The Reporting of a Disproportionality Analysis for Drug Safety Signal Detection Using Individual Case Safety Reports in PharmacoVigilance (READUS-PV): Development and Statement.

BACKGROUND AND AIM: Disproportionality analyses using reports of suspected adverse drug reactions are the most commonly used quantitative methods for detecting safety signals in pharmacovigilance. However, their methods and results are generally poorly reported in published articles and existing guidelines do not capture the specific features of disproportionality analyses. We here describe the development of a guideline (REporting of A Disproportionality analysis for drUg Safety signal detection using individual case safety reports in PharmacoVigilance [READUS-PV]) for reporting the results of disproportionality analyses in articles and abstracts. METHODS: We established a group of 34 international experts from universities, the pharmaceutical industry, and regulatory agencies, with expertise in pharmacovigilance, disproportionality analyses, and assessment of safety signals. We followed a three-step process to develop the checklist: (1) an open-text survey to generate a first list of items; (2) an online Delphi method to select and rephrase the most important items; (3) a final online consensus meeting. RESULTS: Among the panel members, 33 experts responded to round 1 and 30 to round 2 of the Delphi and 25 participated to the consensus meeting. Overall, 60 recommendations for the main body of the manuscript and 13 recommendations for the abstracts were retained by participants after the Delphi method. After merging of some items together and the online consensus meeting, the READUS-PV guidelines comprise a checklist of 32 recommendations, in 14 items, for the reporting of disproportionality analyses in the main body text and four items, comprising 12 recommendations, for abstracts. CONCLUSIONS: The READUS-PV guidelines will support authors, editors, peer-reviewers, and users of disproportionality analyses using individual case safety report databases. Adopting these guidelines will lead to more transparent, comprehensive, and accurate reporting and interpretation of disproportionality analyses, facilitating the integration with other sources of evidence.

The REporting of A Disproportionality Analysis for DrUg Safety Signal Detection Using Individual Case Safety Reports in PharmacoVigilance (READUS-PV): Explanation and Elaboration.

In pharmacovigilance, disproportionality analyses based on individual case safety reports are widely used to detect safety signals. Unfortunately, publishing disproportionality analyses lacks specific guidelines, often leading to incomplete and ambiguous reporting, and carries the risk of incorrect conclusions when data are not placed in the correct context. The REporting of A Disproportionality analysis for drUg Safety signal detection using individual case safety reports in PharmacoVigilance (READUS-PV) statement was developed to address this issue by promoting transparent and comprehensive reporting of disproportionality studies. While the statement paper explains in greater detail the procedure followed to develop these guidelines, with this explanation paper we present the 14 items retained for READUS-PV guidelines, together with an in-depth explanation of their rationale and bullet points to illustrate their practical implementation. Our primary objective is to foster the adoption of the READUS-PV guidelines among authors, editors, peer reviewers, and readers of disproportionality analyses. Enhancing transparency, completeness, and accuracy of reporting, as well as proper interpretation of their results, READUS-PV guidelines will ultimately facilitate evidence-based decision making in pharmacovigilance.

Transparency, reproducibility, and replicability of pharmacoepidemiology studies in a distributed network environment.

PURPOSE: Our objective is to describe how the U.S. Food and Drug Administration (FDA)'s Sentinel System implements best practices to ensure trust in drug safety studies using real-world data from disparate sources. METHODS: We present a stepwise schematic for Sentinel's data harmonization, data quality check, query design and implementation, and reporting practices, and describe approaches to enhancing the transparency, reproducibility, and replicability of studies at each step. CONCLUSIONS: Each Sentinel data partner converts its source data into the Sentinel Common Data Model. The transformed data undergoes rigorous quality checks before it can be used for Sentinel queries. The Sentinel Common Data Model framework, data transformation codes for several data sources, and data quality assurance packages are publicly available. Designed to run against the Sentinel Common Data Model, Sentinel's querying system comprises a suite of pre-tested, parametrizable computer programs that allow users to perform sophisticated descriptive and inferential analysis without having to exchange individual-level data across sites. Detailed documentation of capabilities of the programs as well as the codes and information required to execute them are publicly available on the Sentinel website. Sentinel also provides public trainings and online resources to facilitate use of its data model and querying system. Its study specifications conform to established reporting frameworks aimed at facilitating reproducibility and replicability of real-world data studies. Reports from Sentinel queries and associated design and analytic specifications are available for download on the Sentinel website. Sentinel is an example of how real-world data can be used to generate regulatory-grade evidence at scale using a transparent, reproducible, and replicable process.

