Dataset Information

Characteristics, Quality and Contribution to Signal Detection of Spontaneous Reports of Adverse Drug Reactions Via the WEB-RADR Mobile Application: A Descriptive Cross-Sectional Study.

ABSTRACT: INTRODUCTION:Spontaneous reporting of suspected adverse drug reactions is key for efficient post-marketing safety surveillance. To increase usability and accessibility of reporting tools, the Web-Recognising Adverse Drug Reactions (WEB-RADR) consortium developed a smartphone application (app) based on a simplified reporting form. OBJECTIVE:The objective of this study was to evaluate the characteristics, quality and contribution to signals of reports submitted via the WEB-RADR app. METHODS:The app was launched in the UK, the Netherlands and Croatia between July 2015 and May 2016. Spontaneous reports submitted until September 2016 with a single reporter were included. For each country, app reports and reports received through conventional means in the same time period were compared to identify characteristic features. A random subset of reports was assessed for clinical quality and completeness. The contribution to signal detection was assessed by a descriptive analysis. RESULTS:Higher proportions of app reports were submitted by patients in the UK (28 vs. 18%) and Croatia (32 vs. 7%); both p?

SUBMITTER: Oosterhuis I

PROVIDER: S-EPMC6153975 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Characteristics, Quality and Contribution to Signal Detection of Spontaneous Reports of Adverse Drug Reactions Via the WEB-RADR Mobile Application: A Descriptive Cross-Sectional Study.

Oosterhuis Ingrid I Taavola Henric H Tregunno Philip M PM Mas Petar P Gama Sara S Newbould Victoria V Caster Ola O Härmark Linda L

Drug safety 20181001 10

<h4>Introduction</h4>Spontaneous reporting of suspected adverse drug reactions is key for efficient post-marketing safety surveillance. To increase usability and accessibility of reporting tools, the Web-Recognising Adverse Drug Reactions (WEB-RADR) consortium developed a smartphone application (app) based on a simplified reporting form.<h4>Objective</h4>The objective of this study was to evaluate the characteristics, quality and contribution to signals of reports submitted via the WEB-RADR app. ...[more]

PMID: 29761281

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Project description:Introduction: Post-marketing identification and report of unknown adverse drug reactions (ADRs) are crucial for patient safety. However, complete information on unknown ADRs seldom is available at the time of spontaneous ADR reports and this can hamper their contribution to the pharmacovigilance system. Methods: In order to characterize the seriousness and outcome of unknown ADRs at the time of report and at follow-up, and analyze their contribution to generate pharmacovigilance regulatory actions, a retrospective observational study of those identified in the spontaneous ADR reports of patients assisted at a hospital (January, 2016-December, 2021) was carried out. Information on demographic, clinical and complementary tests was retrieved from patients' hospital medical records. To evaluate the contribution to pharmacovigilance system we reviewed the European Union SmPCs, the list of the pharmacovigilance signals discussed by the Pharmacovigilance Risk Assessment Committee, and its recommendations reports on safety signals. Results: A total of 15.2% of the spontaneous reported cases during the study contained at least one unknown drug-ADR pair. After exclusions, 295 unknown drug-ADR pairs were included, within them the most frequently affected organs or systems were: skin and subcutaneous tissue (34, 11.5%), hepatobiliary disorders (28, 9.5%), cardiac disorders (28, 9.5%) and central nervous system disorders (27, 9.2%). The most frequent ADRs were pemphigus (7, 2.4%), and cytolytic hepatitis, sudden death, cutaneous vasculitis and fetal growth restriction with 6 (2%) each. Vaccines such as covid-19 and pneumococcus (68, 21.3%), antineoplastics such as paclitaxel, trastuzumab and vincristine (39, 12.2%) and immunosuppressants such as methotrexate and tocilizumab (35, 11%) were the most frequent drug subgroups involved. Sudden death due to hydroxychloroquine alone or in combination (4, 1.4%) and hypertransaminasemia by vincristine (n = 3, 1%) were the most frequent unknown drug-ADR pairs. A total of 269 (91.2%) of them were serious. Complementary tests were performed in 82.7% of unknown-ADR pairs and helped to reinforce their association in 18.3% of them. A total of 18 (6.1%) unknown drug-ADR pairs were evaluated by the EMA, in 8 (2.7%) the information was added to the drug's SmPC and in 1 case the risk prevention material was updated. Conclusion: Identification and follow-up of unknown ADRs can be of great relevance for patient safety and for the enrichment of the pharmacovigilance system.

