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Background There have been no studies of the patterns of post-marketing withdrawals of medicinal products to which adverse reactions have been attributed. We identified medicinal products that were withdrawn because of adverse drug reactions, examined the evidence to support such withdrawals, and explored the pattern of withdrawals across countries. Methods We searched PubMed, Google Scholar, the WHO’s database of drugs, the websites of drug regulatory authorities, and textbooks. We included medicinal products withdrawn between 1950 and 2014 and assessed the levels of evidence used in making withdrawal decisions using the criteria of the Oxford Centre for Evidence Based Medicine. Results We identified 462 medicinal products that were withdrawn from the market between 1953 and 2013, the most common reason being hepatotoxicity. The supporting evidence in 72 % of cases consisted of anecdotal reports. Only 43 (9.34 %) drugs were withdrawn worldwide and 179 (39 %) were withdrawn in one country only. Withdrawal was significantly less likely in Africa than in other continents (Europe, the Americas, Asia, and Australasia and Oceania). The median interval between the first reported adverse reaction and the year of first withdrawal was 6 years (IQR, 1–15) and the interval did not consistently shorten over time. Conclusion There are discrepancies in the patterns of withdrawal of medicinal products from the market when adverse reactions are suspected, and withdrawals are inconsistent across countries. Greater co-ordination among drug regulatory authorities and increased transparency in reporting suspected adverse drug reactions would help improve current decision-making processes.

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.

Reporting of toxic adverse effects of anticancer treatments by clinicians generally results in the underreporting of these toxicities. Patient-reported outcomes, which fully reflect the experiences of patients receiving treatment, offer an alternative to reporting of toxicities by clinicians. In this Perspective, the authors describe the barriers and challenges to routine integration of patient-reported outcomes into clinical trials, and describe the PRO–CTCAE, which is designed to help circumvent some of these challenges. Symptomatic toxicities associated with anticancer treatments, such as nausea and vomiting, are frequently underreported by clinicians, even when data are prospectively collected within clinical trials. Such underreporting can result in an underestimation of the absolute rate of toxicity, which is highly relevant information for patients and their physicians in clinical practice, and for regulatory authorities. Systematic collection of patient-reported outcomes (PROs) has been demonstrated to be a valid, reliable, feasible and precise approach to tabulating symptomatic toxicities and enables symptoms that are missed by clinicians to be detected. In this Perspectives, the barriers and challenges that should be addressed when considering broad integration of PRO toxicity monitoring in oncology clinical trials are discussed, including challenges related to data collection logistics, analytical approaches, and resource utilization. Instruments conceived to enable description of treatment-related adverse effects, from the patient perspective, bring the potential to improve risk-versus-benefit analyses in clinical research, and to provide patients with accurate information, on the basis of previous experiences of their peers.

Introduction The Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and VigiBase ® are two established databases for safety monitoring of medicinal products, recently complemented with the EudraVigilance Data Analysis System (EVDAS). Objective Signals of disproportionate reporting (SDRs) can characterize the reporting profile of a drug, accounting for the distribution of all drugs and all events in the database. This study aims to quantify the redundancy among the three databases when characterized by two disproportionality-based analyses (DPA). Methods SDRs for 100 selected products were identified with two sets of thresholds (standard EudraVigilance SDR criteria for all vs Bayesian approach for FAERS and VigiBase ® ). Per product and database, the presence or absence of SDRs was determined and compared. Adverse events were considered at three levels: MedDRA ® Preferred Term (PT), High Level Term (HLT), and HLT combined with Standardized MedDRA ® Query (SMQ). Redundancy was measured in terms of recall (SDRs in EVDAS divided by SDRs from any database) and overlap (SDRs in EVDAS and at least one other database, divided by SDRs in EVDAS). Covariates with potential impact on results were explored with linear regression models. Results The median overlap between EVDAS and FAERS or VigiBase ® was 85.0% at the PT level, 94.5% at the HLT level, and 97.7% at the HLT or SMQ level. The corresponding median recall of signals in EVDAS as a percentage of all signals generated in all three databases was 59.4%, 74.1%, and 87.9% at the PT, HLT, and HLT or SMQ levels, respectively. The overlap difference is partially explained by the relative number of EU cases in EudraVigilance and the ratio of EVDAS cases and FAERS cases, presumably due to differences in marketing authorizations, or market penetration in different regions. Products with few cases in EVDAS (< 1500) also display limited recall of signals relative to FAERs/VigiBase ® . Time-on-market does not predict signal redundancy between the three databases. The choice of the DPA has an expected but somewhat small effect on redundancy. Conclusions Organizations typically consider regulatory expectations, operating performance (e.g., positive predictive value), and procedural complexity when selecting databases for signal management. As SDRs can be seen as a proxy of general reporting characteristics identifiable in a systematic screening process, our results indicate that, for most products, these characteristics are largely similar in each of the databases.

