Multi-item Gamma Poisson Shrinker Research Articles

A real-world pharmacovigilance study of polatuzumab vedotin based on the FDA adverse event reporting system (FAERS).

Polatuzumab vedotin, the first FDA-approved antibody-drug conjugate (ADC) targeting CD79b, is utilized in the treatment of previously untreated diffuse large B-cell lymphoma (DLBCL) or high-grade B-cell lymphoma (HGBL), as well as relapsed or refractory (R/R) DLBCL. Despite its approval, concerns persist regarding the long-term safety profile of polatuzumab vedotin. This study aims to evaluate the adverse events (AEs) associated with polatuzumab vedotin since its approval in 2019, utilizing data mining strategies applied to the FDA Adverse Event Reporting System (FAERS). Signal detection employed four methodologies, including reporting odds ratio (ROR), proportional reporting ratio (PRR), bayesian confidence propagation neural network (BCPNN), and multi-item gamma poisson shrinker (MGPS), to evaluate and quantify the signals of polatuzumab vedotin-associated AEs. Additionally, subgroup analyses based on patients age, gender, and fatal cases were conducted to investigate AEs occurrences in specific subpopulations. A total of 1,521 reports listing polatuzumab vedotin as a "principal suspect (PS)" drug were collected from the FAERS database. Through concurrent compliance with four algorithms, 19 significant Standardized MedDRA Query (SMQ) AEs and 92 significant Preferred Term (PT) AEs were detected. Subgroup analyses revealed a higher incidence of PTs in male patients compared to female patients, increased likelihood of polatuzumab vedotin-associated AEs in elder patients (>65years), and AEs with a high risk of fatal cases include: blood lactate dehydrogenase increased, cytopenia, and hydronephrosis. The median time to AEs occurrence following polatuzumab vedotin initiation was 18.5 (5∼57.75) days, with 95% of AEs occurred within 162days. This study identified various AEs associated with polatuzumab vedotin, offering critical insights for clinical monitoring and risk identification in patients receiving polatuzumab vedotin therapy.

Adverse events associated with eteplirsen: A disproportionality analysis using the 2016–2023 FAERS data

BackgroundEteplirsen (Exondys 51) is an orphan drug approved for the treatment of Duchenne muscular dystrophy (DMD), having received accelerated approval from the U.S. Food and Drug Administration (FDA) in 2016. The primary aim of this study is to closely monitor adverse events (AEs) associated with eteplirsen and to identify emerging signals to better characterize their safety profile. MethodsAEs due to eteplirsen usage reported from the third quarter (Q3) of 2016 to the fourth quarter (Q4) of 2023 were collected from the FDA Adverse Event Reporting System (FAERS). The role_code of AEs mainly includes primary suspect (PS), secondary suspect (SS), concomitant (C), and interaction (I). This study targeted reports with a role_cod of ‘PS.’ According to the FDA deduplication rule, the latest FDA_DT is selected when the CASEID is the same, and the higher PRIMARYID is selected when the CASEID and FDA_DT are the same. Disproportionality analyses, encompassing four algorithms for reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian configuration promotion neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS), were utilized to quantify the signals of AEs associated with eteplirsen. ResultsFrom the FAERS database, a total of 13,205,369 reports were amassed throughout the study duration. Following the eradication of duplicates, the number of reports with eteplirsen designated as the PS amounted to 1480 encompassed 25 organ systems. Among these, “general disorders and administration site conditions,” “injury, poisoning, and procedural complications,” “respiratory, thoracic, and mediastinal disorders,” “infections and infestations,” “vascular disorders,” and “product issues” met at least one of the four computational criteria. Additionally, 55 Preferred Terms (PTs) aligned with the prescribed algorithms. The median time to AEs in these patients was 903 days with an interquartile range (IQR) of 269–1575 days. Moreover, 70.04 % of AEs manifested one year or more after the initiation of treatment. ConclusionAs an orphan drug granted accelerated approval, our study has confirmed well-known adverse drug reactions and identified potential safety issues associated with eteplirsen treatment. This has contributed to a deeper understanding of the complex interrelations between adverse reactions and the use of eteplirsen. The findings underscore the critical importance of ongoing monitoring and sustained observation to promptly detect and effectively manage AEs, thereby enhancing the overall safety and well-being of patients treated with eteplirsen for DMD.

