Eventos adversos em crianças submetidas a cirurgias orofaciais / Adverse events in children submitted to orofacial surgery / Eventos adversos en niños sometidos a cirugía orofacial

Objetivo: Identificar os eventos adversos no pós-operatório imediato de queiloplastia e/ou palatoplastia em crianças e comparar os eventos identificados aos notificados ao Núcleo de Segurança do Paciente. Métodos: Estudo descritivo, retrospectivo e quantitativo, realizado em um hospital público e terciário brasileiro. Os dados foram coletados por meio da descrição nos registros de enfermagem e comparados aos notificados ao Núcleo de Segurança do Paciente, referente a junho e dezembro de 2019. Os resultados foram submetidos a análise estatística descritiva. Resultados: A amostra constou de 203 crianças, das quais 51% (n=103) apresentaram evento adverso. Foram identificados 176 eventos adversos, de 8 tipos, com prevalência da laringite pós-extubação (n=50; 28%), edema de língua (n=34; 19%) e lesão de comissura labial (n=25; 14%). Destes, apenas 5% (n=9) foram notificados ao Núcleo de Segurança do Paciente. Conclusão: Os eventos adversos prevalentes se relacionaram a cavidade oral e tecidos adjacentes, e a subnotificação foi expressiva. (AU)

Objective: To identify adverse events in the immediate postoperative period of cheiloplasty and/or palatoplasty in children and compare the identified events to those notified to the Patient Safety Center. Methods: Descriptive, retrospective and quantitative study, carried out in a Brazilian public and tertiary hospital. Data were collected through descriptions in nursing records and compared to those notified to the Patient Safety Center, referring to June and December 2019. The results were subjected to descriptive statistical analysis. Results: The sample consisted of 203 children, of which 51% (n=103) had an adverse event. A total of 176 adverse events of 8 types were identified, with prevalence of post-extubation laryngitis (n=50; 28%), tongue edema (n=34; 19%) and labral commissure lesion (n=25; 14%). Of these, only 5% (n=9) were notified to the Patient Safety Center. Conclusion: The prevalent adverse events were related to the oral cavity and adjacent tissues, and underreporting was significant. (AU)

Objetivo: Identificar eventos adversos en el postoperatorio inmediato de queiloplastia y/o palatoplastia en niños y comparar los eventos identificados con los notificados al Centro de Seguridad del Paciente. Métodos: Estudio descriptivo, retrospectivo y cuantitativo, realizado en un hospital público y terciario brasileño. Los datos se recolectaron mediante descripciones en registros de enfermería y se compararon con los notificados al Centro de Seguridad del Paciente, referidos a junio y diciembre de 2019. Los resultados fueron sometidos a análisis estadístico descriptivo. Resultados: La muestra estuvo conformada por 203 niños, de los cuales el 51% (n = 103) tuvo un evento adverso. Se identificaron un total de 176 eventos adversos de 8 tipos, con prevalencia de laringitis posextubación (n=50; 28%), edema de lengua (n=34; 19%) y lesión de la comisura del labrum (n=25; 14%). De estos, solo el 5% (n=9) fueron notificados al Centro de Seguridad del Paciente. Conclusion: Los eventos adversos prevalentes se relacionaron con la cavidad bucal y los tejidos adyacentes y el subregistro fue significativo. (AU)

Antiseizure adverse drug reaction and associated factors among epileptic patients at Jimma Medical Center: a prospective observational study.

A growing body of evidence suggests that adverse drug reactions (ADRs) are a major cause of morbidity and mortality in the healthcare system. Fifteen to twenty-five percent of patients with epilepsy discontinued antiseizure drugs (ASDs) within 6 months of therapy owing to intolerable adverse drug reactions. In Ethiopia, the prevalence of antiseizure adverse drug reactions and associated factors was not extensively conducted in advanced settings like Jimma Medical Centers. Hence, the objective of this study is to assess patterns of adverse drug reactions and associated factors among ambulatory epileptic patients at tertiary hospitals in Ethiopia. A hospital-based prospective observational study was spanned for 1 year. Two hundred ninety patients were consecutively recruited into the study from all epileptic patients attending the ambulatory clinic. Relevant data were collected through patient interviews and medical chart reviews. The causality assessment was done by using the Naranjo Probability Scale. Epi-Data manager version 4.6.0.4 was used for data entry and statistical analysis was performed by Statistical Package for Social Science version 25.0 (SPSS). Stepwise backward logistic regression analysis was done to identify factors that increase the risk of antiseizure adverse drug reactions. The mean (± SD) age of the participants were 29.91(± 11.26) years. The overall prevalence of ADR was 33.8% (95% CI 29.2-39.9%). A total of 110 adverse drug reactions were identified among 98 patients with an average of 1.12 per patient. ADRs were frequently reported with phenobarbital (52.04%) and phenytoin (34.70%). The commonly identified adverse drug reactions were epigastric pain (27.55%) and central nervous system drowsiness (23.46%). Comorbidity (AOR = 5.91, 95% CI (2.14-16.32), seizure-free period of fewer than 2 years (AOR = 1.94, 95% CI (1.18-3.19), and polytherapy (AOR = 1.35, 95% CI (1.80-2.26) were significantly associated with adverse drug reactions. This trial had a comparatively high percentage of adverse medication reactions. Adverse medication reactions were more common in patients with polytherapy, comorbidities, and seizure-free durations less than two years. Therefore, medical practitioners should advise patients who exhibit these traits on how to reduce or avoid bad drug responses or provide comfort in the event of small incidents.