An Open-Source R Package for Detection of Adverse Events Under-Reporting in Clinical Trials: Implementation and Validation by the IMPALA (Inter coMPany quALity Analytics) Consortium.

Accurate and timely reporting of adverse events (AEs) in clinical trials is crucial to ensuring data integrity and patient safety. However, AE under-reporting remains a challenge, often highlighted in Good Clinical Practice (GCP) audits and inspections. Traditional detection methods, such as on-site investigator audits via manual source data verification (SDV), have limitations. Addressing this, the open-source R package {simaerep} was developed to facilitate rapid, comprehensive, and near-real-time detection of AE under-reporting at each clinical trial site. This package leverages patient-level AE and visit data for its analyses. To validate its efficacy, three member companies from the Inter coMPany quALity Analytics (IMPALA) consortium independently assessed the package. Results showed that {simaerep} consistently and effectively identified AE under-reporting across all three companies, particularly when there were significant differences in AE rates between compliant and non-compliant sites. Furthermore, {simaerep}'s detection rates surpassed heuristic methods, and it identified 50% of all detectable sites as early as 25% into the designated study duration. The open-source package can be embedded into audits to enable fast, holistic, and repeatable quality oversight of clinical trials.

How Aggregate Safety Assessment Planning Supports Investigational New Drug Safety Reporting Decisions.

In June 2021, FDA released a Draft Guidance on Sponsor Responsibilities for IND Safety Reporting and cited components of a recommended Safety Surveillance Plan (SSP). To meet the expectations of the 2021 FDA guidance, sponsors should document their plan for aggregate safety assessment. The Drug Information Association-American Statistical Association Interdisciplinary Safety Evaluation scientific working group has proposed an Aggregate Safety Assessment Plan (ASAP) that addresses this recommendation. The 2021 FDA guidance also discusses potential strategies for unblinded review of safety data from ongoing studies by an independent Assessment Entity, which could occur via planned periodic evaluations or "triggered" reviews based on blinded data assessments. The Assessment Entity reviewing unblinded data makes recommendations as to whether the threshold has been met for submission of an aggregate IND safety report. In this paper, we discuss how the ASAP supports IND aggregate safety reporting decisions, including elements to be included in a proposed SSP appendix to the ASAP. In addition, the authors advocate for the benefits of developing a charter (or specific section of the Data Monitoring Committee charter, if applicable) that describes the responsibilities and conduct of the Assessment Entity. With these components in place, study sponsors will meet the objective of having clearly defined processes for the monitoring of clinical trial safety data in aggregate and making IND safety reporting decisions.

Pharmacovigilance in low- and middle-income countries: A review with particular focus on Africa.

Low- and middle-income countries (LMIC) face unique challenges with regard to the establishment of robust pharmacovigilance systems capable of generating data to inform healthcare policy and practice. These include the limited integration and reliability of pharmacovigilance systems across LMIC despite recent efforts to harmonize pharmacovigilance rules and regulations in several regional economic communities. There are particular challenges relating to the need to translate reporting tools into numerous local languages and the low numbers of healthcare providers relative to number of patients, with very short consultation times. Additional factors frequent in LMIC include high uptake of herbal and traditional medication, mostly by self-medication; disruptive political conflicts jeopardizing fragile systems; and little or no access to drug utilization data, which makes it difficult to reliably estimate the true risks of medicines use. Pharmacovigilance activities are hindered by the scarcity of well-trained personnel with little or no budgetary support from national governments; high turnover of pharmacovigilance staff whose training involves a substantial amount of resources; and little awareness of pharmacovigilance among healthcare workers, decision makers and consumers. Furthermore, little collaboration between public health programmes and national medicines regulatory authorities coupled with limited investment in pharmacovigilance activities, especially during mass drug administration for neglected tropical diseases and mass vaccinations, produces major challenges in establishing a culture where pharmacovigilance is systematically embedded. Very low spontaneous reporting rates with poor quality reports hinders robust signal detection analyses. This review summarises the specific challenges and areas of progress in pharmacovigilance in LMIC with special focus on the situation in Africa.