Project description:Pharmacovigilance presents many challenges, particularly when managing unpredictable, rare conditions, eg, severe cutaneous adverse reactions (SCARs). Such rare events are often only detected from spontaneous reports, which present their own limitations, particularly during a prolonged global launch schedule. GlaxoSmithKline's routine pharmacovigilance includes regular reviews of global adverse event (AE) reports and aggregate data from a central safety database. Lamotrigine is one of the several antiepileptic drugs associated with SCARs. After identification of increased rates of fatal SCAR cases with lamotrigine in Japan between September and December 2014, this analysis investigated the global incidence of fatal SCARs with lamotrigine and explored whether known risk factors may have contributed to these cases. Global fatal SCAR cases reported with lamotrigine administration from launch until January 2015 were reviewed for evidence of temporal association with dosing and the presence of risk factors, including comorbidities, concomitant medications, and noncompliance with the prescribing information (PI). Worldwide, the estimated cumulative exposure to lamotrigine was >8.4 million patient-years. Globally, there were 54,513 AE reports for lamotrigine, of which 3,454 (6.3%) concerned SCARs. Of these, 122 (3.5%) had a fatal outcome (attributable and nonattributable to lamotrigine), equating to 0.01 fatal SCARs per 1,000 patient-years. In Japan (estimated cumulative exposure 141,000 patient-years), 17 fatal SCARs were reported (attributable and nonattributable), equating to 0.12 per 1,000 patient-years. Seventy-one percent of fatal SCAR cases in Japan showed evidence of noncompliance with the recommended dosing regimen; in 65% of the cases, a delay in discontinuation of lamotrigine after early signs of hypersensitivity was reported. Despite a number of limitations inherent in comparing spontaneous report data, this analysis highlights the need for adherence to the lamotrigine PI and emphasizes the importance of collaboration between global and local pharmacovigilance departments, to promptly identify and reduce the risk of rare and serious events, such as SCARs.

Project description:INTRODUCTION:A large number of studies on systems to detect and sometimes normalize adverse events (AEs) in social media have been published, but evidence of their practical utility is scarce. This raises the question of the transferability of such systems to new settings. OBJECTIVES:The aims of this study were to develop an AE recognition system, prospectively evaluate its performance on an external benchmark dataset and identify potential factors influencing the transferability of AE recognition systems. METHODS:A pipeline based on dictionary lookups and logistic regression classifiers was developed using a proprietary dataset of 196,533 Tweets manually annotated for AE relations and prospectively evaluated the system on the publicly available WEB-RADR reference dataset, exploring different aspects affecting transferability. RESULTS:Our system achieved 0.53 precision, 0.52 recall and 0.52 F1-score on the development test set; however, when applied to the WEB-RADR reference dataset, system performance dropped to 0.38 precision, 0.20 recall and 0.26 F1-score. Similarly, a previously published method aiming at automatically detecting adverse event posts reported 0.5 precision, 0.92 recall and 0.65 F1-score on thus another dataset, while performance on the WEB-RADR reference dataset was reduced to 0.37 precision, 0.63 recall and 0.46 F1-score. We identified four potential factors leading to poor transferability: overfitting, selection bias, label bias and prevalence. CONCLUSION:We warn the community about a potentially large discrepancy between the expected performance of automated AE recognition systems based on published results and the actual observed performance on independent data. This study highlights the difficulty of implementing an all-purpose system for automatic adverse event recognition in Twitter, which could explain the lack of such systems in practical pharmacovigilance settings. Our recommendation is to use benchmark independent datasets, such as the WEB-RADR reference, to investigate the transferability of the adverse event recognition systems and ultimately enforce rigorous comparisons across studies on the task.