Emerging Toxicities of Antibody-Drug Conjugates for Breast Cancer: Clinical Prioritization of Adverse Events from the FDA Adverse Event Reporting System.

BACKGROUND: Antibody-drug conjugates (ADCs) are gaining widespread use in the treatment of breast cancer, although toxicity remains an underexplored issue in the real-world clinical setting. Individual case safety reports collected in large pharmacovigilance databases can advance our knowledge on their safety profile in routine clinical practice. OBJECTIVE: We prioritized adverse events (AEs) reported with ADCs approved for breast cancer using the Food and Drug Administration Adverse Event Reporting System (FAERS). METHODS: We assessed clinical priority of AEs reported in FAERS (February 2013-March 2022) for trastuzumab emtansine (T-DM1), trastuzumab deruxtecan (T-DXd), and sacituzumab govitecan (SG) by attributing a score to each AE disproportionally reported with ADCs. Four criteria were assessed: clinical relevance, reporting rate, reported case fatality rate, and stability of disproportionality signals (consistency of the reporting odds ratio across multiple analyses using three different comparators). RESULTS: We retained 6589 reports (77.4% referring to T-DM1 as suspect), and 572 AEs generated a disproportionality signal in at least one analysis. The majority of these AEs (62%) were classified as moderate clinical priorities (e.g., interstitial lung disease with T-DXd, thrombocytopenia, peripheral neuropathy with T-DM1, febrile neutropenia, and large intestine perforation with SG). Three AEs emerged as high clinical priorities (6 points): septic shock and neutropenic colitis with SG (N = 8 and 13, with median onset 13 and 10 days, respectively), without co-reported immunosuppressive agents; and pulmonary embolism with T-DM1 (N = 31, median onset 109 days, 52% with reported metastasis). CONCLUSION: The heterogeneous spectrum of post-marketing toxicities for ADCs used in breast cancer, as emerging from the FAERS, is largely in line with preapproval evidence. Although causality cannot be proved, we call for increased awareness by oncologists on potential serious unexpected reactions, including early onset of septic shock and neutropenic colitis with SG, and late emergence of pulmonary embolism with T-DM1.

Mining Real-World Big Data to Characterize Adverse Drug Reaction Quantitatively: Mixed Methods Study.

BACKGROUND: Adverse drug reactions (ADRs), which are the phenotypic manifestations of clinical drug toxicity in humans, are a major concern in precision clinical medicine. A comprehensive evaluation of ADRs is helpful for unbiased supervision of marketed drugs and for discovering new drugs with high success rates. OBJECTIVE: In current practice, drug safety evaluation is often oversimplified to the occurrence or nonoccurrence of ADRs. Given the limitations of current qualitative methods, there is an urgent need for a quantitative evaluation model to improve pharmacovigilance and the accurate assessment of drug safety. METHODS: In this study, we developed a mathematical model, namely the Adverse Drug Reaction Classification System (ADReCS) severity-grading model, for the quantitative characterization of ADR severity, a crucial feature for evaluating the impact of ADRs on human health. The model was constructed by mining millions of real-world historical adverse drug event reports. A new parameter called Severity_score was introduced to measure the severity of ADRs, and upper and lower score boundaries were determined for 5 severity grades. RESULTS: The ADReCS severity-grading model exhibited excellent consistency (99.22%) with the expert-grading system, the Common Terminology Criteria for Adverse Events. Hence, we graded the severity of 6277 standard ADRs for 129,407 drug-ADR pairs. Moreover, we calculated the occurrence rates of 6272 distinct ADRs for 127,763 drug-ADR pairs in large patient populations by mining real-world medication prescriptions. With the quantitative features, we demonstrated example applications in systematically elucidating ADR mechanisms and thereby discovered a list of drugs with improper dosages. CONCLUSIONS: In summary, this study represents the first comprehensive determination of both ADR severity grades and ADR frequencies. This endeavor establishes a strong foundation for future artificial intelligence applications in discovering new drugs with high efficacy and low toxicity. It also heralds a paradigm shift in clinical toxicity research, moving from qualitative description to quantitative evaluation.