Optimising reporting of adverse events following immunisation by healthcare workers in Ghana: A qualitative study in four regions.

INTRODUCTION: Despite the emphasis on reporting of Adverse Events Following Immunisation (AEFIs) during didactic training sessions, especially prior to new vaccine introductions, it remains low in Ghana. We explored the factors underlying the under-reporting of AEFI by healthcare workers (HCWs) to provide guidance on appropriate interventions to increase reporting. METHODS: We conducted an exploratory descriptive in-depth study of the factors contributing to low reporting of AEFI among HCWs in four regions in Ghana. Key informant interviews (KII) were held with purposively selected individuals that are relevant to the AEFI reporting process at the district, regional, and national levels. We used KII guides to conduct in-depth interviews and used NVivo 10 qualitative software to analyse the data. Themes on factors influencing AEFI reporting were derived inductively from the data, and illustrative quotes from respondents were used to support the narratives. RESULTS: We conducted 116 KIIs with the health managers, regulators and frontline HCWs and found that lack of information on reportable AEFIs and reporting structures, misunderstanding of reportable AEFIs, heavy workload, cost of reporting AEFIs, fear of blame by supervisors, lack of motivation, and inadequate feedback as factors responsible for underreporting of AEFIs. Respondents suggested that capacity building for frontline HCWs, effective supervision, the provision of motivation and feedback, simplification of reporting procedures, incentives for integrating AEFI reporting into routine monitoring and reporting, standardization of reporting procedures across regions, and developing appropriate interventions to address the fear of personal consequences would help improve AEFI reporting. CONCLUSION: From the perspectives of a broad range of key informants at all levels of the vaccine safety system, we found multiple factors (both structural and behavioural), that may impact HCW reporting of AEFI in Ghana. Improvements in line with the suggestions are necessary for increased AEFI reporting in Ghana.

Improving the data quality of spontaneous ADR reports: a practical example from Malta.

BACKGROUND: Adverse drug reaction (ADR) reporting rates and high-quality data within case summary reports are crucial to detect emerging safety concerns and implement regulatory action. In this study we aimed to improve the data quality and reporting rates of ADR reports in Malta through a series of national activities. RESEARCH DESIGN AND METHODS: Between April 2018 and July 2019, we carried out the following activities: i) a review of wholesale dealers ADR reporting forms; ii) a series of educational workshops targeting physicians and pharmacists; iii) a quality system audit of the Authority's ADR management process. RESULTS: Twelve wholesaler dealer forms were reviewed, and 155 improvements were identified. Incident reporting forms modified to capture ADRs had the most opportunities for improvement. Five workshops were organized and in total 62 physicians and 22 pharmacists attended. Although feedback from participants was positive, in our case, an increase in reporting was not observed following the workshops. The quality system audit resulted in the introduction of the 'four-eye principle' to the Authority's ADR management process. CONCLUSIONS: The implementation of such activities is expected to contribute to the overall pharmacovigilance systems in Malta and our experience could benefit other entities involved in spontaneous ADR reporting.

Post-market surveillance of consumer products: Framework for adverse event management.

Analysis of spontaneous reports of adverse events is an important source of information that can be used to improve consumer products. Various agencies have adverse event reporting requirements and many companies collect such data directly from consumers. Nonetheless, a universal framework is absent that identifies and evaluates spontaneously reported adverse events, and, most important, assesses the potential association between exposure and adverse events. We are presenting a three-part framework: Phase I - Intake and Documentation of Original Incidents; Phase II - In Depth Review and Follow-up of Phase I Incidents (enhanced, tailored questionnaire); Phase III - Association Assessment. The basis for scoring the strength of association between exposure and adverse events requires assessment of standard factors of association including: temporality; biological, physiological, or pharmacological plausibility; results of de-challenge; results of re-challenge; and consideration of confounding factors. Scores tied to the answers to these questions are totaled for each incident to determine the strength of association between exposure and reported adverse event. We propose that consumer product companies come together to adopt such an association assessment framework to improve adverse event management, obtain maximum value from the data obtained, and use the knowledge derived to improve overall product safety for consumers.

