results of our study provide valuable insights for optimizing the use of linezolid and reducing potential side effects, expected to facilitate the safe use of linezolid in clinical settings.

Major cardiovascular events under biologic psoriasis therapies: a 19-year real-world analysis of FAERS data.

Over the years when biologic psoriasis therapies (TNF inhibitors, IL-12/23 inhibitors, IL-23 inhibitors, and IL-17 inhibitors) have been used in psoriasis patients, reports of major cardiovascular events (MACEs) have emerged. This study aims to investigate the association between MACEs and biologic psoriasis therapies by using information reported to the US Food and Drug Administration Adverse Event Reporting System (FAERS). FAERS data (January 2004 to December 2022) were reviewed. For each drug-event pair, the proportional reporting ratio (PRR) and the multi-item gamma Poisson shrinker (MGPS) algorithms were used to identify drug-adverse event associations. We filtered the query for indication and identified 173,330 reports with psoriasis indication in FAERS throughout the analyzed time frame. MACEs occurred in 4,206 patients treated with biologics. All the four biological classes had an elevated and similar reporting rates for MACEs relative to other alternative psoriasis treatments (PRR from 2.10 to 4.26; EB05 from 1.15 to 2.45). The descending order of association was IL-12/23 inhibitors>IL-17 inhibitors>IL-23 inhibitors>TNF inhibitors. The signal strength for myocardial infarction (PRR, 2.86; χ2, 296.27; EBGM 05, 1.13) was stronger than that for stroke, cardiac fatality, and death. All the biological classes demonstrated a little higher EBGM 05 score≥1 for the MACEs in patients aged 45-64 years. The time-to-onset of MACEs was calculated with a median of 228 days. Analysis of adverse event reports in the FAERS reflects the potential risk of MACEs associated with the real-world use of biological therapies in comparison to other alternative psoriasis treatments. Future long-term and well-designed studies are needed to further our knowledge regarding the cardiovascular safety profile of these agents.

A real-world disproportionality analysis of mesalazine data mining of the public version of FDA adverse event reporting system.

Background: Mesalazine, a preparation of 5-aminosalicylic acid, is a medication widely used in clinical practice as a first-line therapy in the treatment of mild and moderate inflammatory bowel disease. However, the long-term safety of mesalazine in large sample population was unknown. The current study was to assess mesalazine -related adverse events of real-world through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: Disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio the Bayesian confidence propagation neural network and the multi-item gamma Poisson shrinker (MGPS) algorithms were employed to quantify the signals of mesalazine -associated AEs. Results: Out of 14,149,980 reports collected from the FDA Adverse Event Reporting System database, 24,284 reports of mesalazine -associated AEs were identified. A total of 170 significant disproportionality preferred terms conforming to the four algorithms simultaneously were retained. The most common AEs included colitis ulcerative, diarrhoea, condition aggravated, crohn's disease, fatigue, abdominal pain, nausea, haematochezia, which were corresponding to those reported in the specification and clinical trials. Unexpected significant AEs as dizziness, drug ineffective, drug hypersensitivity, infection, off label use, weight decreased, decreased appetite, arthralgia, rash might also occur. The median onset time of mesalazine -related AEs was 1,127days (interquartile range [IQR] 1,127-1,674days), and most of the cases occurred 2years later (n = 610, 70.93%) and within the first 1month (n = 89, 10.35%) after mesalazine initiation. Conclusion: Results of our study were consistent with clinical observations. We also found potential new and unexpected AEs signals for mesalazine, suggesting prospective clinical studies were needed to confirm these results and illustrate their relationship. Our results could provide valuable evidence for further safety studies of mesalazine.

Liver injury due to endothelin receptor antagonists: a real-world study based on post-marketing drug monitoring data.