Safety of immune checkpoint inhibitors in patients aged over 80 years: a retrospective cohort study.

BACKGROUND: Immuno-oncology (IO) drugs are essential for treating various cancer types; however, safety concerns persist in older patients. Although the incidence of immune-related adverse events (irAEs) is similar among age groups, higher rates of hospitalization or discontinuation of IO therapy have been reported in older patients. Limited research exists on IO drug safety and risk factors in older adults. Our investigation aimed to assess the incidence of irAEs and identify the potential risk factors associated with their development. METHODS: This retrospective analysis reviewed the clinical data extracted from the medical records of patients aged > 80 years who underwent IO treatment at our institution. Univariate and multivariate analyses were performed to assess the incidence of irAEs. RESULTS: Our study included 181 patients (median age: 82 years, range: 80-94), mostly men (73%), with a performance status of 0-1 in 87% of the cases; 64% received IO monotherapy. irAEs occurred in 35% of patients, contributing to IO therapy discontinuation in 19%. Our analysis highlighted increased body mass index, eosinophil counts, and albumin levels in patients with irAEs. Eosinophil count emerged as a significant risk factor for any grade irAEs, particularly Grade 3 or higher, with a cutoff of 118 (/µL). The group with eosinophil counts > 118 had a higher frequency of irAEs, and Grade 3 or higher events than the group with counts ≤ 118. CONCLUSION: IO therapy is a safe treatment option for patients > 80 years old. Furthermore, patients with elevated eosinophil counts at treatment initiation should be cautiously managed.

Phenotyping Hepatic Immune-Related Adverse Events in the Setting of Immune Checkpoint Inhibitor Therapy.

PURPOSE: We present and validate a rule-based algorithm for the detection of moderate to severe liver-related immune-related adverse events (irAEs) in a real-world patient cohort. The algorithm can be applied to studies of irAEs in large data sets. METHODS: We developed a set of criteria to define hepatic irAEs. The criteria include: the temporality of elevated laboratory measurements in the first 2-14 weeks of immune checkpoint inhibitor (ICI) treatment, steroid intervention within 2 weeks of the onset of elevated laboratory measurements, and intervention with a duration of at least 2 weeks. These criteria are based on the kinetics of patients who experienced moderate to severe hepatotoxicity (Common Terminology Criteria for Adverse Events grades 2-4). We applied these criteria to a retrospective cohort of 682 patients diagnosed with hepatocellular carcinoma and treated with ICI. All patients were required to have baseline laboratory measurements before and after the initiation of ICI. RESULTS: A set of 63 equally sampled patients were reviewed by two blinded, clinical adjudicators. Disagreements were reviewed and consensus was taken to be the ground truth. Of these, 25 patients with irAEs were identified, 16 were determined to be hepatic irAEs, 36 patients were nonadverse events, and two patients were of indeterminant status. Reviewers agreed in 44 of 63 patients, including 19 patients with irAEs (0.70 concordance, Fleiss' kappa: 0.43). By comparison, the algorithm achieved a sensitivity and specificity of identifying hepatic irAEs of 0.63 and 0.81, respectively, with a test efficiency (percent correctly classified) of 0.78 and outcome-weighted F1 score of 0.74. CONCLUSION: The algorithm achieves greater concordance with the ground truth than either individual clinical adjudicator for the detection of irAEs.

Managing polypharmacy through medication review tools - pros and cons.

Inappropriate polypharmacy is a common occurrence in elderly patients, resulting in increased adverse drug reactions, nonadherence, and increased healthcare costs. Medication review and deprescribing are the primary strategies described in the literature for dealing with problematic polypharmacy. To effectively carry out the medication review, various tools have been developed. These tools can support medication review in a variety of ways. Some tools include a list of medications requiring detailed attention, while others guide medical professionals with principles and algorithms for reviewing and prescribing medicines. A third category of tools focuses on tracking and identifying symptoms that may be due to drug-related problems.

Minimising Adverse Drug Reactions and Verifying Economic Legitimacy-Pharmacogenomics Implementation in Children (MARVEL- PIC): protocol for a national randomised controlled trial of pharmacogenomics implementation.