Association of thrombocytopenia with immune checkpoint inhibitors: a large-scale pharmacovigilance analysis based on the data from FDA adverse event reporting system database.

Introduction: An increasing number of immune-related adverse events (irAEs) induced by immune checkpoint inhibitors (ICIs) have been reported during clinical treatment. We aimed to explore the clinical characteristics of patients with ICIs-induced ITP under different therapeutic strategies based on the FAERS database and explore the potential biological mechanisms in combination with TCGA pan-cancer data. Methods: Data from FAERS were collected for ICIs adverse reactions between January 2012 and December 2022. Disproportionality analysis identified ICIs-induced ITP in the FAERS database using the reporting odds ratio (ROR), proportional reporting ratio (PRP), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker algorithms (MGPS). The potential biological mechanisms underlying ITP induced by ICIs were examined using TCGA transcriptome data on cancers. Results: In the FAERS, 345 ICIs-induced ITP reports were retrieved, wherein 290 (84.06%) and 55 (15.94%) were reported as monotherapy and combination therapy, respectively. The median age of the reported patients with ICIs-induced ITP was 69 years (IQR 60-76), of which 62 (18%) died and 47 (13.6%) had a life-threatening outcome. The majority of reported indications were lung, skin, and bladder cancers, and the median time to ITP after dosing was 42 days (IQR 17-135), with 64 patients (43.5%) experiencing ITP within 30 days of dosing and 88 patients experiencing ITP in less than 2months (59.9%). The occurrence of ICIs-induced ITP may be associated with ICIs-induced dysregulation of the mTORC1 signaling pathway and megakaryocyte dysfunction. Conclusion: There were significant reporting signals for ITP with nivolumab, pembrolizumab, cemiplimab, atezolizumab, avelumab, durvalumab, ipilimumab, nivolumab/ipilimumab, and pembrolizumab/ipilimumab. Patients treated with anti-PD-1 in combination with anti-CTLA-4 are more likely to have an increased risk of ICIs-induced ITP. Patients with melanoma are at a higher risk of developing ITP when treated with ICI and should be closely monitored for this risk within 60 days of treatment. The potential biological mechanism of ICIs-induced ITP may be related to the dysfunction of megakaryocyte autophagy through the overactivation of the mTOR-related signaling pathway. This study provides a comprehensive understanding of ICIs-induced ITP. Clinicians should pay attention to this potentially fatal adverse reaction.

Safety evaluation of ceftazidime/avibactam based on FAERS database.

To explore adverse event (AE) signals of Ceftazidime/avibactam (CZA) based on the FDA Adverse Event Reporting System (FAERS) database. AE reports primarily associated with CZA were retrieved from the FAERS database from the second quarter of 2015 to the second quarter of 2023. Signal detection was conducted using the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS) methods. A total of 750 AEs reports with CZA as the preferred suspected drug were obtained, identifying 66 preferred terms (PTs) involving 24 system organ classes (SOCs). Besides, the AEs already mentioned in the drug label, this study also revealed some new, clinically valuable potential AEsignals, such as Cholestasis (n = 14, ROR 29.39, PRR 29.15, IC 3.34, EBGM 29.11), Drug-induced liver injury (n = 8, ROR 9.05, PRR 9.01, IC 2.25, EBGM 9.01), Hepatocellular injury (n = 7, ROR 13.90, PRR 13.84, IC 2.41, EBGM 13.63), Haemolytic anaemia (n = 5, ROR 24.29, PRR 24.22, IC 2.42, EBGM 40.53), etc. Additionally, AE signals with higher intensity were identified, such as Hypernatraemia (n = 5, ROR 40.73, PRR 40.61, IC 2.31, EBGM 24.19), Toxic epidermal necrolysis (n = 4, ROR 11.58, PRR 11.55, IC 1.89, EBGM 11.54). Therefore, special vigilance for these potential AEs is warranted when using CZA clinically. This study highlights the potential AEs and risks associated with the clinical use of CZA, particularly the risks related to Cholestasis, Drug-induced liver injury, Haemolytic anaemia, Hypernatraemia, and Toxic epidermal necrolysis.

Analysis of Inclisiran in the US FDA adverse event reporting system (FAERS): a focus on overall patient population and Sex-specific Subgroups.

