Drug Labels Research Articles

Analysis of ADR reports of cetuximab based on the FDA adverse event reporting system database

This study aims to monitor and identify adverse events (AEs) associated with cetuximab, a drug used to treat various late-stage (metastatic) tumors, to improve patient safety and guide drug use. This study retrospectively analyzed the cases reported in the FDA adverse event reporting system (FAERS) related to the application of cetuximab from 2013 Q1 to 2022 Q4. Disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the empirical Bayesian geometric mean (EBGM) algorithms, were employed to quantify the signals of cetuximab-associated AEs. A total of 8364225 reports were contained in the FAERS database, of which 5186 reports of cetuximab were identified as ‘primary suspected (PS)’ AEs. The application of cetuximab resulted in AEs in 22 system organ classes (SOCs), which preserved 176 significant disproportionality preferred terms (PTs) through the computation of four algorithms. The main SOCs (Skin and subcutaneous tissue disorders, investigations, metabolism and nutrition disorders, and blood and lymphatic system disorders) accounted for 58.63%. Some AEs were not on the drug label: speech disorder, intervertebral discitis, glomerulonephritis rapidly progressive and disseminated intravascular coagulation. This study identified new signals of adverse drug reactions (ADRs) other than those mentioned in the specification associated with cetuximab, providing valuable insights into the relationship between ADRs and cetuximab use. The findings highlight the importance of continuous surveillance to detect and manage AEs effectively, ultimately improving patient safety during treatment with cetuximab.

A Real-World Disproportionality Analysis of Histamine H2-Receptors Antagonists (Famotidine): A Pharmacovigilance Study Based on Spontaneous Reports in the FDA Adverse Event Reporting System.

Famotidine is an H2 receptor antagonist and is currently used on a large scale in gastroenterology. However, Famotidine may also cause severe toxicity to organ systems, including the blood system, digestive system, and urinary system. The objective of this study was to scientifically and systematically investigate the adverse events (AEs) of Famotidine in the real world through the FDA Adverse Event Reporting System (FAERS) database. A disproportionality analysis was used to quantify the signals of AEs associated with Famotidine in FAERS data from the first quarter of 2004 to the first quarter of 2023. The clinical features, onset time, oral and intravenous administration and severe consequences of Famotidine induced AEs were further analyzed. Among the four tests, we found several AEs that were not mentioned in the drug label. For example, abdominal pain upper, abdominal discomfort, dyspepsia, liver disorder, gastrooesophageal reflux disease, and rhabdomyolysis. These AEs are consistent with the drug instructions. Interestingly, we found several unreported AEs, such as: cerebral infarction, hypocalcaemia, hallucination, visual, hypomagnesaemia, hypoparathyroidism, diabetes insipidus, vulvovaginal candidiasis, retro-orbital neoplasm, neuroblastoma recurrent, and malignant cranial nerve neoplasm. Most of our findings are consistent with clinical observations and drug labels, and we also found possible new and unexpected AEs signals, which suggest the need for prospective clinical studies to confirm these results and explain their relationships. Our findings provide valuable evidence for further safety studies.

Post-Marketing Safety of Temozolomide: A Pharmacovigilance Study Based on the Food and Drug Administration Adverse Event Reporting System

Introduction: Temozolomide (TMZ) is a widely used chemotherapy agent for the treatment of malignant gliomas and other brain tumors. Despite its established therapeutic benefits, there is an ongoing need to understand better its safety profile, particularly in real-world clinical settings. This study aimed to identify critical adverse drug reactions (ADRs) associated with TMZ by utilizing the FDA Adverse Event Reporting System (FAERS) database, thereby providing valuable safety insights for clinical practice. Methods: We utilized the reported odds ratio, proportional reporting ratio, Bayesian Confidence Propagation Neural Network, and Empirical Bayes Geometric Mean as primary algorithms for disproportionality analysis. Adverse events (AEs) were classified as ADRs only upon meeting the criteria set by all four algorithms. To ensure the accuracy of our results, we meticulously excluded any AEs deemed unrelated to TMZ. Results: From October 2003 to September 2023, a total of 10,502,538 case reports and 9,073 cases explicitly attributed to TMZ were retrieved from the FAERS database. After applying our filters, 116 ADRs, each with a corresponding Preferred Term (PT), were identified across 18 System Organ Classes (SOCs). The identified ADRs associated with TMZ primarily involved bone marrow suppression, hepatotoxicity, and various infections, notably Pneumocystis jirovecii pneumonia. Furthermore, our analysis identified valuable ADRs not listed in the drug label, including congenital, familial, and genetic disorders at the SOC level, as well as unexpected ADRs at the PT level, such as seizures, pulmonary embolism, and sepsis. Conclusion: This real-world pharmacovigilance study has identified significant and previously unreported ADRs associated with TMZ. Further research for validation and resolution is urgently needed to guide the clinical application of TMZ, ensuring the safety and efficacy of its use in treating brain tumors.