INTRODUCTION: DNA-informed prescribing (termed pharmacogenomics, PGx) is the epitome of personalised medicine. Despite international guidelines existing, its implementation in paediatric oncology remains sparse. METHODS AND ANALYSIS: Minimising Adverse Drug Reactions and Verifying Economic Legitimacy-Pharmacogenomics Implementation in Children is a national prospective, multicentre, randomised controlled trial assessing the impact of pre-emptive PGx testing for actionable PGx variants on adverse drug reaction (ADR) incidence in patients with a new cancer diagnosis or proceeding to haematopoetic stem cell transplant. All ADRs will be prospectively collected by surveys completed by parents/patients using the National Cancer Institute Pediatric Patient Reported [Ped-PRO]-Common Terminology Criteria for Adverse Events (CTCAE) (weeks 1, 6 and 12). Pharmacist will assess for causality and severity in semistructured interviews using the CTCAE and Liverpool Causality Assessment Tool. The primary outcome is a reduction in ADRs among patients with actionable PGx variants, where an ADR will be considered as any CTCAE grade 2 and above for non-haematological toxicities and any CTCAE grade 3 and above for haematological toxicities Cost-effectiveness of pre-emptive PGx (secondary outcome) will be compared with standard of care using hospital inpatient and outpatient data along with the validated Childhood Health Utility 9D Instrument. Power and statistics considerations: A sample size of 440 patients (220 per arm) will provide 80% power to detect a 24% relative risk reduction in the primary endpoint of ADRs (two-sided α=5%, 80% vs 61%), allowing for 10% drop-out. ETHICS AND DISSEMINATION: The ethics approval of the trial has been obtained from the Royal Children's Hospital Ethics Committee (HREC/89083/RCHM-2022). The ethics committee of each participating centres nationally has undertaken an assessment of the protocol and governance submission. TRIAL REGISTRATION NUMBER: NCT05667766.

Adverse drug reactions in paediatric surgery: prospective study on frequency and risk related factors.

BACKGROUND: Paediatric patients are especially prone to experiencing adverse drug reactions (ADRs), and the surgical environment gathers many conditions for such reactions to occur. Additionally, little information exists in the literature on ADRs in the paediatric surgical population. We aimed to quantify the ADR frequency in this population, and to investigate the characteristics and risk factors associated with ADR development. METHODS: A prospective observational study was conducted in a cohort of 311 paediatric patients, aged 1-16 years, admitted for surgery at a tertiary referral hospital in Spain (2019-2021). Incidence rates were used to assess ADR frequency. Odds ratios (ORs) were calculated to evaluate the influence of potential risk factors on ADR development. RESULTS: Distinct ADRs (103) were detected in 80 patients (25.7%). The most frequent being hypotension (N = 32; 35%), nausea (N = 16; 15.5%), and emergence delirium (N = 16; 15.5%). Most ADRs occurred because of drug-drug interactions. The combination of sevoflurane and fentanyl was responsible for most of these events (N = 32; 31.1%). The variable most robustly associated to ADR development, was the number of off-label drugs prescribed per patient (OR = 2.99; 95% CI 1.73 to 5.16), followed by the number of drugs prescribed per patient (OR = 1.26, 95% CI 1.13 to 1.41), and older age (OR = 1.26, 95% CI 1.07 to 1.49). The severity of ADRs was assessed according to the criteria of Venulet and the Spanish Pharmacovigilance System. According to both methods, only four ADRs (3.9%) were considered serious. CONCLUSIONS: ADRs have a high incidence rate in the paediatric surgical population. The off-label use of drugs is a key risk factor for ADRs development.

Adverse event signal mining and serious adverse event influencing factor analysis of fulvestrant based on FAERS database.