ABSTRACT Background our study aimed to identify inclisiran-related adverse events(AEs) for primary hypercholesterolemia and arteriosclerotic cardiovascular disease(ASCVD) from the US FDA Adverse Event Reporting System (FAERS) database, analyzing its links to AEs in the overall patient population and sex-specific subgroups to improve medication safety. Methods We analyzed inclisiran-related AEs signals by using statistical methods like Reporting Odds Ratio (ROR), Proportional Reporting Ratios (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma-Poisson Shrinker (MGPS). Results Analyzing 2,400 AE reports with inclisiran as the primary suspected drug in the FAERS database, we identified 70 AE signals over 13 organ systems using the above four methods. Notable findings were strong signals for systemic diseases and various reactions at the site of administration (ROR 1.49, 95% CI 1.41-1.57), and Various musculoskeletal and connective tissue diseases (ROR 4.07, 95% CI 3.83-4.03) in overall and gender-specific populations. Myalgia, a new ADE signal not in the drug insert, was a top signal by intensity and frequency (ROR 14.76, 95% CI 12.84-16.98). Conclusion Our study revealed the strongest AE signals associated with inclisiran in both the overall population and gender subgroups, highlighting potential risks in clinical medication use and guiding balanced clinical decision-making.

Post-marketing safety concerns with abrocitinib: a real-world pharmacovigilance analysis of the FDA adverse event reporting system

ABSTRACT Background Abrocitinib was newly approved for treatment of moderate-to-severe atopic dermatitis. The present study was to assess abrocitinib-related adverse events (AEs) using the Food and Drug Administration Adverse Event Reporting System (FAERS). 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 abrocitinib-related AEs. Results A total of 3,177,744 reports of AEs were collected from the FAERS database, of which 1370 reports were identified with abrocitinib as the primary suspect drug. Abrocitinib-induced adverse events (AEs) occurred across 27 system organ classes (SOCs). A total of 68 preferred terms (PTs) with significant disproportionality, meeting the criteria of all four algorithms simultaneously, were identified. Unexpected significant AEs, such as increased blood cholesterol, venous embolism, hypoacusis, cellulitis, and tuberculosis, might also occur. The median onset time for abrocitinib-associated AEs was 182 days (interquartile range [IQR] 47–527 days). Conclusions The results of this study were consistent with clinical observations. Additionally, unexpected safety signals for abrocitinib were identified, which provided supportive information for the safety profile of abrocitinib. Prospective clinical studies are warranted to validate these findings.

Data mining and safety analysis of avatrombopag: a retrospective pharmacovigilance study based on the US food and drug administration’s adverse event reporting system

With its increasing use in the treatment of thrombocytopenia, avatrombopag’s associated adverse events (AEs) pose a major challenge to its clinical application. This study aims to comprehensively study AEs associated with avatrombopag by using real-world evidence. We curated AE reports for avatrombopag from the first quarter of 2018 to the fourth quarter of 2023 in the US Food and Drug Administration’s Adverse Event Reporting System (FAERS) database. AEs were coded using the Medical Dictionary for Regulatory Activities of Preferred Terms and System Organ Classes. The reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item Gamma-Poisson Shrinker were used to investigate the relationship between avatrombopag and AE reports. Among 9,060,312 reported cases in the FAERS database, 1211 reports listed avatrombopag as “primary suspected” drug. Disproportionality analysis identified 44 preferred terms across 17 organ systems met the criteria for at least one of the four algorithms. The most commonly reported AEs were platelet count decreased (20.2%), headache (16.7%), platelet count increased (11.9%), platelet count abnormal (6.3%), contusion (2.7%), pulmonary embolism (2.3%), and deep vein thrombosis (2.1%). Unexpected AEs such as seasonal allergy, rhinorrhea, antiphospholipid syndrome, ear discomfort, and photopsia were also observed. Excluding the other serious outcomes, hospitalization (34.6%) was the most frequently reported serious outcome, followed by death (15.4%). Most reported AEs occurred within the first 2 days of initiating avatrombopag therapy, and the median onset time was 60 days. We identified new and unexpected AEs with clinical use of avatrombopag, and our results may provide valuable information for clinical monitoring and identifying risks associated with avatrombopag.

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.

The 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. We 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. The 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. We 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. The 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 from January 2019 to June 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 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 AEs 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. 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.

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.