The potential of training specialist oncology nurses in real-life reporting of adverse drug reactions.

Specialist oncology nurses (SONs) have the potential to play a major role in monitoring and reporting adverse drug reactions (ADRs); and reduce the level of underreporting by current healthcare professionals. The aim of this study was to investigate the long term clinical and educational effects of real-life pharmacovigilance education intervention for SONs on ADR reporting. This prospective cohort study, with a 2-year follow-up, was carried out in the three postgraduate schools in the Netherlands. In one of the schools, the prescribing qualification course was expanded to include a lecture on pharmacovigilance, an ADR reporting assignment, and group discussion of self-reported ADRs (intervention). The clinical value of the intervention was assessed by analyzing the quantity and quality of ADR-reports sent to the Netherlands Pharmacovigilance Center Lareb, up to 2 years after the course and by evaluating the competences regarding pharmacovigilance of SONs annually. Eighty-eight SONs (78% of all SONs with a prescribing qualification in the Netherlands) were included. During the study, 82 ADRs were reported by the intervention group and 0 by the control group. This made the intervention group 105 times more likely to report an ADR after the course than an average nurse in the Netherlands. This is the first study to show a significant and relevant increase in the number of well-documented ADR reports after a single educational intervention. The real-life pharmacovigilance educational intervention also resulted in a long-term increase in pharmacovigilance competence. We recommend implementing real-life, context- and problem-based pharmacovigilance learning assignments in all healthcare curricula.

Artificial Intelligence for Unstructured Healthcare Data: Application to Coding of Patient Reporting of Adverse Drug Reactions.

Adverse drug reaction (ADR) reporting is a major component of drug safety monitoring; its input will, however, only be optimized if systems can manage to deal with its tremendous flow of information, based primarily on unstructured text fields. The aim of this study was to develop an automated system allowing to code ADRs from patient reports. Our system was based on a knowledge base about drugs, enriched by supervised machine learning (ML) models trained on patients reporting data. To train our models, we selected all cases of ADRs reported by patients to a French Pharmacovigilance Centre through a national web-portal between March 2017 and March 2019 (n = 2,058 reports). We tested both conventional ML models and deep-learning models. We performed an external validation using a dataset constituted of a random sample of ADRs reported to the Marseille Pharmacovigilance Centre over the same period (n = 187). Here, we show that regarding area under the curve (AUC) and F-measure, the best model to identify ADRs was gradient boosting trees (LGBM), with an AUC of 0.93 (0.92-0.94) and F-measure of 0.72 (0.68-0.75). This model was run for external validation showing an AUC of 0.91 and a F-measure of 0.58. We evaluated an artificial intelligence pipeline that was found able to learn how to identify correctly ADRs from unstructured data. This result allowed us to start a new study using more data to further improve our performance and offer a tool that is useful in practice to efficiently manage drug safety information.

Severe Acute Respiratory Syndrome Coronavirus 2 Vaccines and Cutaneous Adverse Reactions: A Review.

We are entering a new stage of the severe acute respiratory syndrome coronavirus 2 pandemic with the initiation of large-scale vaccination programs globally. In these circumstances, even rare adverse effects of vaccines may be encountered more often, if millions of people are to be vaccinated in a short period. Vaccination has the potential for causing cutaneous adverse effects. Thus, it is paramount that dermatologists worldwide are acquainted with the possible skin reaction patterns to the coming vaccines. Herein, we conduct a review to discuss the most frequent cutaneous adverse effects of vaccines and their management, with a particular focus on the expected adverse reactions for the coming severe acute respiratory syndrome coronavirus 2 vaccines, such as local reactions, as well as immediate- and delayed-type hypersensitivity reactions, including erythema multiforme, Stevens-Johnson syndrome, toxic epidermal necrosis, serum sickness-like reactions, and vasculitides. We also discuss the yet unanswered questions on vaccines for which we may soon be asked to provide an expert opinion.

Medical students as adverse drug event managers, learning about side effects while improving their reporting in clinical practice.

