Medical Dictionary For Regulatory Activities Research Articles

A real-world pharmacovigilance study of drug-induced QT interval prolongation: analysis of spontaneous reports submitted to FAERS

PurposeTo identify the most commonly reported drugs associated with QT interval prolongation in the FDA Adverse Event Reporting System (FAERS) and evaluate their risk for QT interval prolongation.MethodsWe employed the preferred term (PT) “electrocardiogram QT prolonged” from the Medical Dictionary for Regulatory Activities (MedDRA) 26.0 to identify adverse drug events (ADEs) of QT interval prolongation in the FAERS database from the period 2004–2022. Reporting odds ratio (ROR) was performed to quantify the signals of ADEs.ResultsWe listed the top 40 drugs that caused QT interval prolongation. Among them, the 3 drugs with the highest number of cases were quetiapine (1,151 cases, ROR = 7.62), olanzapine (754 cases, ROR = 7.92), and citalopram (720 cases, ROR = 13.63). The two most frequently reported first-level Anatomical Therapeutic Chemical (ATC) groups were the drugs for the nervous system (n = 19, 47.50%) and antiinfectives for systemic use (n = 7, 17.50%). Patients with missing gender (n = 3,482, 23.68%) aside, there were more females (7,536, 51.24%) than males (5,158, 35.07%) were involved. 3,720 patients (25.29%) suffered serious clinical outcomes resulting in deaths or life-threatening conditions. Overall, most drugs that caused QT interval prolongation had early failure types according to the assessment of the Weibull's shape parameter (WSP) analysis.ConclusionsOur study offered a list of drugs that frequently caused QT interval prolongation based on the FAERS system, along with a description of some risk profiles for QT interval prolongation brought on by these drugs. When prescribing these drugs in clinical practice, we should closely monitor the occurrence of ADE for QT interval prolongation.

Isatuximab plus pomalidomide and dexamethasone in patients with relapsed/refractory multiple myeloma in real-world: The retrospective IMAGE study.

IMAGE is a retrospective cohort study of patients enrolled in early access programs (EAPs) in France with relapsed/refractory multiple myeloma (RRMM) receiving isatuximab with pomalidomide and dexamethasone (Isa-Pd). Patients aged ≥18 years with RRMM who received ≥1 dose of Isa under the EAPs between July 29, 2019 and August 30, 2020 were included. Effectiveness endpoints included progression-free survival (PFS) and response rates. Verbatim terms for adverse events (AEs) were coded using the Medical Dictionary for Regulatory Activities and not graded for severity. A total of 294 and 299 patients were included in the effectiveness and safety populations, respectively. IMAGE included patients who received one prior line of treatment (10.2%) and were daratumumab-refractory (19.1%). At median follow-up of 14.2 months, median PFS in the effectiveness population was 12.4 months (95% CI 9.0-15.0). Overall response and very good partial response rates were 46.3% and 27.9%, respectively. Subgroup analyses reflected similar results. In the safety population, 26.4% of patients reported at least one AE; the most common any-grade AE was neutropenia (9.4%). IMAGE demonstrated Isa-Pd had meaningful effectiveness in median PFS and depth of response and no new safety signals in a real-world context, consistent with clinical trial results.

Cardiovascular adverse events associated with antibody-drug conjugates (ADCs): a pharmacovigilance study based on the FAERS database

ObjectiveAs a novel drug formulation, antibody drug conjugates (ADCs) are widely used in various types of cancer. However, clinically, there is a lack of attention to the CVD produced by them, as well as a lack of research on the real-world situation. Using the Food and Drug Administration Adverse Event Reporting System (FAERS) database, to ensure its clinical safety application, we analyzed post-marketing data on antitumor ADCs to identify risk factors and drugs associated with the risk of cardiovascular events.Research design and methodsWe used OpenVigil 2.1 to conduct a database query for adverse events (AEs) reported to the FAERS database between the time the drug was launched and the second quarter of 2023. Cardiovascular adverse events (AEs) were grouped into fourteen narrow categories using the Standardized Medical Dictionary for Regulatory Activities (MedDRA) Queries (SMQs), and the reporting odds ratio (ROR) and the proportional reporting ratio (PRR) for reporting the association between different drugs and cardiovascular disease (CVD) risk were calculated.ResultsIn the FAERS database, 1863 AEs associated with CVD we studied were identified in patients receiving ADC therapy. Most reports came from people aged ≥65, but a significant number of cases were found to be unknown. The number of patients with antibody-drug conjugates (ADCs)-related CVD cases aged <18 years, 18–64 years, and≥ 65 years was 52 (2.79%), 586 (31.45%), and 613 (32.90%), respectively. The proportion of female patients (834, 44.77%) was higher than that of male patients (752, 40.37%). Death (770 reports), disability (9 reports), Hospitalization initial or prolonged (407 reports), and life-threatening reactions (187 reports). Of the 770 deaths reported, 103 (31.7%) were associated with brentuximab vedotin, 10 (24.4%) with sacituzumab govitecan, 22 (19.3%) with enfortumab vedotin, and 35 (34.7%) with trastuzumab emtansine.49 (41.2%) cases were associated with polatuzumab vedotin, 62 (29%) with trastuzumab deruxtecan, 423 (54.3%) with gemtuzumab ozogamicin, and 66 (38.8%) with inotuzumab ozogamicin. In a disproportionate number of SMQS, cardiac failure (n = 277) and embolic and thrombotic events, venous (n = 446) were the most frequently reported CVD-related AEs in ADCs.ConclusionBy mining the FAERS database, we provided relevant information on the association between ADC use and cardiovascular-associated AEs. ADCs were associated with increased cardiovascular toxicity, deserving distinct monitoring and appropriate management. Further research is needed to confirm these findings and assess causality.