Fulvestrant, as the first selective estrogen receptor degrader, is widely used in the endocrine treatment of breast cancer. However, in the real world, there is a lack of relevant reports on adverse reaction data mining for fulvestrant. To perform data mining on adverse events (AEs) associated with fulvestrant and explore the risk factors contributing to severe AEs, providing a reference for the rational use of fulvestrant in clinical practice. Retrieved adverse event report information associated with fulvestrant from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database, covering the period from market introduction to September 30, 2023. Suspicious AEs were screened using the reporting odds ratio (ROR) and proportional reporting ratio methods based on disproportionality analysis. Univariate and multivariate logistic regression analyses were conducted on severe AEs to explore the risk factors associated with fulvestrant-induced severe AEs. A total of 6947 reports related to AEs associated with fulvestrant were obtained, including 5924 reports of severe AEs and 1023 reports of non-severe AEs. Using the disproportionality analysis method, a total of 210 valid AEs were identified for fulvestrant, with 45 AEs (21.43%) not listed in the product labeling, involving 11 systems and organs. The AEs associated with fulvestrant were sorted by frequency of occurrence, with neutropenia (325 cases) having the highest number of reports. By signal strength, injection site pruritus showed the strongest signal (ROR = 658.43). The results of the logistic regression analysis showed that concurrent use of medications with extremely high protein binding (≥ 98%) is an independent risk factor for severe AEs associated with fulvestrant. Age served as a protective factor for fulvestrant-related AEs. The co-administration of fulvestrant with CYP3A4 enzyme inhibitors did not show statistically significant correlation with the occurrence of severe AEs. Co-administration of drugs with extremely high protein binding (≥ 98%) may increase the risk of severe adverse reactions of fulvestrant. Meanwhile, age (60-74 years) may reduce the risk of severe AEs of fulvestrant. However, further clinical research is still needed to explore and verify whether there is interaction between fulvestrant and drugs with high protein binding through more clinical studies.

HMMF: a hybrid multi-modal fusion framework for predicting drug side effect frequencies.

BACKGROUND: The identification of drug side effects plays a critical role in drug repositioning and drug screening. While clinical experiments yield accurate and reliable information about drug-related side effects, they are costly and time-consuming. Computational models have emerged as a promising alternative to predict the frequency of drug-side effects. However, earlier research has primarily centered on extracting and utilizing representations of drugs, like molecular structure or interaction graphs, often neglecting the inherent biomedical semantics of drugs and side effects. RESULTS: To address the previously mentioned issue, we introduce a hybrid multi-modal fusion framework (HMMF) for predicting drug side effect frequencies. Considering the wealth of biological and chemical semantic information related to drugs and side effects, incorporating multi-modal information offers additional, complementary semantics. HMMF utilizes various encoders to understand molecular structures, biomedical textual representations, and attribute similarities of both drugs and side effects. It then models drug-side effect interactions using both coarse and fine-grained fusion strategies, effectively integrating these multi-modal features. CONCLUSIONS: HMMF exhibits the ability to successfully detect previously unrecognized potential side effects, demonstrating superior performance over existing state-of-the-art methods across various evaluation metrics, including root mean squared error and area under receiver operating characteristic curve, and shows remarkable performance in cold-start scenarios.

Monitoring of Adverse Events and Safety in Autoinflammatory Diseases: Real-Life Data from the Eurofever Registry.

OBJECTIVES: The study is aimed to evaluate the impact of safety events in the Eurofever registry for Autoinflammatory diseases. METHODS: This was a retrospective and longitudinal observational multicentre study. Data were retrieved from the international registry Eurofever, starting patients' enrolment since 2009. All moderate, severe, or very severe AEs reported by treating physician in Eurofever were analyzed regardless of a possible suspected causal relationship to any therapies and according to the latest release of the Medical Dictionary for Regulatory Activities. RESULTS: Complete information on safety were available in 2464 patients enrolled in the registry. In 1499 of them retrospective data encompassing the period from disease onset to enrolment were available, whereas 965 consecutive patients entered in the longitudinal part of the study. A total of 479 AEs have been reported in 275 patients. Eighty-two AEs were reported as serious and 99 were drug-related according to the physicians. Infections or infestations (94; 19.6%), gastrointestinal disorders (66; 13.8%), nervous system disorders (41; 8.6%) and systemic disorders or administration site reactions (35; 7.3%) were the most frequent reported events. The highest absolute number of drug-related AEs were related to biologic DMARDs (40/99 reports, 40,4%) and colchicine (31/99 reports, 31.3%). CONCLUSIONS: Present study shows the importance of a longitudinal and homogeneous registration of the AEs in rare conditions, with a particular focus on the safety profile of the treatments used in these conditions.

Evaluation of adverse reactions induced by anti-tuberculosis drugs among hospitalized patients in Wuhan, China: A retrospective study.