Introduction The increased access to medicinal products in Africa is not well-matched with the pharmacovigilance capacity to monitor drug safety. The objective of this study was to assess the functionality and identify the strengths and limitations of the national pharmacovigilance systems in Ethiopia, Kenya, Rwanda, and Tanzania, and compare these systems. Methods Legal and statutory documents governing the pharmacovigilance systems of each participating country were examined by assessors prior to on-site review. The staff of the pharmacovigilance unit of the National Medicines Regulatory Authorities (NMRAs) were interviewed using the East African Community Harmonized Pharmacovigilance Indicators tool, supplemented with indicators from the World Health Organization (WHO) Global Benchmarking Tool. Responses were recorded, and data were analyzed. Results The pharmacovigilance systems were supported by law and regulations in line with international standards. Standard operating procedures for receiving, processing, and communicating suspected adverse event reports were in place, but reporting of suspected medicine-related harm from stakeholders was inadequate in all countries. The number of Individual Case Safety Reports (ICSRs) received by NMRAs in Kenya, Ethiopia, and Tanzania (mainland) were 35.0, 6.7, and 4.1 per million inhabitants, respectively, in the last calendar year. At the time of assessment, Rwanda did not have an operational system. Overall, ≤ 1% of the total number of health facilities per country submitted ICSRs. Only Kenya and Tanzania had a designated budget for pharmacovigilance activities and an electronic ICSR reporting system. The national pharmacovigilance systems in all four countries did not have access to data on drug utilization. Conclusions The national pharmacovigilance systems in the four East African countries have policy and legal frameworks defined by law and regulation to conduct pharmacovigilance activities. However, the four national pharmacovigilance systems are at different levels of capacity and performance with respect to conducting pharmacovigilance activities. Targeted interventions are needed to strengthen the pharmacovigilance systems to enable evidence-based decision making for patient safety.