Project description:BackgroundAdverse drug reactions (ADRs) in the pediatric population may differ in types and frequencies compared to other populations. Respective studies analyzing ADR reports referring to children have already been performed for certain countries. However, differences in drug prescriptions, among others, complicate the transferability of the results from other countries to Germany or were rarely considered. Hence, the first aim of our study was to analyze the drugs and ADRs reported most frequently in ADR reports from Germany referring to children contained in the European ADR database (EudraVigilance). The second aim was to set the number of ADR reports in relation to the number of drug prescriptions. These were provided by the Research Institute for Ambulatory Health Care in Germany.MethodsFor patients aged 0-17 years 20,854 spontaneous ADR reports were received between 01/01/2000-28/2/2019. The drugs and ADRs reported most frequently were identified. Stratified analyses with regard to age, sex and drugs used "off-label" were performed. Reporting rates (number of ADR reports/number of drug prescriptions) were calculated.ResultsMethylphenidate (5.5%), ibuprofen (2.3%), and palivizumab (2.0%) were most frequently reported as suspected. If related to the number of drug prescriptions, the ranking changed (palivizumab, methylphenidate, ibuprofen). Irrespective of the applied drugs, vomiting (5.4%), urticaria (4.6%) and dyspnea (4.2%) were the ADRs reported most frequently. For children aged 0-1 year, drugs for the treatment of nervous system disorders and foetal exposure during pregnancy were most commonly reported. In contrast, methylphenidate ranked first in children older than 6 years and referred 3.5 times more often to males compared to females. If age- and sex-specific exposure was considered, more ADR reports for methylphenidate referred to children 4-6 years and females 13-17 years. Drugs for the treatment of nervous system disorders ranked first among "off-label" ADR reports.ConclusionsOur analysis underlines the importance of putting the number of ADR reports of a drug in context with its prescriptions. Additionally, differences in age- and sex-stratified analysis were observed which may be associated with age- and sex-specific diseases and, thus, drug exposure. The drugs most frequently included in "off-label" ADR reports differed from those most often used according to literature.

Project description:BackgroundThe development of anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) has improved the survival outcomes of patients with advanced ALK-rearranged non-small-cell lung cancer (NSCLC). The adverse events (AEs) related to ALK inhibitors are fairly well known; notably, about 20% of patients receiving lorlatinib experienced cognitive effects and behavioral alterations in pivotal trials. Therefore, psychiatric disorders could represent AEs of special interest for all ALK TKIs, deserving careful assessment in the post-marketing setting.ObjectiveWe conducted a real-world pharmacovigilance study on psychiatric AEs with marketed ALK inhibitors in subjects with advanced NSCLC.Patients and methodsWe performed an observational, retrospective analysis of spontaneous reports submitted to the Food and Drug Administration Adverse Events Reporting System (FAERS, as of December 2020), selecting psychiatric AEs to ALK TKIs approved in NSCLC (crizotinib, ceritinib, alectinib, brigatinib, lorlatinib). These AEs were independently scrutinized by three oncologists applying predefined exclusion criteria, described in terms of clinical/demographic features and assessed for drug-related causality according to an adaptation of the WHO-UMC system, a standardized probabilistic algorithm.ResultsAmong 584 reported psychiatric AEs, 95 cases were selected as potentially treatment related, with higher reporting frequency for lorlatinib (26, 2.8%), followed by brigatinib (10, 1.2%), alectinib (18, 0.7%), ceritinib (12, 0.6%), and crizotinib (29, 0.3%). Reported psychiatric symptoms were mood disorders (39), psychotic disorders (24), and anxiety, agitation, and irritability (25). In the majority (74%) of cases, psychiatric AEs were serious and required hospitalization in about 32% of patients; 15.8% of retained cases were considered as highly probable and 69.5% as probable. Drug discontinuation was recorded in 31.6% of the reported cases, with the highest proportion for lorlatinib (65.4%).ConclusionNotwithstanding limitations, our study found a higher proportion of psychiatric AEs with lorlatinib, but also raised the hypothesis of psychiatric reactions as a class effect of ALK TKIs.

Dataset Information

Characteristics, Quality and Contribution to Signal Detection of Spontaneous Reports of Adverse Drug Reactions Via the WEB-RADR Mobile Application: A Descriptive Cross-Sectional Study.

Publications

Characteristics, Quality and Contribution to Signal Detection of Spontaneous Reports of Adverse Drug Reactions Via the WEB-RADR Mobile Application: A Descriptive Cross-Sectional Study.

Similar Datasets

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