A review on the role of extrapolation as basis for paediatric marketing authorization applications of medicines in the EU.

For new medicines, drug companies obtain regulatory approval on the strategy to generate evidence in the paediatric population, which can be supported by extrapolation of evidence obtained in a reference population. This study investigated whether paediatric marketing authorization applications (PMAAs) supported by extrapolation based on exposure-matching were more successful-i.e. approval of the targeted paediatric population-and efficient-i.e. duration of the drug development-compared to PMAAs not supported by extrapolation. Data was extracted from completed paediatric investigation plans (PIPs), associated drug labels and public assessment reports published on the European Medicines Agency website. Assessment reports were evaluated to assess whether PMAAs were supported by extrapolation based on exposure-matching. Wilcoxon rank-sum tests were used to compare PMAAs supported and not supported by extrapolation based on exposure-matching for outcomes of interest. Exposure-matching supported the benefit/risk assessment of 39.6% of the PMAAs. Targeted and approved minimum age of the paediatric population were comparable for PMAAs where extrapolation based on exposure-matching supported the benefit/risk assessment (2.0 vs. 2.0 years, P-value = .72), but not for PMAAs not supported by extrapolation (0.2years vs. 0.5 years, P-value = .05). Completion of drug development was 5.4years vs. 4.3 years (P = .04) in PMAAs supported by extrapolation based on exposure-matching compared to those not supported by extrapolation, respectively. PMAAs supported by extrapolation based on exposure-matching succeeded more often in obtaining marketing approval in the targeted paediatric population than PMAAs not supported by exposure-matching, but were also less efficient.

P1205 Long-term treatment patterns, dose escalation, and steroid use among patients with moderate-to-severe ulcerative colitis using advanced therapies: >3 years of continuous follow up using IQVIA PharMetrics Plus database

Abstract Background Induction and/or maintenance of remission is seen in less than half of ulcerative colitis (UC) patients with advanced therapies (AT).1,2 This results in frequent switching, dose-optimization, and steroid use to maintain disease control. Long term characterization of these treatment patterns and treatment persistence is needed. Methods This retrospective study used the IQVIA PharMetrics® Plus database (2019-2023) to analyze adults in the United States with moderate-to-severe UC who received at least one AT. Baseline characteristics were assessed 6 months prior to AT initiation (index date). Patients were required to have no evidence of other autoimmune diseases at baseline and ≥3 years of continuous follow-up after AT initiation. Switching was defined as filling a prescription for a different AT than was used in the previous line. We further assessed the number of patients who had no claims for an AT following their index treatment (discontinuation), stratified by whether they had ≥1 year of follow-up after discontinuation. Subsequent lines of therapy were similarly examined. Dose escalation was defined as an increase in AT dose or a shortening of prescription intervals, derived from drug label indications and clinical input. Results Baseline characteristics and treatment patterns are summarized in Figures 1 and 2. The study included 2,188 patients, with a mean age of 38.6 years, of whom 54% were male. The mean follow-up duration was 46.3 months (median: 45.7 months). Among these patients, 28%, 13%, and 4% had no AT fill for at least one year following their last AT fill in the first, second, and third lines of therapy, respectively. Most patients initially received adalimumab, vedolizumab, or infliximab as their first-line AT, and 42% switched therapies at least once. Vedolizumab was the most common second-line AT. In the third and fourth lines, there was greater variation in AT use, with ustekinumab being the most frequent. Around 25-33% of patients experienced a dose escalation at some point in their treatment line. About 40% of patients had a glucocorticoid (prednisone or budesonide) prescription at the time of switching therapies, with usage increasing in later lines. Among patients with discontinuation, 40% used steroids at time or after discontinuing AT. Among patients with at least one year of follow-up after their last AT fill, 23% used steroids after discontinuing AT. Conclusion Advanced therapies for moderate-to-severe UC are associated with high rates of discontinuations, switching and dose escalations. Almost half of all patients completely discontinue AT for ulcerative colitis when followed for 3+ years.