Abstract PO3-12-04: Pulmonary Complication related to Trastuzumab Deruxtecan. A pharmacovigilance study from 2022-2023 FAERS Database

Abstract Background: The horizon of Trastuzumab Deruxtecan (T-DXd), an antibody-drug conjugate, has been expanding. After its promising results in HER2-positive/HER2-low Breast cancer, it has been on trial for other cancers, such as HER2-negative breast cancers, Gastrointestinal, lung, colorectal, urothelial, etc., and it has shown promising results in clinical trials. However, there have been reports of pulmonary adverse events associated with T-DXd, including interstitial lung disease (ILD) and pneumonitis. Understanding the occurrence and characteristics of these pulmonary complications is essential for optimizing patient care and ensuring the safe use of T-DXd. Using the FAERS (FDA Adverse Event Reporting System) database for 2022-2023 aims to see T-DXd-related pulmonary complications and guide healthcare professionals in monitoring and managing these adverse events effectively. Methods: We conducted a retrospective analysis of all reported cases of respiratory complications in patients using TDXD, utilizing data reported to the FDA Adverse Event Reporting System (FAERS) database for January 2022 to March 2023. We included patients of more than 18; these cases were identified and classified using the Medical Dictionary for Regulatory Activities (MedDRA) terminology. Results: In this study, a total of 296 cases of adverse events were reported in patients using TDXD. Among these cases, 74 (27%) were respiratory adverse events. The most frequently observed respiratory complications were interstitial lung disease (ILD) and pneumonitis, with 21 cases each, accounting for 56% of the total respiratory complications. Out of the 14 reported deaths in this cohort, pneumonitis was the most commonly seen respiratory complication, occurring in 8 patients, followed by pulmonary embolism and ILD, each reported in 4 patients. Conclusion: Respiratory complications were the most frequent among the reported adverse events, accounting for 27% of all cases. ILD and pneumonitis were the most common complications, with 14 deaths reported in this group. These findings underline the importance of closely monitoring and managing pulmonary adverse events in patients treated with T-DXd. Healthcare professionals can use this information to optimize patient care and ensure the safe use of T-DXd. However, it is important to note that this study was based on a database and has limitations such as underreporting bias and lack of a control group, which hinders establishing a causal relationship. Additional research is needed to identify risk factors and improve patient outcomes. Citation Format: Niraj Neupane, Himal Kharel, Sangharsha Thapa. Pulmonary Complication related to Trastuzumab Deruxtecan. A pharmacovigilance study from 2022-2023 FAERS Database [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-12-04.

Experiences of Women With Medical Abortion Care Reflected in Social Media (VEILLE Study): Noninterventional Retrospective Exploratory Infodemiology Study.