This study aimed to assess the completeness and consistency of adverse event (AE) reporting in ClinicalTrials.gov and corresponding peer-reviewed publications for clinical trials investigating targeted therapeutics for endocrine and metabolic disorders. On September 12, 2022, a search of ClinicalTrials.gov was conducted to identify completed interventional trials investigating targeted therapeutics for the treatment of endocrine and metabolic disorders registered after September 1, 2009. The main outcome was the completeness of AE reporting in ClinicalTrials.gov and corresponding peer-reviewed journal articles. The completeness of registry reporting for serious AEs (SAEs) and other AEs (OAEs) was also assessed, as well as the all-cause mortality (ACM) data for trials with a primary completion date after January 18, 2017. In addition, the study examined the concordance in AE reporting between the two sources. Out of 7405 trials identified in the ClinicalTrials.gov registry, 92 met the inclusion criteria. All trials reported SAEs and OAEs in the registry, and all eligible trials reported ACM data. In the corresponding peer-reviewed journal publications, SAEs were reported for 86% of trials, OAEs for 91%, and ACM data for 64% of eligible trials. Among the trials with complete AE reporting in ClinicalTrials.gov and journal publications, 38% showed discrepancies in the number of participants experiencing SAEs, 86% for OAEs, and 36% for ACM data. In addition, 18% of journal articles used different terminology for reporting of AEs compared to the registry, and 60% applied different frequency thresholds. Our analysis revealed significant discrepancies between registry data and journal articles regarding AE reporting in clinical trials investigating targeted therapy for endocrine and metabolic disorders. Greater efforts are needed to enhance transparency and harmonization in AE reporting, ensuring accurate risk communication and informed clinical decision-making. Accurate reporting of adverse events (AEs) in clinical trials is essential for evaluating the safety of new therapeutics. This study assessed whether safety data reported in clinical trials investigating treatments for endocrine and metabolic disorders were consistently presented in ClinicalTrials.gov and corresponding journal publications. A total of 92 completed clinical trials registered on ClinicalTrials.gov and their published articles were analyzed. Although all trials reported serious AEs (SAEs), other AEs (OAEs), and mortality data in the registry, journal publications frequently omitted these data. Specifically, 86% of journal articles reported SAEs, 91% reported OAEs, and only 64% provided data on mortality. Even when AEs were reported in both sources, inconsistencies were common. Differences in the number of participants experiencing AEs were found in 38% of trials for SAEs, 86% for OAEs, and 36% for mortality data. In addition, 18% of journal articles used different terminology, and 60% applied different thresholds for reporting AEs compared to the registry. These findings underscore substantial inconsistencies between clinical trial registry data and peer-reviewed publications, highlighting the need for improved reporting practices. Greater transparency and standardization in AE reporting are essential to ensure the reliability of safety data for novel therapeutics. •All trials reported SAEs, OAEs, and ACM data in the registry.•SAEs were reported in 86%, OAEs in 91%, and ACM in 64% of journal publications.•Discrepancies between the sources were seen in 38% SAEs, 86% OAEs, and 36% ACM.•Different AE terminology was used in 18% of journal publications.•Different frequency thresholds were used in 60% of journal publications.

•Methods used to generate disproportionality signals are extremely heterogeneous.•Seventy eight percent of studies failed to report methods for case, adverse drug reactions or comparator selection.•One third of studies did not define the threshold for signal generation. To review and appraise methods and reporting characteristics of pharmacovigilance disproportionality analyses. We randomly selected 100 disproportionality analyses indexed in Medline found during a systematic literature search. We then extracted and synthetized methodological and reporting characteristics using seven key items: (1) title transparency; (2) protocol pre-registration; (3) date of data extraction and analysis; (4) outcome, population, exposure and comparator definitions; (5) adjustment and stratification of results; (6) method and threshold for signal detection; (7) secondary and sensitivity analyses. We found that methods used to generate disproportionality signals were extremely heterogeneous; there were nearly as many unique analyses as studies. The authors used various populations, methods, signal detection thresholds, adjustment or stratification variables, generally without justification for their choice or pre-specification in protocols. Moreover, 78% of studies failed to report methods for case, adverse drug reactions or comparator selection and 32 studies did not define the threshold for signal generation. Our survey raises major concerns regarding all aspects of disproportionality analyses that could lead to misleading results and generate unjustified alarms. We advocate for a strong and transparent rationale for variable selection, choice of population and comparators pre-specified in a protocol and assessed by sensitivity analyses.