A multidimensional assessment of adverse events associated with paliperidone palmitate: a real-world pharmacovigilance study using the FAERS and JADER databases

ObjectivePaliperidone palmitate is a second-generation antipsychotic that has undergone extensive investigation in clinical trials. However, real-world studies assessing its safety in large populations are lacking. As such, this study aimed to comprehensively evaluate real-world adverse drug events (ADEs) linked to paliperidone palmitate by employing data mining techniques on the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) database and the Japanese Adverse Drug Event Report (JADER) database.MethodsThe study retrieved ADE reports from the FAERS database covering the period from 2009 through the third quarter of 2024, and from the JADER database covering the period from 2013 through the second quarter of 2024. Utilizing disproportionality analyses such as the reporting odds ratios (ROR), proportional reporting ratios (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item Poisson shrinkage (MGPS), significant associations between ADEs and paliperidone palmitate were evaluated.ResultsA total of 27,672 ADE reports related to paliperidone palmitate were identified in FAERS, with 285 significantly disproportionate preferred terms (PTs) identified by all four algorithms. Paliperidone palmitate-associated ADEs encompassed 27 System Organ Classes (SOCs). The top three PTs with the highest reported cases were off-label use, drug ineffective, and hospitalization. Common ADEs included increased blood prolactin, galactorrhea, and schizophrenia, which was consistent with drug label. Noteworthy, unexpected signals not listed in the drug label were also identified, such as psychosexual disorders, prolactin-producing pituitary tumors, suicide attempt, and sudden death. The median onset time for all ADEs was 40 days. Furthermore, gender-based difference in risk signals was detected. Females are more likely to experience elevated blood prolactin and weight increase, whereas males are more prone to sexual dysfunction. Among the 1,065 ADE reports from the JADER database, we identified 51 positive signals, 35 of which overlapped with those found in FAERS, including schizophrenia, hyperprolactinemia, and erectile dysfunction.ConclusionThe study findings from two independent databases serve as crucial references for ensuring the safe of paliperidone palmitate. Additionally, the gender-specific monitoring references provided can enhance clinical surveillance efforts and facilitate more effective risk identification.

Disproportionate adverse event signals of selumetinib in neurofibromatosis type I: insights from FAERS.

Neurofibromatosis type 1 (NF1) is a rare neurogenetic disorder with limited treatment options. Selumetinib, a MEK1/2 inhibitor, has emerged as a promising therapy for inoperable NF1-related plexiform neurofibromas. Our retrospective pharmacovigilance study utilized the FDA Adverse Event Reporting System (FAERS) to comprehensively evaluate Selumetinib's safety profile in real-world settings. Data from the third quarter of 2020 to the fourth quarter of 2023 were analyzed, identifying 498 adverse event reports with Selumetinib as the primary suspect drug. Statistical analysis revealed disproportionate signals for skin and subcutaneous tissue disorders, eye disorders, and various congenital, familial, and genetic disorders. The most common adverse events were elevated blood creatine phosphokinase, rash, and acneiform dermatitis. Notably, several adverse events, including rhabdomyolysis, were identified but not listed on the Selumetinib product label, based on a comparison with the FDA drug labeling. The study underscores the importance of early detection and management of adverse reactions associated with Selumetinib, particularly within the initial month of treatment. These findings provide valuable insights for clinicians and regulators to ensure the safe and effective use of Selumetinib in NF1 patients.

Drug-induced urinary retention: a real-world pharmacovigilance study using FDA and Canada vigilance databases.

