Medical Dictionary For Regulatory Activities Research Articles

Exploring the Landscape of Immune Checkpoint Inhibitor-Induced Adverse Events Through Big Data Mining of Pan-Cancer Clinical Trials.

Immune checkpoint inhibitors (ICIs) have significantly improved the survival of patients with cancer and provided long-term durable benefit. However, ICI-treated patients develop a range of toxicities known as immune-related adverse events (irAEs), which could compromise clinical benefits from these treatments. As the incidence and spectrum of irAEs differs across cancer types and ICI agents, it is imperative to characterize the incidence and spectrum of irAEs in a pan-cancer cohort to aid clinical management. We queried >400 000 trials registered at ClinicalTrials.gov and retrieved a comprehensive pan-cancer database of 71 087 ICI-treated participants from 19 cancer types and 7 ICI agents. We performed data harmonization and cleaning of these trial results into 293 harmonized adverse event categories using Medical Dictionary for Regulatory Activities. We developed irAExplorer (https://irae.tanlab.org), an interactive database that focuses on adverse events in patients administered with ICIs from big data mining. irAExplorer encompasses 71 087 distinct clinical trial participants from 343 clinical trials across 19 cancer types with well-annotated ICI treatment regimens and harmonized adverse event categories. We demonstrated a few of the irAE analyses through irAExplorer and highlighted some associations between treatment- or cancer-specific irAEs. The irAExplorer is a user-friendly resource that offers exploration, validation, and discovery of treatment- or cancer-specific irAEs across pan-cancer cohorts. We envision that irAExplorer can serve as a valuable resource to cross-validate users' internal datasets to increase the robustness of their findings.

Evaluating MedDRA-to-ICD terminology mappings

BackgroundIn this era of big data, data harmonization is an important step to ensure reproducible, scalable, and collaborative research. Thus, terminology mapping is a necessary step to harmonize heterogeneous data. Take the Medical Dictionary for Regulatory Activities (MedDRA) and International Classification of Diseases (ICD) for example, the mapping between them is essential for drug safety and pharmacovigilance research. Our main objective is to provide a quantitative and qualitative analysis of the mapping status between MedDRA and ICD.We focus on evaluating the current mapping status between MedDRA and ICD through the Unified Medical Language System (UMLS) and Observational Medical Outcomes Partnership Common Data Model (OMOP CDM). We summarized the current mapping statistics and evaluated the quality of the current MedDRA-ICD mapping; for unmapped terms, we used our self-developed algorithm to rank the best possible mapping candidates for additional mapping coverage.ResultsThe identified MedDRA-ICD mapped pairs cover 27.23% of the overall MedDRA preferred terms (PT). The systematic quality analysis demonstrated that, among the mapped pairs provided by UMLS, only 51.44% are considered an exact match. For the 2400 sampled unmapped terms, 56 of the 2400 MedDRA Preferred Terms (PT) could have exact match terms from ICD.ConclusionSome of the mapped pairs between MedDRA and ICD are not exact matches due to differences in granularity and focus. For 72% of the unmapped PT terms, the identified exact match pairs illustrate the possibility of identifying additional mapped pairs. Referring to its own mapping standard, some of the unmapped terms should qualify for the expansion of MedDRA to ICD mapping in UMLS.

Dabigatran-related serious medication errors: an analysis using data from VigiBase

ObjectiveTo analyze the serious medication errors (MEs) on dabigatran, and their related factors, in order to avoid or reduce the occurrence of adverse events.MethodsSerious MEs related to dabigatran were extracted from the WHO global database of reported potential side effects of medicinal products (VigiBase) by using “Medication errors and other product use errors and issues” High Level Group Term (HLGT) of the international Medical Dictionary for Regulatory Activities (MedDRA). Well-documented reports, vigiGrade completeness score ≥ 0.80, or with an informative narrative were analyzed with a focus on the clinical features of the cases. The PCNE Classification for drug-related problems (DRP) was used to classify medication errors in our analysis of cases.ResultsUntil January 26, 2020, there were 453 cases with serious MEs related to dabigatran in VigiBase, and 113 were well-documented. Among these, 69 patients (61%) were hospitalized or had prolonged hospitalization, 16 (14%) had life-threatening events, and 12 (11%) died. The MEs occurred in the prescription phase in 77 cases, in administration in 35, and at the dispensing stage in one case. The MEs in prescription were related to a drug selection error in 44 cases (24 concerning contraindications and 20 drug interactions) and to dose error in 33 cases (17 with excessive dose; eight with insufficient frequency; four had an incorrect time; in three, the dose was too low; and in one, too frequent). The MEs in administration were medical-staff-related errors in five cases (three with wrong administration route, one administration omission, and one overdose), patient-related errors in 28 (14 insufficient dose or no administration, seven improper drug storage, four wrong administration method, and three over prescribed dose), and other errors in two (without efficacy monitoring). The dispensing error of a wrong drug strength occurred in a pharmacy. The main adverse events in the 113 patients were haemorrhage in 57 cases (50%) and ischemia in 29 cases (26%).ConclusionBased on the analysis of reports in VigiBase, serious MEs related to dabigatran mainly occurred during prescription and administration. Although the incidence of MEs with clinical consequences in the use of dabigatran cannot be determined, attention should be paid to selection of the appropriate dose to a right patient in the prescription, and to patient compliance and storage in drug administration. The patient harm mainly manifested itself as bleeding or ischemia including fatal outcome in rare patients.