Abortion (also known as termination of pregnancy) is an essential element of women's reproductive health care. Feedback from women who underwent medical termination of pregnancy about their experience is crucial to help practitioners identify women's needs and develop necessary tools to improve the abortion care process. However, the collection of this feedback is quite challenging. Social media offer anonymity for women who share their abortion experience. This exploratory infodemiology study aimed to analyze, through French social media posts, personal medical symptoms and the different experiences and information dynamics associated with the medical abortion process. A retrospective study was performed by analyzing posts geolocated in France and published from January 1, 2017, to November 30, 2021. Posts were extracted from all French-language general and specialized publicly available web forums using specific keywords. Extracted messages were cleaned and pseudonymized. Automatic natural language processing methods were used to identify posts from women having experienced medical abortion. Biterm topic modeling was used to identify the main discussion themes and the Medical Dictionary for Regulatory Activities was used to identify medical terms. Encountered difficulties were explored using qualitative research methods until the saturation of concepts was reached. Analysis of 5398 identified posts (3409 users) led to the identification of 9 major topics: personal experience (n=2413 posts, 44.7%), community support (n=1058, 19.6%), pain and bleeding (n=797, 14.8%), psychological experience (n=760, 14.1%), questioned efficacy (n=410, 7.6%), social pressure (n=373, 6.9%), positive experiences (n=257, 4.8%), menstrual cycle disorders (n=107, 2%), and reported inefficacy (n=104, 1.9%). Pain, which was mentioned in 1627 (30.1%) of the 5398 posts by 1024 (30.0%) of the 3409 users, was the most frequently reported medical term. Pain was considered severe to unbearable in 24.5% of the cases (399 of the 1627 posts). Lack of information was the most frequently reported difficulty during and after the process. Our findings suggest that French women used social media to share their experiences, offer and find support, and provide and receive information regarding medical abortion. Infodemiology appears to be a useful tool to obtain women's feedback, therefore offering the opportunity to enhance care in women undergoing medical abortion.

Phosphodiesterase type 5 inhibitors related hearing impairment: a real world study based on the FDA adverse event reporting system

Recent studies focused on exploring phosphodiesterase type 5 inhibitors (PDE5Is)-related hearing impairment. This study aimed to comprehensively explore real-world hearing impairment associated with PDE5Is based on the US Food and Drug Administration Adverse Event Reporting System (FAERS). The characteristics and correlation of PDE5Is-related hearing impairment reported in the FAERS database from the fourth quarter of 2003 to the second quarter of 2023 were analyzed using disproportionality analysis. The Standardized Medical Dictionary for Regulatory Activities (MedDRA) Queries (SMQs) were used to analyze the adverse events (AEs) of hearing impairment. A total of 1,438 reported cases of hearing impairment were associated with four PDE5Is, revealing statistically significant reporting odds ratio (ROR), proportional reporting ratio (PRR), and information component (IC) with the SMQ. The average age of all patients was more than 55 years, over 70% of AEs were reported in men. Most of the reported cases were from the United States. Reports for all the drugs indicated an increase since 2008, except for avanafil. This study showed that the disability rates of PDE5Is were 8.14–40%, the rates of initial or prolonged hospitalization were 6.21–10.24%, and the rates of required intervention were 3.31–9.45%. The pharmacovigilance study identified a potential risk of hearing impairment associated with PDE5Is, indicating the need for continuous monitoring and appropriate management.

Antiviral influenza treatments and hemorrhage-related adverse events in the United States Food and Drug Administration Adverse Event Reporting System (FAERS) database.

To determine whether there is a signal for gastrointestinal (GI) or intracranial (IC) hemorrhage associated with the use of antiviral medications for influenza in the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database. Disproportionality analysis. The FAERS database was searched using OpenVigil 2.1 to identify GI and IC hemorrhage events reported between 2004 and 2022. Antiviral medications for influenza included the following: oseltamivir, zanamivir, peramivir, and baloxavir marboxil. Hemorrhage events were identified using Standardized Medical Dictionary for Regulatory Activities (MedDRA) Queries for GI and IC hemorrhages. Reporting odds ratios (RORs) were calculated to compare the occurrence of GI and IC hemorrhage events between antiviral drugs for influenza and (i) all other medications and (ii) antibiotics. RORs were also calculated for each of the individual antiviral medications. A total of 245 cases of GI hemorrhage and 23 cases of IC hemorrhage were identified in association with four antivirals. In comparison with all other drugs, the RORs of GI hemorrhage for oseltamivir, zanamivir, peramivir, baloxavir, and all antivirals combined were 1.17, 0.62, 4.44, 2.53, and 1.22, respectively, indicating potential variations in GI hemorrhage risk among the antivirals. In contrast, in comparison with all other drugs, the RORs of IC hemorrhage for oseltamivir (0.44), zanamivir (0.16), baloxavir (0.44), and all antivirals combined (0.41) were less than 1.0 which is consistent with no elevated risk of IC hemorrhage. In this study, some signals for GI hemorrhage were observed, particularly for peramivir and baloxavir marboxil. Further investigation is warranted to better understand and evaluate the potential risks of GI hemorrhage associated with antiviral treatments for influenza.