Urinary retention (UR) is a clinical condition where patients cannot fully empty their bladder. Although numerous drugs are associated with UR, comprehensive and reliable studies identifying drugs that induce UR are scarce. This study leveraged data from the FDA Adverse Event Reporting System (FAERS) and the Canadian Vigilance Adverse Reaction (CVAR) database to explore adverse events (AEs) related to UR from 2004 to Q1 2024. The top 50 drugs were analyzed for annual reporting trends using linear regression. Disproportionality analysis using the reporting odds ratio (ROR) method, with P-values adjusted via Bonferroni correction, identified significant signals, which were then validated against drug labels and re-evaluated using the CVAR database. Time-to-onset analysis was also performed. From 2004 to Q1 2024, FAERS recorded 17,785,793 AEs, with 16,183 (0.09%) identified as UR cases. The median age among these cases was 65years, with males comprising 53.4%. There were significant annual increases in UR reports associated with antineoplastic agents (0.19% per year) and antidiabetic drugs (0.09% per year), while reports linked to bronchodilators decreased (-0.53% per year). Disproportionality analysis revealed significant signals for 34 drugs (68%), with the highest RORs observed in Fesoterodine, Mirabegron, and Solifenacin. Initial signal detection identified potential new UR signals for Abiraterone, Valacyclovir, Fluoxetine, Empagliflozin, Clopidogrel, and Amlodipine, with CVAR confirming signals for Abiraterone, Fluoxetine, and Empagliflozin. The median time to onset of UR was 29days, with over half of the cases occurring within 30days of initiating medication. The study identifies a rising trend in drug-related UR reports over the past 2 decades. The validation of new signals for Abiraterone, Fluoxetine, and Empagliflozin underscores the critical need for continuous drug safety monitoring and targeted research to better understand the mechanisms behind drug-induced UR.

Application of Generative Artificial Intelligence Models for Accurate Prescription Label Identification and Information Retrieval for the Elderly in Northern East of Thailand.

This study introduces a novel AI-driven approach to support elderly patients in Thailand with medication management, focusing on accurate drug label interpretation. Two model architectures were explored: a Two-Stage Optical Character Recognition (OCR) and Large Language Model (LLM) pipeline combining EasyOCR with Qwen2-72b-instruct and a Uni-Stage Visual Question Answering (VQA) model using Qwen2-72b-VL. Both models operated in a zero-shot capacity, utilizing Retrieval-Augmented Generation (RAG) with DrugBank references to ensure contextual relevance and accuracy. Performance was evaluated on a dataset of 100 diverse prescription labels from Thai healthcare facilities, using RAG Assessment (RAGAs) metrics to assess Context Recall, Factual Correctness, Faithfulness, and Semantic Similarity. The Two-Stage model achieved high accuracy (94%) and strong RAGAs scores, particularly in Context Recall (0.88) and Semantic Similarity (0.91), making it well-suited for complex medication instructions. In contrast, the Uni-Stage model delivered faster response times, making it practical for high-volume environments such as pharmacies. This study demonstrates the potential of zero-shot AI models in addressing medication management challenges for the elderly by providing clear, accurate, and contextually relevant label interpretations. The findings underscore the adaptability of AI in healthcare, balancing accuracy and efficiency to meet various real-world needs.

Pharmacologically induced autoimmune encephalitis—disproportionality analysis utilizing FAERS database

ABSTRACT Background Autoimmune encephalitis (AE) is a neuroimmune disorder that presents significant diagnostic challenges. The FDA Adverse Event Reporting System (FAERS) database can help explore the relationship between drugs and AE, but comprehensive studies are lacking. This study aims to analyze the association between drugs and AE using the FAERS database, providing insights for clinical practice and pharmacovigilance. Research Design and Methods Adverse event reports in the FAERS database were analyzed, focusing on the incidence of drug-induced AE, as well as characteristics such as gender and age. Multiple statistical methods were employed to assess the association between drugs and adverse reactions. Results The study revealed that drug-induced AE predominantly occurred in individuals aged 41 and above, with a higher prevalence among female patients. Nivolumab and pembrolizumab were among the drugs most frequently reported for adverse drug reactions. However, only a minority of drug labels mentioned these adverse reactions. Conclusion This study underscores the potential risk of drug-induced AE, advocating for close monitoring in clinical practice. Further epidemiological investigations are warranted to elucidate the exact relationship between drugs and these disorders. While the FAERS database provides crucial leads for such research, additional studies and validation are necessary.