A Model for Monitoring Spontaneously Reported Medication Errors Using the Adjuvanted Recombinant Zoster Vaccine as an Example.

A European legislation was put in place for the reporting of medication errors, and guidelines were drafted to help stakeholders in the reporting, evaluation, and, ultimately, minimization of these errors. As part of pharmacovigilance reporting, a proper classification of medication errors is needed. However, this process can be tedious, time-consuming, and resource-intensive. To fulfill this obligation regarding medication errors, we developed an algorithm that classifies the reported errors in an automated way into four categories: potential medication errors, intercepted medication errors, medication errors without harm (i.e., not associated with adverse reaction(s)), and medication errors with harm (i.e., associated with adverse reaction(s)). A fifth category ("conflicting category") was created for reported cases that could not be unambiguously classified as either potential or intercepted medication errors. Our algorithm defines medication error categories based on internationally accepted terminology using the Medical Dictionary for Regulatory Activities (MedDRA®) preferred terms. We present the algorithm and the strengths of this automated way of reporting medication errors. We also give examples of visualizations using spontaneously reported vaccination error data associated with the adjuvanted recombinant zoster vaccine. For this purpose, we used a customized web-based platform that uses visualizations to support safety signal detection. The use of the algorithm facilitates and ensures a consistent way of categorizing medication errors with MedDRA® terms, thereby saving time and resources and avoiding the risk of potential mistakes versus manual classification. This allows further assessment and potential prevention of medication errors. In addition, the algorithm is easy to implement and can be used to categorize medication errors from different databases.

Assessment of safety profile of secukinumab in real-world scenario using United States food and drug administration adverse event reporting system database

Secukinumab is an anti-IL-17 monoclonal antibody approved for treating psoriasis and various arthritides. A comprehensive evaluation of its safety, especially in a real-world setting, is necessary. This study aimed to describe the adverse events (AE) associated with secukinumab use using the United States Food and Drug Administration Adverse Event Reporting System (FAERS) database. FAERS data files containing AE reports from 2015 to 2021 were downloaded for data mining. Primary or secondary suspect medications indicated for psoriasis were identified and analyzed. Medical dictionary for regulatory activities (MedDRA version 24.1) was used to analyze the AE terms. To detect potential safety signals of AE from secukinumab use, disproportionality analysis was used. A total of 365,590 adverse event reports were identified; of these, 44,761 reports involved the use of secukinumab. Safety signals were identified for ocular infections and gastrointestinal adverse events at the standardised MedDRA query level. Safety signals for oral candidiasis, oral herpes, conjunctivitis, eye infections, and ulcerative colitis were identified at the preferred term level. The findings of our study are consistent with those of earlier studies, such as the increased risk of infections and inflammatory bowel disease. However, our study also identified additional safety signals that need to be further evaluated.

Otorhinolaryngologic complications after COVID-19 vaccination, vaccine adverse event reporting system (VAERS).

There have been reports of otolaryngological adverse event following immunization (AEFI) such as instances of olfactory and gustatory dysfunction following COVID-19 vaccination. This study aimed to analyze otolaryngological AEFIs following COVID-19 vaccination. This study was conducted with a secondary data analysis that the Vaccine Adverse Events Reporting System (VAERS) and the COVID-19 Data Tracker, which are both administered by the Centers for Disease Control and Prevention in the US. Using Medical Dictionary for Regulatory Activities (MedDRA) concepts, AEFIs included: Considering the overall frequency and similarity of symptoms in the first 153 PTs, they were grouped into major 19 AEFIs groups. The incidence rates (IRs) of AEFIs per 100,000 were calculated on individual and cumulative AEFIs levels, involving people who received complete primary series and an updated bivalent booster dose with one of the available COVID-19 vaccines in the US. The proportions of AEFIs by age, sex, and vaccine manufacturer were reported. We also calculated the proportional reporting ratio (PRR) of AEFIs. We identified 106,653 otorhinolaryngologic AEFIs from the VAERS database, and a total of 226,593,618 people who received complete primary series in the US. Overall, the IR of total Otorhinolaryngologic AEFIs was 47.068 of CPS (completed primary series) and 7.237 UBB (updated bivalent booster) per 100,000. For most symptoms, being female was associated with statistically significant higher AEFIs. Upon examining the impact of different vaccine manufacturers, the researchers found that Janssen's vaccine exhibited higher IRs for hearing loss (5.871), tinnitus (19.182), ear infection (0.709), dizziness (121.202), sinusitis (2.088), epistaxis (4.251), anosmia (5.264), snoring (0.734), allergies (5.555), and pharyngitis (5.428). The highest PRRs were for Anosmia (3.617), Laryngopharyngeal Reflux - Acid Reflux (2.632), and Tinnitus -Ringing in the ears (2.343), in that order, with these three significantly incidence than other background noises. This study, utilizing an extensive sample sizes, represents a significant step toward comprehensively characterizing the otolaryngological AEFIs associated with COVID-19 vaccinations. This large-scale analysis aims to move beyond isolated case reports and anecdotal evidence, providing a robust and detailed portrait of the otolaryngological AEFIs landscape in response to COVID-19 vaccinations.

