UNASSIGNED: This research focused on meticulously tracking and identifying adverse reactions associated with leuprorelin, a drug prescribed for conditions such as prostate cancer, endometriosis, uterine fibroids, and early-onset puberty. The main objective was to enhance patient safety and offer informed guidance on the appropriate use of this treatment.
UNASSIGNED: From the first quarter of 2004 to the fourth quarter of 2023, a comprehensive analysis was conducted on a significant number of adverse event reports (AERs) from the FDA Adverse Event Reporting System (FAERS) database. Data mining with dismutation analysis was conducted to quantify signals associated with adverse events (AEs) related to leuprorelin, utilizing powerful algorithms such as ROR, PRR, BCPNN, and EBGM.
UNASSIGNED: A total of 102 positive reaction terms (PT) spanning 24 System Organ Classes (SOCs) were identified from an analysis of 60,709 reports associated with leuprorelin use. Notably, several previously unrecognized adverse reactions were uncovered, including Artificial Menopause, Ovarian Adhesion, Follicular Cystitis, Intercepted product preparation error, among others. These findings underscore the importance of exercising additional vigilance regarding the potential adverse effects of leuprorelin, such as Abscess Sterile, Injection site granuloma, Intercepted medication error, and Bulbospinal muscular atrophy congenital.
UNASSIGNED: This research has successfully uncovered new and unforeseen signals associated with adverse drug reactions (ADRs) following leuprorelin administration. The study provides valuable insights into the intricate connection between ADRs and leuprorelin usage. The results underscore the crucial significance of continuous surveillance and meticulous monitoring to promptly identify and manage AEs, ultimately enhancing patient safety and well-being while undergoing leuprorelin therapy.

UNASSIGNED: The primary aim of this study was to closely monitor and identify adverse events (AEs) linked to lenvatinib, a pharmacotherapeutic agent employed for the management of renal cell carcinoma, thyroid cancer, and hepatocellular carcinoma. The ultimate goal was to optimize patient safety and provide evidence-based guidance for the appropriate utilization of this medication.
UNASSIGNED: A comprehensive collection and analysis of reports from the FDA Adverse Event Reporting System (FAERS) database was conducted, encompassing the period from the first quarter of 2015 to the first quarter of 2023. Disproportionality analysis, employing robust algorithms including ROR, PRR, BCPNN, and EBGM was employed for effective data mining to quantify signals associated with lenvatinib-related AEs.
UNASSIGNED: Among the collected reports, a total of 15,193 cases were identified where lenvatinib was the \"primary suspected (PS)\" drug, resulting in 50,508 lenvatinib-induced AEs. An analysis was conducted to examine the occurrence of lenvatinib-induced adverse drug reactions (ADRs) across 26 organ systems. The findings revealed the presence of expected ADRs, including diarrhea, vomiting, stomatitis, hepatic encephalopathy, decreased appetite, dehydration, decreased weight, and electrolyte imbalances, which were consistent with the information provided in the drug labels. Furthermore, unexpected significant ADRs were observed at the preferred terms (PT) level, such as interstitial lung disease, pneumothorax, hypophysitis, failure to thrive, polycythemia, hypopituitarism, spontaneous pneumothorax, pulmonary cavitation, and limbic encephalitis. These findings indicated the potential occurrence of adverse effects that are currently not documented in the drug instructions.
UNASSIGNED: This study has successfully detected novel and unforeseen signals pertaining to ADRs associated with the administration of lenvatinib, thereby contributing significant insights into the intricate correlation between ADRs and the utilization of lenvatinib. The outcomes of this investigation underscore the utmost significance of continuous monitoring and vigilant surveillance in order to promptly identify and effectively manage AEs, consequently enhancing overall patient safety and well-being in the context of lenvatinib therapy.

UNASSIGNED: Ospemifene has been authorized for the treatment of vulvovaginal atrophy (VVA). This study wasto evaluate adverse events (AEs) associated with ospemifene by data mining the US Food and Drug Administration Adverse Event Reporting System (FAERS).
UNASSIGNED: The signals of AEs linked to ospemifene were measured using disproportionality analyses, such as 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.
UNASSIGNED: There were 2283 events of ospemifene being the \'primary suspected (PS)\' AE out of the 12,692,824 reports from the FAERS database. Ospemifene-induced AEs hit 25 organ systems. There were 726 severely disproportional preferred terms (PTs) that complied with the four algorithms. The investigation turned up a number of anticipated adverse drug reactions (ADRs), and significant unanticipated ADRs linked to eye and renal problems were found, indicating potential side effects not yet included in the prescription instructions.
UNASSIGNED: We detected novel AEs signals for ospemifene, and the results of our investigation were compatible with clinical observations. This suggests that further prospective clinical trials are required to confirm these findings and demonstrate their link. Our findings might be useful supporting data for ospemifene safety research in the future.