Adverse drug events associated with metreleptin administration: a real-world pharmacovigilance study from 2014 to 2024 using the FAERS database

ABSTRACT Background This study analyzed adverse drug event (ADE) signals associated with metreleptin using the FDA Adverse Event Reporting System (FAERS) to provide insights for safe clinical use. Research design and methods Data from 1 January 2014, to 31 March 2024, were extracted. Signal intensity for adverse events was assessed using reporting odds ratio (ROR), Medicines and Healthcare Products Regulatory Agency (MHRA), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS) methods. Time-to-onset (TTO) correlations were evaluated using the Weibull shape parameter (WSP). Logistic regression identified potential hospitalization risk factors. Results 4,000 ADE reports were identified, with 1,025 significant events mainly involving females (66.73%) and reported by healthcare professionals (67.80%), primarily from the United States (84.10%). 101 preferred term (PT) signals were confirmed by all methods, with 57 PTs not listed on the drug label. Overall TTO was 547 days (IQR: 113–1325), with gastrointestinal disorders and investigations as hospitalization risk factors. Conclusions This study provides critical insights into the TTO of ADEs related to metreleptin, informing safe clinical application and emphasizing the importance of monitoring potential side effects.

Applications of deep learning in Alzheimer’s disease: a systematic literature review of current trends, methodologies, challenges, innovations, and future directions

Alzheimer’s Disease (AD) constitutes a significant global health issue. In the next 40 years, it is expected to affect 106 million people. Although more and more people are getting AD, there are still no effective drugs to treat it. Insightful information about how important it is to find and treat AD quickly. Recently, Deep Learning (DL) techniques have been used more and more to diagnose AD. They claim better accuracy in drug reuse, medication recognition, and labeling. This essay meticulously examines the works that have talked about using DL with Alzheimer’s disease. Some of the methods are Natural Language Processing (NLP), drug reuse, classification, and identification. Concerning these methods, we examine their pros and cons, paying special attention to how easily they can be explained, how safe they are, and how they can be used in medical situations. One important finding is that Convolutional Neural Networks (CNNs) are most often used for AD research and Python is most often used for DL issues. Some security problems, like data protection and model stability, are not looked at enough in the present research, according to us. This study thoroughly examines present methods and also points out areas that need more work, like better data integration and AI systems that can be explained. The findings should help guide more research and speed up the creation of DL-based AD identification tools in the future.

Congenital anomalies associated with the use of cardiovascular drugs during pregnancy: a large-scale data analysis from the FAERS database

ABSTRACT Background Cardiovascular drugs can cross the placenta during pregnancy, potentially exposing the fetus to teratogenic effects. However, ethical constraints on clinical trials with pregnant women limit safety data and result in inadequate drug labeling. Research Design and Methods Using the FAERS database (2004–2023), we conducted a retrospective pharmacovigilance study analyzing adverse event reports involving congenital anomalies in newborns (<28 days). Signal detection methods included Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS). Our analysis concentrated on the systems or organs involved in the signals, particularly those with higher report counts or signal values, to explore the association between drugs and congenital abnormalities. Results Among 6,208 cases of congenital anomalies in newborns, 387 were linked to cardiovascular drugs, generating 97 signals for 16 drugs. Strong signals included sartans (renal failure, skeletal deformity), metoprolol (hypospadias, large-for-dates baby), amlodipine (gastrointestinal malformations), and statins, furosemide, and spironolactone (dysmorphism). Conclusions Enhanced monitoring is recommended for fetal malformations in women exposed to these drugs before or during pregnancy. While our findings suggest associations, they do not establish causality, highlighting the need for further research to ensure medication safety during pregnancy.

Postmarketing Safety Surveillance of Topiramate: A Signal Detection and Analysis Study Based on the FDA Adverse Event Reporting System Database.

This study aims to investigate the occurrence of adverse events associated with topiramate by analyzing data from the FDA Adverse Event Reporting System. The goal is to provide a basis for the safe clinical use of topiramate. Adverse event data from the FDA Adverse Event Reporting System, from its inception through the first quarter of 2024, were extracted. Signal detection was conducted using three methods: the reporting odds ratio, the medicines and healthcare products regulatory agency method, and the Bayesian confidence propagation neural network. Adverse events were statistically analyzed according to the preferred term and system organ class classifications from the Medical Dictionary for Regulatory Activities version 27.0. Positive signals were then compared against the drug label and the Important Medical Event list. A total of 12,168 adverse event reports involving topiramate as the primary suspect were analyzed, resulting in the extraction of 244 positive signals across 15 system organ classes. Among these, 21 signals were identified as serious adverse reactions not included in the drug label, encompassing 5 system organ classes. Notable signals included hypospadias, spina bifida, abortion spontaneous, renal tubular dysfunction, uveitis, retinal detachment, and choroidal effusion. Additionally, signals such as osmotic demyelination syndrome and Arnold-Chiari malformation were identified as requiring further monitoring. This study identified several unexpected and serious adverse reaction signals that align with previously reported cases. These findings underscore the need for ongoing study, focused attention, and vigilant monitoring during the clinical use of topiramate.