Enhancing antidepressant safety surveillance: comparative analysis of adverse drug reaction signals in spontaneous reporting and healthcare claims databases.

Background/Objective: Spontaneous reporting systems (SRS) such as the Korea Adverse Event Reporting System (KAERS) are limited in their ability to detect adverse drug reaction (ADR) signals due to their limited data on drug use. Conversely, the national health insurance claim (NHIC) data include drug use information for all qualifying residents. This study aimed to compare ADR signal profiles for antidepressants between KAERS and NHIC, evaluating the extent to which detected signals belong to common ADRs and labeling information. Materials and Methods: ADR signal detection in KAERS and NHIC databases, spanning January to December 2017, employed disproportionality analysis. Signal classes were determined based on System Organ Class (SOC) of the Medical Dictionary for Regulatory Activities (MedDRA). Also, Common ADR Coverage (CAC), the proportion of detected signals deemed common ADRs, and labeling information coverage (LIC) represented by mean average precision (mAP) were calculated. Additionally, protopathic bias and relative risk (RR) evaluation were performed to check for signal robustness. Results: Signal detection revealed 51 and 62 signals in KAERS and NHIC databases, respectively. Both systems predominantly captured signals related to nervous system disorders, comprising 33.3% (N = 17) in KAERS and 50.8% (N = 31) in NHIC. Regarding the type of antidepressants, KAERS predominantly reported signals associated with tricyclic antidepressants (TCAs) (N = 21, 41.2%), while NHIC produced most signals linked to selective serotonin reuptake inhibitors (SSRIs) (N = 22, 35.5%). KAERS exhibited higher CAC (68.63% vs. 29.03%) than NHIC. LIC was also higher in KAERS than in NHIC (mAP for EB05: 1.00 vs. 0.983); i.e., NHIC identified 5 signals not documented in drug labeling information, while KAERS found none. Among the unlabeled signals, one (Duloxetine-Myelopathy) was from protopathic bias, and two (duloxetine-myelopathy and tianeptine-osteomalacia) were statistically significant in RR. Conclusion: NHIC exhibited greater capability in detecting ADR signals associated with antidepressant use, encompassing unlabeled ADR signals, compared to KAERS. NHIC also demonstrated greater potential for identifying less common ADRs. Further investigation is needed for signals detected exclusively in NHIC but not covered by labeling information. This study underscores the value of integrating different sources of data, offering substantial regulatory insights and enriching the scope of pharmacovigilance.

Lessons learned from annotation of VAERS reports on adverse events following influenza vaccination and related to Guillain-Barré syndrome

BackgroundVaccine Adverse Events ReportingSystem (VAERS) is a promising resource of tracking adverse events following immunization. Medical Dictionary for Regulatory Activities (MedDRA) terminology used for coding adverse events in VAERS reports has several limitations. We focus on developing an automated system for semantic extraction of adverse events following vaccination and their temporal relationships for a better understanding of VAERS data and its integration into other applications. The aim of the present studyis to summarize the lessons learned during the initial phase of this project in annotating adverse events following influenza vaccination and related to Guillain-Barré syndrome (GBS). We emphasize on identifying the limitations of VAERS and MedDRA.ResultsWe collected 282 VAERS reports documented between 1990 and 2016 and shortlisted those with at least 1,100 characters in the report. We used a subset of 50 reports for the preliminary investigation and annotated all adverse events following influenza vaccination by mapping to representative MedDRA terms. Associated time expressions were annotated when available. We used 16 System Organ Class (SOC) level MedDRA terms to map GBS related adverse events and expanded some SOC terms to Lowest Level Terms (LLT) for granular representation. We annotated three broad categories of events such as problems, clinical investigations, and treatments/procedures. The inter-annotator agreement of events achieved was 86%. Incomplete reports, typographical errors, lack of clarity and coherence, repeated texts, unavailability of associated temporal information, difficulty to interpret due to incorrect grammar, use of generalized terms to describe adverse events / symptoms, uncommon abbreviations, difficulty annotating multiple events with a conjunction / common phrase, irrelevant historical events and coexisting events were some of the challenges encountered. Some of the limitations we noted are in agreement with previous reports.ConclusionsWe reported the challenges encountered and lessons learned during annotation of adverse events in VAERS reports following influenza vaccination and related to GBS. Though the challenges may be due to the inevitable limitations of public reporting systems and widely reported limitations of MedDRA, we emphasize the need to understand these limitations and extraction of other supportive information for a better understanding of adverse events following vaccination.