Investigating bleeding adverse events associated with BTK inhibitors in the food and drug administration adverse event reporting system (FAERS)

ABSTRACT Background This study analyzed the bleeding adverse events (AEs) resulting from the treatment of B-cell lymphoma with Bruton tyrosine kinase (BTK) inhibitors, according to reports in the US Food and Drug Administration’s Adverse Event Reporting System (FAERS) Methods Bleeding AEs associated with BTK inhibitors (including ibrutinib, zanubrutinib, and acalabrutinib) from the first quarter of 2013 to the third quarter of 2023 were extracted. Reporting odds ratio (ROR) and proportional reporting ratio (PRR) were reported. Preferred Terms (PTs) of Medical Dictionary for Regulatory Activities (MedDRA) terms were mapped to System Organ Class terms (SOC) terms and analyzed bleeding AEs associated with three BTK inhibitors. Results A total of 463 cases of bleeding AEs were included. Contusion, subcutaneous hemorrhage, hematuria, and cerebral hemorrhage were included in PTs. Blood urine was present and subdural hematoma were also reported. The incidence of bleeding AEs was higher with ibrutinib (Case number = 10,696) than with zanubrutinib (Case number = 213) and acalabrutinib (Case number = 314). Conclusion Our findings indicate that bleeding AEs linked to BTK inhibitors in various conditions underscore the need for cautious clinical decision-making, particularly in nervous system disorders, injuries, poisoning, surgical complications, vascular disorders, and others.

Safety Profile of Selective Serotonin Reuptake Inhibitors in Real-World Settings: A Pharmacovigilance Study Based on FDA Adverse Event Reporting System.

Selective serotonin reuptake inhibitors (SSRIs) are the most frequently prescribed agents to treat depression. Considering the growth in antidepressant prescription rates, SSRI-induced adverse events (AEs) need to be comprehensively clarified. This study was to investigate safety profiles and potential AEs associated with SSRIs using the Food and Drug Administration Adverse Event Reporting System (FAERS). A retrospective pharmacovigilance analysis was conducted using the FAERS database, with Open Vigil 2.1 used for data extraction. The study included cases from the marketing date of each SSRI (ie, citalopram, escitalopram, fluoxetine, paroxetine, fluvoxamine, and sertraline) to April 30, 2023. We employed the reporting odds ratio and Bayesian confidence propagation neural network as analytical tools to assess the association between SSRIs and AEs. The Medical Dictionary for Regulatory Activities was used to standardize the definition of AEs. AE classification was achieved using system organ classes (SOCs). Overall, 427 655 AE reports were identified for the 6 SSRIs, primarily associated with 25 SOCs, including psychiatric, nervous system, congenital, familial, genetic, cardiac, and reproductive disorders. Notably, sertraline (n = 967) and fluvoxamine (n = 169) exhibited the highest and lowest signal frequencies, respectively. All SSRIs had relatively strong signals related to congenital, psychiatric, and nervous disorders. Most of our findings are consistent with those reported previously, but some AEs were not previously identified. However, AEs attributed to SSRIs remain ambiguous, warranting further validation. Applying data-mining methods to the FAERS database can provide additional insights that can assist in appropriately utilizing SSRIs.

Exploring Safety in Gender-Affirming Hormonal Treatments: An Observational Study on Adverse Drug Events Using the Food and Drug Administration Adverse Event Reporting System Database.

People with gender dysphoria are treated with hormone therapy for gender reassignment. The indication of this therapy was initially for the opposite sex, and information on potential adverse drug reaction (ADR) is lacking. To describe ADR associated with gender transition medication in transgender individuals reported to the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. Data from the FAERS database up to June 2023 were examined, focusing on reports of gender transition medication use in the context of gender dysphoria. The ADRs were categorized using the Medical Dictionary for Regulatory Activities at both Preferred Term and System Organ Class (SOC) levels. Descriptive statistics summarized report counts, medication types, indications, and ADR severity. For individuals assigned female at birth undergoing gender transition to male (transgender men), 82 reports (230 ADRs) were analyzed, with an average age of 29.5 years. Transgender hormonal therapy was cited in 72% of reports, predominantly from the United States (67.1%). A striking 88% were categorized as serious ADRs, primarily SOC injury, poisoning, and procedural complications (26.5%), followed by psychiatric disorders (14.8%) and nervous system disorders (12.2%). Among those assigned sex male at birth transitioning to female (transgender women) (81 reports, 237 ADRs), mean age was 33.3 years, with 58% indicating use for gender dysphoria. A significant proportion (53.6%) were serious ADRs, primarily SOC: injury, poisoning, and procedural complications (26.6%). The FAERS data reveal significant ADRs in transgender individuals using hormone therapy, sometimes unintended for their recipient gender. Population-level studies are crucial to enhance transgender health care. Spontaneous surveillance databases like FAERS illuminate off-label ADRs, urging health care providers to approach hormone therapies with informed caution.

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”).

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.