Safety assessment of tafamidis: a real-world adverse event analysis from the FAERS database

ABSTRACT Background Tafamidis emerged as the first FDA-approved drug for treating termed amyloid fibrils. This study aims to analyze adverse events (AEs) related to tafamidis from the second quarter (Q2) of 2019 to the fourth quarter (Q4) of 2023 from the FDA adverse event reporting system (FAERS) database. Research design and methods The AE data related to tafamidis from 2019 Q2 to 2023 Q4 were collected and standardized. Various signal quantification techniques, including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker, were employed for analysis. Results Among the 8742 AE reports with tafamidis as the primary suspected drug, 180 preferred terms of AEs spanning 27 different system organ classes were identified. Unique adverse events to tafamidis included renal and urinary disorders and ear and labyrinth disorders, with not mentioned in the official drug label. Additionally, uncommon but significantly strong AE signals, such as blood culture positive and acquired hemophilia, were observed. Common AEs with relatively high occurrence rates included death, off-label use, fall, hypoacusis, and dysphagia. Conclusion These findings offer valuable insights for optimizing the use of tafamidis and reducing potential side effects, thereby facilitating its safe use in clinical settings.

In vitro human ion channel assays predictive of drug-induced seizure.

Seizure is among the most severe FDA black box warnings of neurotoxicity reported on drug labels. Gaining a better mechanistic understanding of off-targets causative of seizure will improve the identification of potential seizure risks preclinically. In the present study, we evaluated an in vitro panel of 9 investigational (Cav2.1, Cav3.2, GlyRA1, AMPA, HCN1, Kv1.1, Kv7.2/7.3, NaV1.1, Nav1.2) and 2 standard (GABA-A, NMDA) ion channel targets with strong correlative links to seizure, using automated electrophysiology. Each target was assessed with a library of 34 preclinical compounds and 10 approved drugs with known effects of convulsion in vivo and/or in patients. Cav2.1 had the highest frequency of positive hits, 20 compounds with an EC30 or IC30 ≤ 30 µM, and the highest importance score relative to the 11 targets. An additional 35 approved drugs, with categorized low to frequent seizure risk in patients, were evaluated in the Cav2.1 assay. The Cav2.1 assay predicted preclinical compounds to cause convulsion in nonclinical species with a sensitivity of 52% and specificity of 78%, and approved drugs to cause seizure in nonclinical species or in patients with a sensitivity of 48% or 54% and specificity of 71% or 78%, respectively. The integrated panel of 11 ion channel targets predicted preclinical compounds to cause convulsion in nonclinical species with a sensitivity of 68%, specificity of 56%, and accuracy of 65%. This study highlights the utility of expanding the in vitro panel of targets evaluated for seizurogenic activity, in order to reduce compound attrition early on in drug discovery.

A real-world pharmacovigilance study of neuroleptic malignant syndrome based on FDA adverse event reporting system.

Neuroleptic malignant syndrome (NMS) is a rare but potentially life-threatening adverse drug reaction. This study aims to identify the most prevalent drugs associated with the risk of NMS according to the United States Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database. Analyses were performed using data from the FAERS database from January 2004 to June 2024. Single-drug signals were evaluated using the reporting odds ratio (ROR), proportional reporting ratio (PRR), information component (IC), and empirical Bayes geometric mean (EBGM). Meanwhile, comparisons were performed with drug labels. Additionally, subgroup analysis was conducted, focusing on adverse drug reaction signals among populations of different genders and age groups. A total of 10,433 adverse event reports related to NMS were identified, with the top 50 drugs ranked by ROR mainly involving antipsychotics (18, 36%), antiparkinson drugs (10, 20%), antidepressants (7, 14%), antiepileptics (3, 6%), anxiolytics (3, 6%), as well as hypnotics and sedatives (3, 6%). NMS is more prevalent in males (5,713, 54.76%). Among the top 20 drugs with the strongest signal strength, the pediatric group showed an additional presence of benzodiazepines and antiepileptic drugs compared to the adult group. The current comprehensive pharmacovigilance study identified more drugs associated with NMS and provides references to clinicians for clinical practice. Also, further research is needed to investigate the causal relationship between these drugs and NMS.