A patient safety knowledge graph supporting vaccine product development

BackgroundKnowledge graphs are well-suited for modeling complex, unstructured, and multi-source data and facilitating their analysis. During the COVID-19 pandemic, adverse event data were integrated into a knowledge graph to support vaccine safety surveillance and nimbly respond to urgent health authority questions. Here, we provide details of this post-marketing safety system using public data sources. In addition to challenges with varied data representations, adverse event reporting on the COVID-19 vaccines generated an unprecedented volume of data; an order of magnitude larger than adverse events for all previous vaccines. The Patient Safety Knowledge Graph (PSKG) is a robust data store to accommodate the volume of adverse event data and harmonize primary surveillance data sources.MethodsWe designed a semantic model to represent key safety concepts. We built an extract-transform-load (ETL) data pipeline to parse and import primary public data sources; align key elements such as vaccine names; integrated the Medical Dictionary for Regulatory Activities (MedDRA); and applied quality metrics. PSKG is deployed in a Neo4J graph database, and made available via a web interface and Application Programming Interfaces (APIs).ResultsWe import and align adverse event data and vaccine exposure data from 250 countries on a weekly basis, producing a graph with 4,340,980 nodes and 30,544,475 edges as of July 1, 2022. PSKG is used for ad-hoc analyses and periodic reporting for several widely available COVID-19 vaccines. Analysis code using the knowledge graph is 80% shorter than an equivalent implementation written entirely in Python, and runs over 200 times faster.ConclusionsOrganizing safety data into a concise model of nodes, properties, and edge relationships has greatly simplified analysis code by removing complex parsing and transformation algorithms from individual analyses and instead managing these centrally. The adoption of the knowledge graph transformed how the team answers key scientific and medical questions. Whereas previously an analysis would involve aggregating and transforming primary datasets from scratch to answer a specific question, the team can now iterate easily and respond as quickly as requests evolve (e.g., “Produce vaccine-X safety profile for adverse event-Y by country instead of age-range”).

Cross-Cancer Type Evaluation of Potential Interstitial Lung Disease Complications of Immune Checkpoint Inhibitors Using JADER.

Interstitial lung disease (ILD) is a serious adverse event caused by the administration of immune checkpoint inhibitors (ICIs). However, only few large-scale studies have explored the association among ICI use, underlying cancer type, and ILD complications. This study aimed to analyze the association between the primary cancer type and ICI-induced ILD in a cross-sectional manner using the Japanese Adverse Drug Event Report (JADER) database. Nivolumab and pembrolizumab (anti-programmed cell death 1 (PD-1) antibodies) and durvalumab, avelumab, and atezolizumab (anti-programmed cell death ligand 1 (PD-L1) antibodies) were included as ICIs in this study. Adverse events were identified based on the preferred terms of Medical Dictionary for Regulatory Activities (MedDRA) version 27.0/J listed in the Standardized MedDRA Queries (SMQ) "interstitial lung disease." The reporting odds ratio was calculated to detect the association between ICI use and ILD complications, and a signal was detected if the lower limit of the 95% confidence interval exceeded 1. In the analysis of all cancer types, a signal was detected for all ICIs except avelumab. An association between ICI and ILD was detected for all cancer types with nivolumab. However, pembrolizumab exhibited a signal only in colorectal cancer. In contrast, anti-PD-L1 antibodies displayed signals in five cancer types, excluding head and neck cancer, which was not reported in JADER. Among these cancer types, atezolizumab exhibited a signal only in breast cancer. The results of this study will help guide the safe use of ICIs based on the underlying cancer type in terms of ILD complications.

A real-world disproportionality analysis of FDA adverse event reporting system (FAERS) events for denosumab.

Denosumab is authorized to treat several diseases, including cancer and bone disorders. Nevertheless, its use in clinical practice has been affected by safety concerns. The work retrospectively investigated adverse events (AEs) of denosumab to better understand toxicities. The FAERS data base data from Q1 of 2010 to Q3 of 2023 was chosen. The definition of Medical Dictionary for Regulatory Activities (MedDRA) was dependent on preferred terms (PTs) and system organ class (SOCs). Following the removal of duplicate reports, a disproportionality analysis was conducted to identify safety signals through the calculation of reporting odds ratios (ROR). During the reporting period, 130611 denosumab-related cases were identified; 670pTs with a substantial disproportionality were retained. The connective and musculoskeletal tissue disorders, poisoning, injury, and procedural complications, as well as medical and surgical procedures, were among the important SOCs that satisfied the criteria. Reports at PT levels including off-label use, death, osteonecrosis of the jaw, arthralgia, and pain in extremities were determined. Severe consequences in terms of life-threatening injuries and death accounted for 841 and 19704 cases, respectively of the reported cases. These findings underscore the critical importance of pharmacovigilance and are consistent with established clinical observations. Notably, osteonecrosis of the jaw, arthralgia, pain in extremities, back pain, myalgia, and bone pain were identified as the most prevalent risk signals associated with denosumab.

Efficient analysis of adverse drug events and toxicological mechanisms of newly marketed drugs by integrating pharmacovigilance and network toxicology: selumetinib as an example.