The study aims to estimate the incidence and risk factors of adverse drug reactions (ADRs) induced by anti-tuberculosis (TB) drugs. A single center retrospective analysis of patients taking anti-TB therapy from January 2016 to December 2018 in the hospital was conducted. Univariate and multivariate logistic regression analysis were used to identify these risk factors of ADRs induced by anti-TB drugs. Among 1430 patients receiving anti-TB therapy, 440 (30.77%) patients showed at least 1 ADR induced by anti-TB drugs. Hyperuricemia was the most common ADR, followed by hepatic function test abnormality, liver damage and gastrointestinal reactions. Significant differences (P < .05) were also seen in diabetes, age, treatment duration, type of TB (extrapulmonary) and some therapeutic regimens between ADR group and non-ADR group, respectively. Multivariate logistic regression analysis showed that treatment duration (OR = 1.029, 95%CI[1.018-1.040], P = .000), type of TB (extrapulmonary, OR = 1.487, 95%CI[1.134-1.952], P = .004) and some therapeutic regimens (HREZ, OR = 1.425, 95%CI[0.922-2.903], P = .001; HRZS, OR = 2.063, 95% CI[1.234-3.449], P = .006; HRZ, OR = 3.623, 95%CI[2.289-5.736], P = .000) were risk factors for ADRs induced by anti-TB drugs. Anti-TB drugs usually induced the occurrence of severe and frequent adverse effects, such as hyperuricemia. Treatment duration, HREZ, HRZS and HRZ regimens, and type of TB (extrapulmonary) should be considered as high-risk factors. Thus, it should be recommended to consider optimum management during anti-TB therapy, particularly hyperuricemia monitoring and hepatic function test.

A deep learning based multi-model approach for predicting drug-like chemical compound's toxicity.

Ensuring the safety and efficacy of chemical compounds is crucial in small-molecule drug development. In the later stages of drug development, toxic compounds pose a significant challenge, losing valuable resources and time. Early and accurate prediction of compound toxicity using deep learning models offers a promising solution to mitigate these risks during drug discovery. In this study, we present the development of several deep-learning models aimed at evaluating different types of compound toxicity, including acute toxicity, carcinogenicity, hERG_cardiotoxicity (the human ether-a-go-go related gene caused cardiotoxicity), hepatotoxicity, and mutagenicity. To address the inherent variations in data size, label type, and distribution across different types of toxicity, we employed diverse training strategies. Our first approach involved utilizing a graph convolutional network (GCN) regression model to predict acute toxicity, which achieved notable performance with Pearson R 0.76, 0.74, and 0.65 for intraperitoneal, intravenous, and oral administration routes, respectively. Furthermore, we trained multiple GCN binary classification models, each tailored to a specific type of toxicity. These models exhibited high area under the curve (AUC) scores, with an impressive AUC of 0.69, 0.77, 0.88, and 0.79 for predicting carcinogenicity, hERG_cardiotoxicity, mutagenicity, and hepatotoxicity, respectively. Additionally, we have used the approved drug dataset to determine the appropriate threshold value for the prediction score in model usage. We integrated these models into a virtual screening pipeline to assess their effectiveness in identifying potential low-toxicity drug candidates. Our findings indicate that this deep learning approach has the potential to significantly reduce the cost and risk associated with drug development by expediting the selection of compounds with low toxicity profiles. Therefore, the models developed in this study hold promise as critical tools for early drug candidate screening and selection.

BERT-based language model for accurate drug adverse event extraction from social media: implementation, evaluation, and contributions to pharmacovigilance practices.

Introduction: Social media platforms serve as a valuable resource for users to share health-related information, aiding in the monitoring of adverse events linked to medications and treatments in drug safety surveillance. However, extracting drug-related adverse events accurately and efficiently from social media poses challenges in both natural language processing research and the pharmacovigilance domain. Method: Recognizing the lack of detailed implementation and evaluation of Bidirectional Encoder Representations from Transformers (BERT)-based models for drug adverse event extraction on social media, we developed a BERT-based language model tailored to identifying drug adverse events in this context. Our model utilized publicly available labeled adverse event data from the ADE-Corpus-V2. Constructing the BERT-based model involved optimizing key hyperparameters, such as the number of training epochs, batch size, and learning rate. Through ten hold-out evaluations on ADE-Corpus-V2 data and external social media datasets, our model consistently demonstrated high accuracy in drug adverse event detection. Result: The hold-out evaluations resulted in average F1 scores of 0.8575, 0.9049, and 0.9813 for detecting words of adverse events, words in adverse events, and words not in adverse events, respectively. External validation using human-labeled adverse event tweets data from SMM4H further substantiated the effectiveness of our model, yielding F1 scores 0.8127, 0.8068, and 0.9790 for detecting words of adverse events, words in adverse events, and words not in adverse events, respectively. Discussion: This study not only showcases the effectiveness of BERT-based language models in accurately identifying drug-related adverse events in the dynamic landscape of social media data, but also addresses the need for the implementation of a comprehensive study design and evaluation. By doing so, we contribute to the advancement of pharmacovigilance practices and methodologies in the context of emerging information sources like social media.

Adverse events associated with immune checkpoint inhibitors in non-small cell lung cancer: a safety analysis of clinical trials and FDA pharmacovigilance system.