Background Factors Contributing to Safety Warning Discordance in the Initial Labeling of New Drugs in Japan, the United States, and the European Union.

Drug labels summarize essential safety information for healthcare professionals and patients. However, studies have reported a discordance of safety information in drug labeling among countries/regions. We aimed to identify the characteristics of adverse events associated with discordant safety warnings during the initial labeling of new drugs approved at approximately the same time in Japan, the United States, and the European Union. Safety warning discordance/concordance between two countries/regions and the explanatory variables were assessed using multivariable logistic regression. The safety warning concordance rate was 71.0% (152/214) for the United States and the European Union, 59.5% (135/227) for Japan and the United States, and 64.3% (144/224) for Japan and the European Union. A significant association with discordant safety warnings was revealed for "adverse event rate" and "warning status in a similar drug" between the United States and the European Union; "adverse event rate," "adverse event included in important medical event list," and "warning status in a similar drug" between Japan and the United States; and "adverse event included in important medical event list" and "warning status in a similar drug" between Japan and the European Union. Clarifying and publicizing the reasons for safety warnings, along with an awareness of the factors associated with the discordance identified in this study, will help healthcare professionals, patients, marketing authorization holders, and regulatory authorities around the world share the background of country/region-specific warnings, reducing the possibility of confusion among them due to the discrepancies.

Students’ Engagement in Learning Nursing Pharmacotherapeutics: A Self-reported Volunteer Experience

Hands-on experiential learning within a clinical setting and the integration and translation of theoretical knowledge to practice have been explored as pedagogical methods to enhance nursing education. This study reports nursing students’ self-assessment of volunteer learning experience at hospitals and community pharmacies to enhance nursing pharmacologic knowledge. The study quantitatively evaluated the self-reported assessment of nursing students at hospital and community pharmacies in Belize using a convenient sampling technique. Forty-six nursing students spent 48 hours at assigned community and hospital pharmacies under the supervision of a licensed pharmacist. Self-assessment questionnaires and the grades from preceptors were analysed and reported. Students described a positive experience with high mean scores indicating self-reported learning of new medications, drug side effects, labelling of drugs, dispensing prescriptions, patients’ assessment, communication and experience working alongside interprofessional healthcare team members. This study shows that undergraduate nursing students can benefit from volunteer learning at community and hospital-based pharmacies to enhance hands-on learning of pharmacotherapeutics knowledge. Daily interactions with pharmacists, medications and patients complemented students’ learning of medications and skills acquisition. Nursing educators should explore nonconventional pedagogical approaches, such as pharmacy clinical sites, to complement students’ pharmacologic learning.

Signal detection and analysis of adverse events associated with Genvoya® based the FAERS database.

This study aims to evaluate and understand the safety profile of Genvoya® by mining and analyzing adverse drug event (ADE, adverse drug event) reports from the FDA Adverse Event Reporting System (FAERS, FDA Adverse Event Reporting System) database, thus providing valuable reference information for individuals infected with HIV. Data were obtained from the FAERS database, covering the period from the first quarter of 2015 to the fourth quarter of 2023, focusing on reports where Genvoya® was the primary suspected drug. Data import and extraction were conducted using MySQL 8.0, with adverse events standardized according to the Medical Dictionary for Regulatory Activities (MedDRA, Medical Dictionary for Regulatory Activities) 27.0 terminology. Potential adverse event signals were identified through disproportionality analysis, including the reporting odds ratio (ROR, reporting odds ratio) method and the comprehensive standard by the Medicines and Healthcare products Regulatory Agency (MHRA, Medicines and Healthcare products Regulatory Agency) method. Statistical analyses and graphical representations were performed. A total of 2, 376 adverse drug event reports related to Genvoya® were analyzed. Reports from male patients accounted for 74.33%, while those from female patients accounted for 22.39%. Common adverse events included weight gain, drug interactions, and increased viral load. Additionally, new potential adverse reactions, such as fat redistribution, HIV-associated neurocognitive disorders, and meningoencephalitis, were identified. These reactions were not adequately described in the existing literature and drug labels. Multiple adverse reactions were observed with the use of Genvoya®. Clinicians should closely monitor these reactions and implement necessary preventive and intervention measures based on patient-specific conditions and treatment guidelines. Although this study has limitations, the analysis of FAERS database data has revealed various potential risks associated with Genvoya®, providing important safety references for HIV treatment.