To integrate pharmacovigilance and network toxicology methods to explore the potential adverse drug events (ADEs) and toxic mechanisms of selumetinib, and to provide a reference for quickly understanding the safety and toxicological mechanisms of newly marketed drugs. Taking selumetinib as an example, this study integrated pharmacovigilance methods based on real-world data and network toxicology methods to analyze its ADE and its potential toxicological mechanism. First, the ADE reports of selumetinib were extracted from the US Food and Drug Administration (FDA) adverse event reporting system (FAERS), and the ADE signals were detected by reporting odds ratio (ROR) and UK medicines and healthcare products regulatory agency (MHRA) methods. The ADE signals were classified and described according to the preferred terms (PTs) and system organ class (SOC) derived from the Medical Dictionary for Regulatory Activities (MedDRA). The network toxicology method was used to analyze the toxicological mechanism of the interested SOCs. The specific steps included predicting the potential targets of selumetinib using TOXRIC, STITCH, ChEMBL, CTD, SwissTargetPreditcion, and Super-PRED databases, collecting the targets of SOC using GeneCards database, conducting protein-protein interaction (PPI) analysis through STRING database, conducting gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis through DAVID database, and testing the molecular affinity using AutoDock software. A total of 1388 ADE reports related to selumetinib were extracted, and 53 positive signals were detected by ROR and MHRA methods, of which 20 signals were not mentioned in the package insert, including ingrowing nail, hyperphosphatemia, cardiac valve disease, hematuria, neutropenia, etc. Analysis of the toxicological mechanism of six SOCs involved in positive ADE signals revealed that the key targets included EGFR, STAT3, AKT1, IL6, BCL2, etc., and the key pathways included PI3K/Akt pathway, apoptosis, ErbB signaling pathway, and EGFR tyrosine kinase inhibitor resistance, etc. Molecular docking assays showed spontaneous binding of selumetinib to key targets in these pathways. The pharmacovigilance analysis identified some new potential ADEs of selumetinib, and the network toxicology analysis showed that the toxic effects of selumetinib may be related to PI3K/Akt pathway, apoptosis, ErbB signaling pathway, EGFR tyrosine kinase inhibitor resistance and other pathways.

Adverse events following COVID-19 vaccination: A comprehensive analysis of spontaneous reporting data in Ghana.

Vaccines are important public health tools and formed part of the fight against the COVID-19 pandemic. Five COVID-19 vaccines were given Emergency Use Authorization in Ghana and deployed during the pandemic. Early phase trials of the vaccines were mostly not conducted in Africans. This study examines safety data during their deployment under real-life conditions in Ghana. This study analysed secondary data on COVID-19 vaccine-related adverse events following immunization (AEFI) reported to the Ghana Food and Drugs Authority (GFDA) between March 2021 and June 2022 using STATA. AEFIs were coded with their Preferred Terms using the Medical Dictionary for Regulatory Activities, version 24.0. Statistical tests examined associations between demographic characteristics, vaccine types, seriousness, and AEFI outcomes. Binary logistic regression model assessed factors associated with serious AEFIs, while the GFDA's Joint COVID-19 Vaccine Safety Review Committee provided causality assessments of serious AEFIs. Overall cumulative incidence of AEFIs was about 25 per 100,000 persons vaccinated. Across the five vaccines, majority of the AEFIs reported were not serious (98.7%) with higher incidences in those below 50 years (74.0%) and females (51.2%). The most common AEFIs recorded were headache (52.9%), pains (44.4%), pyrexia (35.1%), chills (16.7%) and injection site pain (15.6%). Relative to those 50 years and above, the odds of serious AEFI were 60% less among those aged <30 years (aOR = 0.40, CI: [0.19, 0.86], p = 0.019). However, a causality assessment of the 57 serious AEFIs indicated only 8 (14%) were vaccine product-related. There was a low incidence of AEFIs following deployment of the vaccines in Ghana with a much lower incidence of serious AEFIs. Informing the public about the safety of the vaccines and potential side effects may increase trust and acceptance, decreasing hesitancy in current and future vaccination programmes.

Descriptive analysis on disproportionate medication errors and associated patient characteristics in the Food and Drug Administration's Adverse Event Reporting System.

Medication errors (MEs) are a major public health concern which can cause harm and financial burden within the healthcare system. Characterizing MEs is crucial to develop strategies to mitigate MEs in the future. To characterize ME-associated reports, and investigate signals of disproportionate reporting (SDRs) on MEs in the Food and Drug Administration's Adverse Event Reporting System (FAERS). FAERS data from 2004 to 2020 was used. ME reports were identified with the narrow Standardised Medical Dictionary for Regulatory Activities® (MedDRA®) Query (SMQ) for MEs. Drug names were converted to the Anatomical Therapeutic Chemical (ATC) classification. SDRs were investigated using the reporting odds ratio (ROR). In total 488 470 ME reports were identified, mostly (59%) submitted by consumers and mainly (55%) associated with females. Median age at time of ME was 57 years (interquartile range: 37-70 years). Approximately 1 out of 3 reports stated a serious health outcome. The most prevalent reported drug class was "antineoplastic and immunomodulating agents" (25%). The most common ME type was "incorrect dose administered" (9%). Of the 1659 SDRs obtained, adalimumab was the most common drug associated with MEs, noting a ROR of 1.22 (95% confidence interval: 1.21-1.24). This study offers a first of its kind characterization of MEs as reported to FAERS. Reported MEs are frequent and may be associated with serious health outcomes. This FAERS data provides insights on ME prevention and offers possibilities for additional in-depth analyses.