Liver injury is the hallmark adverse reaction of endothelin receptor antagonist (ERA). Since the first drug, bosentan has been widely used in clinical practice, hepatotoxicity has been accompanied by the history of ERA. The new ERA has been proven to have a lower liver risk but the current research findings are inconsistent. ERA-based targeted drug combinations are commonly used in the treatment of pulmonary arterial hypertension, where the risk of liver injury is difficult to estimate. This study aimed to compare the correlation between ERA and different ERA combination regimens with liver injury in the real world. This is a retrospective study using data from the Adverse Event Reporting System (Food and Drug Administration AERS, FAERS). The study used proportional imbalance and Bayesian analysis to mine FAERS data from January 2004 to December 2022 to determine the association of three ERAs with liver injury and to further mine the risk of liver injury due to the combination of ERAs with other targeted drugs. In addition, we analyzed the onset time, mortality, and hospitalization rate of liver injury caused by different ERA combination regimens. We screened out 3581 ERA-related liver injury events, of which bosentan (59.82%) had the largest number of cases. The patients with liver injury were mainly female (60.63%), and the age was concentrated between 61 and 75 years (26.75%). According to different signal mining methods, reporting odds ratio (ROR; 3.38, 95% confidence interval = 3.23-3.53), proportional reporting ratio (PRR; 3.22, χ2 = 37.84), Bayesian confidence propagation neural network (BCPNN; 1.68, 95% confidence interval = 1.61), multi-item gamma Poisson shrinker (MGPS; 3.21, 95% confidence interval = 3.09), bosentan had the strongest association with liver injury compared to ambrisentan and macitentan. Furthermore, bosentan + sildenafil [ROR (2.52, 95% confidence interval = 2.23-2.84), PRR (2.44, χ2 = 15.92), BCPNN (1.29, 95% confidence interval = 1.14), MGPS (2.44, 95% confidence interval = 2.21)], bosentan + epoprostenol [ROR (5.39, 95% confidence interval = 4.29-6.77), PRR (4.94, χ2 = 65.18), BCPNN (2.30, 95% confidence interval = 1.83), MGPS (4.94, 95% confidence interval = 4.08)], bosentan + iloprost [ROR (2.70, 95% confidence interval = 2.11-3.45), PRR (2.61, χ2 = 31.03), BCPNN (1.38, 95% confidence interval = 1.08), MGPS (2.61, 95% confidence interval = 2.12)] had a higher risk of liver injury caused by the three ERA combination regimens. The median time to onset of hepatotoxicity associated with all ERA combination regimens was 259 days (interquartile range: 58-716.5 days). Finally, the hospitalization rate for patients experiencing hepatotoxicity with ERA combination regimens was 47.86% and the mortality rate was 12.67%. By mining the FAERS, we analyzed and compared the risk of liver injury related to different ERA and ERA combination regimens, and the onset time and adverse reaction outcomes of all ERA combination regimens. According to the results of the study, bosentan had the highest risk of liver injury and the combination regimens bosentan + sildenafil, bosentan + epoprostenol, and bosentan + iloprost had a stronger risk of liver injury. From the early stages of treatment, we need to regularly monitor the liver function of patients, especially for females and the elderly, and discontinue the suspected drug as soon as the liver injury occurs.

Adverse events in patients with advanced urothelial carcinoma treated with erdafitinib: a retrospective pharmacovigilance study

Purpose: On 12 April 2019, erdafitinib gained the first FDA approval as the second-line treatment for adult patients with locally advanced or metastatic urothelial cancer following progression during or after at least one previous line of platinum-based chemotherapy. However, the long-term safety profile of erdafitinib in a large patient population remains unexplored. The current study aimed to assess the adverse events (AEs) associated with erdafitinib through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS).Method: 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 based on disproportionality were employed to quantify the signals of erdafitinib-associated AEs.Results: A total of 6,322,279 reports of AEs were retrieved from the FAERS database spanning 2019 to 2022, out of which, 700 reports of erdafitinib as the “primary suspected” were identified. These erdafitinib-induced AEs were observed across 24 targeted system organ classes (SOCs). After conforming to the four algorithms at the same time, a total of 441 signals of erdafitinib-induced AEs were detected across 23 SOCs. Notably, signals associated with metabolism and nutrition disorders, eye disorders, and skin and subcutaneous tissue disorders were among the most prevalent. The median onset time for AEs was found to be 54 days [interquartile range (IQR) 17–112 days], with a majority of AEs occurring within the initial 6 months after initiating erdafitinib (37.23% within the first month, 15.53% within the second month, and 16.79% within the third month).Conclusion: The findings of this study align with existing clinical observations, offering a comprehensive long-term post-marketing safety evaluation of erdafitinib. The results provide valuable evidence to enhance the understanding of erdafitinib’s safety profile, aiding further research and guiding clinical practice.

Mining and analysis of adverse event signals of Cariprazine based on the real-world data of FAERS database

ObjectiveThis study aims to analyze the adverse events (AEs) of Cariprazine based on the FAERS database, providing evidence for its safety surveillance. MethodsFor signal quantification of Cariprazine-related AEs, we used disproportionality analysis including the Ratio of Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS) algorithms. ResultsWe selected Cariprazine-related AE reports from the FAERS database from the fourth quarter of 2015 to the first quarter of 2023, and performed a detailed data analysis. Out of a total of 12,278,580 case reports, 3659 were found to be directly related to Cariprazine. We identified 140 Preferred Terms (PT) to describe these AEs, finding that they involved 27 organ systems. Specifically, AEs related to eye disorders such as Cataract cortical, Cataract nuclear, Accommodation disorder, Lenticular opacities, Oculogyric crisis, Dyschromatopsia were not explicitly mentioned in the drug's leaflet, indicating the presence of new ADR signals. ConclusionAnalysis of the FAERS database identified AEs associated with Cariprazine, notably in eye disorders not previously documented in the drug's official leaflet. These findings emphasize the need for continuous post-market surveillance and awareness among healthcare professionals regarding potential new ADR signals.