Objectives: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of non-small cell lung cancer (NSCLC). However, the application of ICIs can also cause treatment-related adverse events (trAEs) and immune-related adverse events (irAEs). This study was to evaluate both the irAEs and trAEs of different ICI strategies for NSCLC based on randomized clinical trials (RCTs). The study also examined real-world pharmacovigilance data from the Food and Drug Administration Adverse Event Reporting System (FAERS) regarding claimed ICI-associated AEs in clinical practice. Methods: Based on Pubmed, Embase, Medline, and the Cochrane CENTRAL, we retrieved RCTs comparing ICIs with chemotherapy drugs or with different ICI regimens for the treatment of NSCLC up to October 20, 2023. Bayesian network meta-analysis (NMA) was performed using odds ratios (ORs) with 95% credible intervals (95%CrI). Separately, a retrospective pharmacovigilance study was performed based on FAERS database, extracting ICI-associated AEs in NSCLC patients between the first quarter (Q1) of 2004 and Q4 of 2023. The proportional reports reporting odds ratio was calculated to analyze the disproportionality. Results: The NMA included 51 RCTs that involved a total of 26,958 patients with NSCLC. Based on the lowest risk of any trAEs, cemiplimab, tislelizumab, and durvalumab were ranked as the best. Among the agents associated with the lowest risk of grades 3-5 trAEs, tislelizumab, avelumab, and nivolumab were most likely to rank highest. As far as any or grades 3-5 irAEs are concerned, atezolizumab plus bevacizumab plus chemotherapy is considered the most safety option. However, it is associated with a high risk of grades 3-5 trAEs. As a result of FAERS pharmacovigilance data analysis, 9,420 AEs cases have been identified in 7,339 NSCLC patients treated with ICIs, and ICIs were related to statistically significant positive signal with 311 preferred terms (PTs), and comprehensively investigated and identified those AEs highly associated with ICIs. In total, 152 significant signals were associated with Nivolumab, with malignant neoplasm progression, death, and hypothyroidism being the most frequent PTs. Conclusion: These findings revealed that ICIs differed in their safety profile. ICI treatment strategies can be improved and preventive methods can be developed for NSCLC patients based on our results.

Rare and severe adverse events in children with inflammatory bowel disease: analysis of data from the PIBD-SETQuality Safety Registry.

BACKGROUND: Rare and severe adverse events can occur in children with inflammatory bowel disease (IBD), and the relationship with disease or drug treatment is often uncertain. We aimed to establish a method of reporting adverse events of interest in children with IBD, allowing for estimates of incidence rates with comparison between different regions, and, if possible, to compare with published data on rates of adverse events in children overall. METHODS: For this analysis, we used data from the Paediatric Inflammatory Bowel Disease Network for Safety, Efficacy and Treatment and Quality improvement of care (PIBD-SETQuality) Safety Registry, which collects data on multiple rare and severe adverse events in children younger than 19 years with IBD. Overall, the registry collected data on ten prespecified rare and severe adverse events in children with IBD, as established by a panel of paediatric IBD experts, via reports from paediatric gastroenterologists at participating hospitals between Nov 1, 2016, and March 31, 2023. Reporting physicians, who could only be paediatric gastroenterologists or IBD nurses reporting on behalf of paediatric gastroenterologists, were recruited through invitations sent to both national and international IBD networks and at conferences. Once per month, participating paediatric gastroenterologists received an email with an anonymous and unique link to an online survey asking them to report whether any of ten rare and severe adverse events had occurred in a patient in their paediatric-IBD population in the previous month. Prevalent or retrospective rare and severe adverse events were excluded, as were events occurring in children with an unconfirmed diagnosis of IBD or for whom inflammatory colitis was part of a monogenic immunodeficiency disorder. Duplicates and events that did not meet the definitions and criteria were excluded. Physicians could also report other, non-categorised adverse events if they considered them rare and severe. In case of no response, up to two reminders were sent for each per-month survey. Annual denominator data surveys were sent to obtain the total number of person-years for the estimation of incidence rates, which were calculated via Poisson regression models. FINDINGS: Responses were gathered from 220 paediatric gastroenterologists from 167 centres. 121 centres were in Europe, 23 centres were in North America, 17 centres were in Asia, and six centres were in Oceania. Combined, the total population with paediatric IBD consisted of an estimated 30 193 children with 114 528 person-years of follow-up. 451 adverse events were initially reported. After excluding and reorganising adverse events, 402 were eligible; 261 (65%) were categorised and 141 (35%) were non-categorised. The most frequently reported adverse events were venous-thromboembolic events (n=66), renal failure (n=43), opportunistic infections (n=42), and cancer (n=33). Haemophagocytic lymphohistiocytosis (n=4) and liver failure (n=3) were the least frequently reported adverse events. Incidence rates per 10 000 person-years were 5·50 (95% CI 4·25-6·97) for venous-thromboembolic events, 3·75 (2·74-4·99) for renal failure, 3·67 (2·67-4·89) for opportunistic infection, and 2·88 (2·01-3·98) for cancer. Of 66 venous-thromboembolic events, 31 (47%) involved cerebral venous sinus thrombosis at an incidence rate of 2·71 (95% CI 1·86-3·77). INTERPRETATION: The PIBD-SETQuality Safety Registry enabled us to identify incidence rates of rare and severe adverse events in children with IBD. Our findings can guide physicians and enhance awareness of the incidence of adverse events in children with IBD that are considered to be rare. FUNDING: EU Horizon 2020 Research and Innovation Programme.