Toxicity Spectrum of Anti-GD2 Immunotherapy: A Real-World Study Leveraging the US Food and Drug Administration Adverse Event Reporting System.

Anti-disialoganglioside (anti-GD2) monoclonal antibodies are effective immunotherapeutic drugs for treating neuroblastoma, yet their toxicity spectrum is unclear. This study aimed to assess the toxicity profiles of three anti-GD2 monoclonal antibodies (dinutuximab, dinutuximab β, and naxitamab) in clinical applications by mining and evaluating the adverse drug reaction (ADR) signals from the US Food and Drug Administration Adverse Event Reporting System. Data in the US Food and Drug Administration Adverse Event Reporting System from the time anti-GD2 monoclonal antibodies became available in the market to the first quarter of 2023 were searched. The signals of anti-GD2 monoclonal antibody-associated ADRs were quantified using four types of algorithms, including the reporting odds ratio, the proportional reporting ratio, the combination of the proportional reporting ratio and χ2 statistic method used by the UK Medicines and Healthcare Products Regulatory Agency, and the Bayesian confidence propagation neural network. The ADRs were categorized by System Organ Class based on the Medical Dictionary for Regulatory Activities, and were sorted according to the frequency and signal strength of ADRs. A total of 370 adverse drug event reports with anti-GD2 monoclonal antibodies listed as the 'primary suspected drugs' were identified, with 116 ADR signals detected, of which 22 were not in the drug labels. Among the adverse drug event reports, 276 reports concerned dinutuximab/dinutuximab β as primary suspected drugs with 90 ADR signals, involving 19 System Organ Classes, of which 21 signals were not in the label; 94 adverse drug event reports concerned naxitamab as the primary suspected drug with 26 ADR signals, involving 11 System Organ Classes, of which one was not in the label. For dinutuximab/dinutuximab β-related ADRs, the top five most frequent were "fever", "abdominal pain", "elevated aspartate aminotransferase (AST)", "elevated alanine aminotransferase (ALT)" and "hypotension"; the top five most intensive signals were "hypoalbuminemia", "elevated AST", "capillary leakage syndrome", "hypoxia" and "elevated ALT". For naxitamab-related ADRs, the top five most frequent were "hypotension", "pain", "urticarial", "hypertension" and "rash"; the top five most intensive signals were "hypotension", "urticaria", "hypoxemia", "bronchospasm" and "hypertension". Involved System Organ Classes included "investigations" and "respiratory, thoracic and mediastinal disorders" containing the most types of ADR signals in dinutuximab/dintuximab β-related ADRs and naxitamab-related ADRs, respectively. Our study comprehensively analyzed the toxicity profiles of anti-GD2 monoclonal antibodies and provides an important reference for clinical monitoring and ADR identification of these drugs.

Sex differences in adverse events from systemic treatments for psoriasis: A decade of insights from the Swiss Psoriasis Registry (SDNTT).

Psoriasis is a disease that often requires prolonged systemic treatment. It is important to determine the safety of available therapies. There is currently little insight into sex-specific differences in the safety of systemic psoriasis therapies. To examine the real-world, long-term safety of systemic psoriasis therapies with sex stratification in drug-related adverse events (ADRs). Ten-year data from adults with moderate-to-severe psoriasis requiring systemic treatment (conventional systemic therapies [CST], biologics) were obtained from the Swiss psoriasis registry (SDNTT). ADRs were categorized according to the international terminology Medical Dictionary for Regulatory Activities (MedDRA). Safety was assessed by calculating event rates per 100 patient-years (PY). We used descriptive statistics for patient and disease characteristics, and binomial and t-tests to compare treatment groups and sex. In total, 791 patients (290 females) were included with a mean age of 46 years. 358 (45%) received CSTs and 433 (55%) biologics; both groups had similar baseline characteristics except for more joint involvement in patients using biologics (26.86% vs. 14.8%, p < 0.0001). CSTs were associated with a 2.2-fold higher ADR rate (40.43/100 PY vs. 18.22/100 PY, p < 0.0001) and an 8.0-fold higher drug-related discontinuation rate than biologics (0.16/PY vs. 0.02/PY, p < 0.0001). Trends showed non-significant higher serious adverse event rates per 100 PY for biologics (8.19, CI 6.87-9.68) compared to CSTs (7.08, CI 5.39-9.13) (p = 0.3922). Sex stratification revealed a significantly higher overall ADR rate for all treatments in females (1.8-fold for CSTs [57.30/100 PY vs. 31.69/100 PY] and 2.0-fold for biologics [27.36/100 PY vs. 13.9/100 PY], p < 0.0001), and drug-related discontinuation rates for most CSTs in females. Females were associated with a significantly higher rate of ADRs and drug-related discontinuation rates. Sex stratification should be taken into consideration when designing studies in the patient-tailored management of psoriasis.