Managing adverse drug reactions (ADRs) is a challenge, especially because most healthcare professionals are insufficiently trained for this task. Since context-based clinical pharmacovigilance training has proven effective, we assessed the feasibility and effect of a creating a team of Junior-Adverse Drug Event Managers (J-ADEMs). The J-ADEM team consisted of medical students (1st-6th year) tasked with managing and reporting ADRs in hospitalized patients. Feasibility was evaluated using questionnaires. Student competence in reporting ADRs was evaluated using a case-control design and questionnaires before and after J-ADEM program participation. From Augustus 2018 to Augustus 2019, 41 students participated in a J-ADEM team and screened 136 patients and submitted 65 ADRs reports to the Netherlands Pharmacovigilance Center Lareb. Almost all patients (n = 61) found it important that "their" ADR was reported, and all (n = 62) patients felt they were taken seriously by the J-ADEM team. Although attending physicians agreed that the ADRs should have been reported, they did not do so themselves mainly because of a "lack of knowledge and attitudes" (50%) and "excuses made by healthcare professionals" (49%). J-ADEM team students were significantly more competent than control students in managing ADRs and correctly applying all steps for diagnosing ADRs (control group 38.5% vs. intervention group 83.3%, p < 0.001). The J-ADEM team is a feasible approach for detecting and managing ADRs in hospital. Patients were satisfied with the care provided, physicians were supported in their ADR reporting obligations, and students acquired relevant basic and clinical pharmacovigilance skills and knowledge, making it a win-win-win intervention.

Global COVID-19 pandemic and reporting behavior - An analysis of the Food and Drug Administration adverse events reporting system.

PURPOSE: To describe the characteristics of adverse event reporting in the United States (US) Food and Drug Administration Adverse Event Reporting System (FAERS) before and after the outbreak of the COVID-19 pandemic. METHODS: We included all FAERS reports from the US and Canada from November 7, 2019 to July 15, 2020 and divided the study period into three equal time intervals (pre-pandemic, first pandemic, second pandemic). We focused on methotrexate, a broadly used drug unrelated to COVID-19, and (hydroxy)chloroquine, another broadly used drug implicated in COVID-19 treatment. Using descriptive statistics, we compared reporting characteristics before and after the COVID-19 outbreak. RESULTS: During the study period, 366 998 cases (60% female, median age: 59 years) were submitted to FAERS. The daily median number of reports (1796 in the pre-pandemic, 1810 in the second pandemic time interval) and other characteristics remained stable. The daily median number of reports for methotrexate decreased from 28 in the pre-pandemic to 15 in the second pandemic time interval, with no considerable differences in other characteristics. The daily median number of reports for (hydroxy)chloroquine increased slightly from 1 in the pre-pandemic to 3 in the second pandemic time interval, while there were also changes in the demographics of cases and an increase in the proportion of cases reported by health professionals. CONCLUSIONS: The overall reporting to FAERS did not change after the outbreak of the COVID-19 pandemic. However, some stimulated reporting was observed for (hydroxy)chloroquine, highlighting the need for caution when conducting pharmacovigilance analyses with substances related to COVID-19.

Analysis of completeness for spontaneous reporting of disease-modifying therapies in multiple sclerosis.

Introduction: Considering the need for effective postmarketing surveillance of disease-modifying therapies (DMTs) in multiple sclerosis (MS), we analyzed the potential of the spontaneous reports for safety signal detection, verifying the completeness of the reports in the FDA Adverse Event Reporting System (FAERS).Methods: All reports with DMTs for MS considered the primary suspect cause of ADRs and registered between January 2004 and June 2019 were selected. The vigiGrade completeness score was applied and reports with a score greater than 0.80 were considered well documented. Descriptive statistical analysis and comparisons of well-documented reports by DMTs were performed.Results: A total of 297,926 reports were analyzed. The lowest completeness rates were observed for type of report (13.5%), dose (62.7%), and time from treatment start to the ADR (79.0%). Overall, 80.8% of reports were classified as well documented and those related to natalizumab had the highest proportion (92.4%, p < 0.001), while the lowest was observed for reports sent in 2017 (53.1%, p < 0.001) and for teriflunomide (48.5%, p < 0.001).Conclusions: The high proportion of well-documented reports for DMTs indicates that they can be a valuable source for safety signal detection. A more careful analysis should be performed for data from the groups identified with low completeness to avoid the disclosure of spurious results.