UNASSIGNED: The aim of this study is to monitor, identify, and compare the adverse events (AEs) related to tenecteplase and alteplase, with the objective of exploring the potential safety of tenecteplase for acute ischemic stroke (AIS) and guiding its use to enhance patient safety.
UNASSIGNED: In order to evaluate the disproportionality of AEs associated with tenecteplase and alteplase in real-world data, four algorithms (ROR, PRR, BCPNN, EBGM) were utilized as measures to detect signals of AEs related to both drugs. Subsequently, Breslow-Day statistical analysis was applied to compare the RORs of the main system organ classes (SOCs) and key preferred terms (PTs) between tenecteplase and alteplase.
UNASSIGNED: A statistical analysis was performed utilizing data gleaned from the Food and Drug Administration Adverse Event Reporting System (FAERS) database, encompassing 19,514,140 case reports from 2004Q1 to 2023Q1. There were 1,004 cases where tenecteplase was reported as the primary suspected (PS) and 2,363 tenecteplase-related adverse drug reactions (ADRs) at the PTs level were identified, the two data of alteplase were 10,945 and 25,266, respectively. The occurrence of drug-induced ADRs was analyzed across 27 organ systems, The analysis revealed several expected ADRs, such as Haemorrhage, Hypersensitivity which were consistent with the two drug-labels. It is of note that the signal strengths of \'death,\' \'ventricular fibrillation,\' \'cardiogenic shock\' and \'pneumonia aspiration\' at the PT level were markedly higher for tenecteplase than for alteplase, whereas the signal strength of \'angioedema\' at the PT level was significantly higher for alteplase in comparison to tenecteplase. Additionally, unexpected significant ADRs associated with ocular adverse reactions and pneumonia aspiration at the PT level were identified, indicating potential AEs not currently mentioned in the drug instructions.
UNASSIGNED: This study identified and compared signals of ADRs associated with tenecteplase and alteplase, although tenecteplase is as effective as alteplase and has advantages such as ease of use and affordability, it cannot replace alteplase in the treatment of AIS until its safety profile is fully recognized. Additionally, previously unreported ocular ADRs and pneumonia were identified, providing valuable insights into the relationship between ADRs and the use of these thrombolytic drugs. These findings underscore the importance of continuous monitoring and effective detection of AEs to ultimately enhance the safety of AIS patients undergoing thrombolytic therapy.

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UNASSIGNED: The objective of this study was to monitor and identify adverse events (AEs) associated with topotecan, a medication used for the treatment of solid tumors, in order to improve patient safety and guide medication usage.
UNASSIGNED: To assess the disproportionality of topotecan-related AEs in real-world data, four algorithms (ROR, PRR, BCPNN, and EBGM) were employed as measures to detect signals of topotecan-associated AEs.
UNASSIGNED: A statistical analysis was conducted using data from the FAERS database, encompassing 9,511,161 case reports from 2004Q1 to 2021Q4. Among these reports, 1,896 were identified as primary suspected (PS) AEs related to topotecan, and 155 topotecan-related adverse drug reactions (ADRs) at the preferred terms (PTs) level were selected. The occurrence of topotecan-induced ADRs was analyzed across 23 organ systems. The analysis revealed several expected ADRs, such as anemia, nausea, and vomiting, which were consistent with the drug labels. Additionally, unexpected significant ADRs associated with eye disorders at the system organ class (SOC) level were identified, indicating potential adverse effects not currently mentioned in the drug instructions.
UNASSIGNED: This study identified new and unexpected signals of adverse drug reactions (ADRs) related to topotecan, providing valuable insights into the relationship between ADRs and topotecan usage. The findings highlight the importance of ongoing monitoring and surveillance to detect and manage AEs effectively, ultimately improving patient safety during topotecan treatment.

It is well-known that a spontaneous reporting system suffers from significant under-reporting of adverse drug reactions from the source population. The existing methods do not adjust for such under-reporting for the calculation of measures of association between a drug and the adverse drug reaction under study. Often there is direct and/or indirect information on the reporting probabilities. This work incorporates the reporting probabilities into existing methodologies, specifically to Bayesian confidence propagation neural network and DuMouchel\'s empirical Bayesian methods, and shows how the two methods lead to biased results in the presence of under-reporting. Considering all the cases to be reported, the association measure for the source population can be estimated by using only exposure information through a reference sample from the source population.

OBJECTIVE: For disproportionality measures based on the Relative Reporting Ratio (RRR) such as the Information Component (IC) and the Empirical Bayesian Geometrical Mean (EBGM), each product and event is assumed to represent a negligible fraction of the spontaneous report database (SRD). Here, we provide the tools for allowing signal detection experts to assess the consequence of the violation of this assumption on their specific SRD.
METHODS: For each product-event pair (P-E), a worst-case scenario associated all the reported events-of-interest with the product of interest. The values of the RRR under this scenario were measured for different sets of stratification factors using the GlaxoSmithKline vaccines SRD. These values represent the RRR upper bound that RRR cannot exceed whatever the true strength of association.
RESULTS: Depending on the choice of stratification factors, the RRR could not exceed an upper bound of 2 for up to 2.4% of the P-Es. For Engerix™, 23.4% of all reports in the SDR, the RRR could not exceed an upper bound of 2 for up to 13.8% of pairs. For the P-E Rotarix™-Intussusception, the choice of stratification factors impacted the upper bound to RRR: from 52.5 for an unstratified RRR to 2.0 for a fully stratified RRR.
CONCLUSIONS: The quantification of the upper bound can indicate whether measures such as EBGM, IC, or RRR can be used for SRD for which products or events represent a non-negligible fraction of the entire SRD. In addition, at the level of the product or P-E, it can also highlight detrimental impact of overstratification.