Effect of acid suppressant medications on the laxative action of magnesium preparations in patients with opioid-induced constipation: A pharmacovigilance analysis of the FDA Adverse Event Reporting System.

Objective: Magnesium oxide is widely used for treating opioid-induced constipation, a serious analgesic-associated problem. Opioid analgesic users are often prescribed non-steroidal anti-inflammatory drugs, which are sometimes combined with acid suppressants to prevent gastrointestinal adverse events. Magnesium preparations combined with acid suppressants may diminish magnesium preparations' laxative effect. This study was aimed at evaluating the effect of magnesium preparations combined with acid suppressants on the incidence of opioid-induced constipation by using the Food and Drug Administration Adverse Event Reporting System. Methods: Adverse events were defined per the Medical Dictionary for Regulatory Activities; the term 'constipation (preferred term code: 10010774)' was used for analysis. After adjusting for patient background factors using propensity score matching, acid suppressants' effect on constipation incidence was evaluated in opioid users prescribed magnesium preparations alone as laxatives by using a test for independence. Key Findings: The Food and Drug Administration Adverse Event Reporting System contains 14,475,614 reports for January 2004 to December 2021. Significantly increased constipation incidence was related to magnesium preparations combined with acid suppressants, especially proton pump inhibitors (P < 0.0001, McNemar's test). Conclusion: Magnesium preparations combined with acid suppressants may diminish magnesium preparations' laxative effect; healthcare professionals should pay attention to this issue.

Comparing Common Therapies in Polycythemia Vera (PV): A Disproportionality Analysis in the FDA Adverse Event Reporting System (FAERS) Database

Background: Prior to the approval of ropeginterferon alfa-2b-njft (ropeginterferon) in November 2021, the alternatives to hydroxyurea for the treatment of polycythemia vera (PV) included Janus Kinase inhibitors (JAKi) and older versions of recombinant interferon-alpha (rIFNα). As ropeginterferon and the JAKi ruxolitinib are the only FDA approved medications for the treatment of PV, we conducted a safety review of the FDA's Adverse Event Reporting System (FAERS) to assess reporting rates for adverse events (AEs) of both FDA-approved and non-FDA approved rIFNα and JAKi agents. Methods: AE data for ropeginterferon, peginterferon alfa-2a, ruxolitinib, and pacritinib in PV-treated patients were obtained from FAERS reports from November 1, 2021, through March 31, 2023. AEs were recorded using preferred terms (PTs) and primary system organ classes (SOCs) from the Medical Dictionary for Regulatory Activities (MedDRA). Serious non-fatal AEs (SAEs) were defined as AEs requiring hospitalization, life-threatening, resulting in disability, congenital anomaly, or otherwise medically significant. Reporting odds ratios (RORs) and 95% confidence intervals (95% CIs) were calculated using R v4.2.3 Statistical Software. The RORs were used to detect disproportional reporting rates for non-serious AEs, SAEs, and fatal AEs as well as SOC-specific reporting rates. A reporting signal was considered significant when the ROR 95% CI lower limit was greater than one. Results: SOC-specific RORs for the assessed treatments are summarized in Table 1. RORs by AE seriousness are displayed in Figure 1. Ropeginterferon had the only non-serious AE significant ROR (ROR = 5.37; 95% CI: 3.63 - 7.94). The two highest SOC-specific RORs for ropeginterferon were “Medical and Surgical Procedures” (ROR = 15.32; 95% CI: 1.88 - 124.67) and “Social Circumstances” (ROR = 6.30; 95% CI: 2.66 - 14.94). Peginterferon alfa-2a had the highest SAE reporting odds (ROR = 5.68; 95% CI: 3.03 - 10.6). The highest SOC RORs for peginterferon alfa-2a were “Hepatobiliary Disorders” (ROR = 16.35; 95% CI: 4.86 - 55.01) and “Immune System Disorders” (ROR = 5.11; 95% CI: 1.49 - 17.48). Ruxolitinib was the only agent assessed to have significant reporting signals for both SAEs (ROR = 1.93; 95% CI: 1.43 - 2.61) and fatal AEs (ROR = 9.86; 95% CI: 3.62 - 26.82) The highest SOC RORs for ruxolitinib were “Neoplasms Benign, Malignant, and Unspecified” (ROR = 7.96; 95% CI = 3.47 - 18.27) and “Product Issues” (ROR = 3.85; 95% CI: 2.42 - 6.12). Conclusions: This study examined FAERS reports to detect disproportional reporting odds of drug-associated AEs severity and SOCs in four PV treatments: ropeginterferon, ruxolitinib, interferon alfa-2a, and pacritinib. Ropeginterferon had a significant ROR for non-serious AEs. Peginterferon alfa-2a demonstrated a significant ROR for SAEs. Ruxolitinib had both significant SAE and fatal AE RORs. The highest SOC-specific RORs for ropeginterferon were in the non-specific categories of “Medical and Surgical Procedures” and “Social Circumstances.” Peginterferon alfa-2a had significant SOC signals for “Hepatobiliary Disorders” and “Immune System Disorders,” which are AE categories also reported in the prescribing information for peginterferon alfa-2a. “Neoplasms Benign, Malignant, and Unspecified” was the highest SOC ROR for ruxolitinib and may potentially relate to the association of treatment with secondary malignancies. Limitations include a lack of adjustments for multiplicity due to the exploratory nature of the analysis. AEs reports to FAERS may not be treatment related. In addition, publicity or FDA approvals may disproportionately affect reporting rates for ropeginterferon (FDA-approved in 2021) or ruxolitinib (approved for PV in 2014). FAERS may also not include representative AE reports as healthcare provider and patient submissions are both postmarketing and voluntary. Fatal events during clinical trials were reported to the FDA (including ropeginterferon) but are not reflected in FAERS. Therefore, FAERS data may not represent the true incidence of AEs. Reporting signals for any treatments or any causal relationship should be confirmed by assessing future AE reporting trends, electronic health records analysis, or prospective clinical trials.