Trends in Adverse Event Reporting Before and After the Introduction of the Med Safety App in Nigeria.

INTRODUCTION: Spontaneous reporting of adverse events (AEs) is a mainstay of pharmacovigilance, and an ongoing challenge is how to ensure that more high-quality reports are collected for comprehensive information provision. The Med Safety App, a smartphone-based application, was launched in Nigeria in November 2020 to provide an electronic platform for users to seamlessly report AEs. There has been a paucity of evidence on the use of this application or other mobile applications for reporting adverse drug reactions/AEs following immunization in the Nigerian environment. OBJECTIVE: The aim of this study was to evaluate the trends in adverse event reporting before and after the introduction of the Med Safety App in Nigeria. METHODS: This was a retrospective, observational study using data from the VigiFlow database to compare adverse event reporting in Nigeria before and after the deployment of the Med Safety App. The baseline period was 1st April 2019 to 30th October 2020 and the comparison period was 1st November 2020 to 31st May 2022. We used Vigilance Hub, the back-end system for the Med Safety App, to extract data on App downloads and de-identified user statistics. Data were summarized using descriptive statistics, frequencies and proportions. Quality was assessed by assigning a completeness score to each individual case safety report. The Kruskal-Wallis test was used to test for differences in medians between groups. RESULTS: Following deployment of the App, the Nigerian National Pharmacovigilance Centre recorded an increase in the total number of adverse event reports received in VigiFlow, from 2051 in the baseline period to 18,995 following deployment of the App, with 81.7% of those reported via the Med Safety App. There was a reduction in the proportion of paper-based reporting from 98.4 to 15.7% post-deployment, and direct reporting by consumers increased from 2.7 to 17.6%. Of the 15,526 reports submitted via the App, 15,111 (97.3%) had a completeness score above 70% and 6993 (45%) had a completeness score of 100%. The median completeness score of adverse event reports on the Med Safety App was 6 out of 7. On bivariate analysis using the Kruskal-Wallis test, there was an association between means of reporting and completeness score, and this association was significant, with a p value of 0.0001, which may reflect the validation rules that are applied within the App. CONCLUSION: Deployment of the Med Safety App increased both the number and quality of adverse event reports; however, more awareness and capacity building are needed to strengthen and sustain reporting on the tool by all categories of healthcare professionals and consumers/patients.

An innovative method to strengthen evidence for potential drug safety signals using Electronic Health Records.

Reports from spontaneous reporting systems (SRS) are hypothesis generating. Additional evidence such as more reports is required to determine whether the generated drug-event associations are in fact safety signals. However, underreporting of adverse drug reactions (ADRs) delays signal detection. Through the use of natural language processing, different sources of real-world data can be used to proactively collect additional evidence for potential safety signals. This study aims to explore the feasibility of using Electronic Health Records (EHRs) to identify additional cases based on initial indications from spontaneous ADR reports, with the goal of strengthening the evidence base for potential safety signals. For two confirmed and two potential signals generated by the SRS of the Netherlands Pharmacovigilance Centre Lareb, targeted searches in the EHR of the Leiden University Medical Centre were performed using a text-mining based tool, CTcue. The search for additional cases was done by constructing and running queries in the structured and free-text fields of the EHRs. We identified at least five additional cases for the confirmed signals and one additional case for each potential safety signal. The majority of the identified cases for the confirmed signals were documented in the EHRs before signal detection by the Dutch Medicines Evaluation Board. The identified cases for the potential signals were reported to Lareb as further evidence for signal detection. Our findings highlight the feasibility of performing targeted searches in the EHR based on an underlying hypothesis to provide further evidence for signal generation.