Patient-Reported Reasons for Antihypertensive Medication Change: A Quantitative Study Using Social Media.

Hypertension is the leading cause of heart disease in the world, and discontinuation or nonadherence of antihypertensive medication constitutes a significant global health concern. Patients with hypertension have high rates of medication nonadherence. Studies of reasons for nonadherence using traditional surveys are limited, can be expensive, and suffer from response, white-coat, and recall biases. Mining relevant posts by patients on social media is inexpensive and less impacted by the pressures and biases of formal surveys, which may provide direct insights into factors that lead to non-compliance with antihypertensive medication. This study examined medication ratings posted to WebMD, an online health forum that allows patients to post medication reviews. We used a previously developed natural language processing classifier to extract indications and reasons for changes in angiotensin receptor II blocker (ARB) and angiotensin-converting enzyme inhibitor (ACEI) treatments. After extraction, ratings were manually annotated and compared with data from the US Food and Drug administration (FDA) Adverse Events Reporting System (FAERS) public database. From a collection of 343,459 WebMD reviews, we automatically extracted 1867 posts mentioning changes in ACEIs or ARBs, and manually reviewed the 300 most recent posts regarding ACEI treatments and the 300 most recent posts regarding ARB treatments. After excluding posts that only mentioned a dose change or were a false-positive mention, 142 posts in the ARBs dataset and 187 posts in the ACEIs dataset remained. The majority of posts (97% ARBs, 91% ACEIs) indicated experiencing an adverse event as the reason for medication change. The most common adverse events reported mapped to the Medical Dictionary for Regulatory Activities were "musculoskeletal and connective tissue disorders" like muscle and joint pain for ARBs, and "respiratory, thoracic, and mediastinal disorders" like cough and shortness of breath for ACEIs. These categories also had the largest differences in percentage points, appearing more frequently on WebMD data than FDA data (p<0.001). Musculoskeletal and respiratory symptoms were the most commonly reported adverse effects in social media postings associated with drug discontinuation. Managing such symptoms is a potential target of interventions seeking to improve medication persistence.

Parasitic infections related to anti-type 2 immunity monoclonal antibodies: a disproportionality analysis in the food and drug administration's adverse event reporting system (FAERS).

Introduction: Monoclonal antibodies (mAbs) targeting immunoglobulin E (IgE) [omalizumab], type 2 (T2) cytokine interleukin (IL) 5 [mepolizumab, reslizumab], IL-4 Receptor (R) α [dupilumab], and IL-5R [benralizumab]), improve quality of life in patients with T2-driven inflammatory diseases. However, there is a concern for an increased risk of helminth infections. The aim was to explore safety signals of parasitic infections for omalizumab, mepolizumab, reslizumab, dupilumab, and benralizumab. Methods: Spontaneous reports were used from the Food and Drug Administration's Adverse Event Reporting System (FAERS) database from 2004 to 2021. Parasitic infections were defined as any type of parasitic infection term obtained from the Standardised Medical Dictionary for Regulatory Activities® (MedDRA®). Safety signal strength was assessed by the Reporting Odds Ratio (ROR). Results: 15,502,908 reports were eligible for analysis. Amongst 175,888 reports for omalizumab, mepolizumab, reslizumab, dupilumab, and benralizumab, there were 79 reports on parasitic infections. Median age was55 years (interquartile range 24-63years) and 59.5% were female. Indications were known in 26 (32.9%) reports; 14 (53.8%) biologicals were reportedly prescribed for asthma, 8 (30.7%) for various types of dermatitis, and 2 (7.6%) for urticaria. A safety signal was observed for each biological, except for reslizumab (due to lack of power), with the strongest signal attributed to benralizumab (ROR = 15.7, 95% Confidence Interval: 8.4-29.3). Conclusion: Parasitic infections were disproportionately reported for mAbs targeting IgE, T2 cytokines, or T2 cytokine receptors. While the number of adverse event reports on parasitic infections in the database was relatively low, resulting safety signals were disproportionate and warrant further investigation.