Numerous observational studies suggest that preventable adverse drug reactions are a significant burden in healthcare, but no meta-analysis using a standardised definition for adverse drug reactions exists. The aim of the study was to estimate the percentage of patients with preventable adverse drug reactions and the preventability of adverse drug reactions in adult outpatients and inpatients. Studies were identified through searching Cochrane, CINAHL, EMBASE, IPA, Medline, PsycINFO and Web of Science in September 2010, and by hand searching the reference lists of identified papers. Original peer-reviewed research articles in English that defined adverse drug reactions according to WHO's or similar definition and assessed preventability were included. Disease or treatment specific studies were excluded. Meta-analysis on the percentage of patients with preventable adverse drug reactions and the preventability of adverse drug reactions was conducted. Data were analysed from 16 original studies on outpatients with 48797 emergency visits or hospital admissions and from 8 studies involving 24128 inpatients. No studies in primary care were identified. Among adult outpatients, 2.0% (95% confidence interval (CI): 1.2-3.2%) had preventable adverse drug reactions and 52% (95% CI: 42-62%) of adverse drug reactions were preventable. Among inpatients, 1.6% (95% CI: 0.1-51%) had preventable adverse drug reactions and 45% (95% CI: 33-58%) of adverse drug reactions were preventable. This meta-analysis corroborates that preventable adverse drug reactions are a significant burden to healthcare among adult outpatients. Among both outpatients and inpatients, approximately half of adverse drug reactions are preventable, demonstrating that further evidence on prevention strategies is required. The percentage of patients with preventable adverse drug reactions among inpatients and in primary care is largely unknown and should be investigated in future research.

Introduction Immune checkpoint inhibitors (ICPI), a breakthrough immunotherapy for cancer, can cause serious neurological adverse events (AEs). We aimed to investigate the characteristics of the neurological and related AEs associated with ICPI treatment, using a large pharmacovigilance database from Japan. Methods We conducted disproportionality analysis using the Japanese Adverse Drug Event Report (JADER) database containing 566,698 patient cases recorded between April 2004 and March 2019, to detect neurological and related AE signals associated with ICPI treatment by calculating reporting odds ratio (ROR). Results Among 7604 cases with ICPI usage, we identified 583 cases (7.67%) with a significantly high reporting of neurological and related AEs (lower 95% of the ROR > 1), including myasthenia gravis (MG), inflammatory myositis, non-infectious encephalitis/myelitis, non-infectious meningitis, hypophysitis/hypopituitarism, and peripheral neuropathy including Guillain–Barre syndrome (GBS). Among the ICPI subtypes, when compared to nivolumab as a reference, number of hypophysitis, hypopituitarism, and meningitis reports from the use of ipilimumab and number of encephalitis/myelitis and meningitis reports from the use of anti-programmed cell death-ligand-1 (PD-L1) agents were significantly higher. Additionally, time to AE onset of symptoms post administration was short in meningitis (median 21 days), MG (median 28 days), myositis (median 28 days), and encephalitis/myelitis (median 32.5 days), while it was longer in peripheral neuropathy (median 42 days), hypophysitis (median 94 days), and hypopituitarism (median 112 days). Conclusions Our results showed characteristic features of neurological and related AEs associated with each ICPI subtype, reported in a large number of Japanese patients. This would help in prompt identification and treatment of neurological AEs associated with ICPI treatment.

Acute kidney injury (AKI) associated with “Triple Whammy” drug therapy consisting of renin-angiotensin system inhibitors, diuretics, and nonsteroidal anti-inflammatory drugs (NSAIDs) has been reported. There have been no reports investigating “Triple Whammy” drug therapy and the time to AKI onset using adverse drug events report databases. The aim of this study was to determine the relationship between the time to AKI onset and treatment with “Triple Whammy” drug therapy. We analyzed AKI cases registered in the Japanese Adverse Drug Event Report database. The data were analyzed using the Kaplan–Meier approach, generalized Wilcoxon tests, and Weibull distribution. AKI was reported in 18,415 cases, of which 7,466 cases used Triple Whammy drugs. All combinations of Triple Whammy drugs were associated with significantly higher odds ratios for reporting AKI. In Weibull analysis, AKI onset was early for most combination patterns of Triple Whammy drugs. The Kaplan–Meier approach showed that the treatment duration to AKI onset was much shorter in cases using NSAIDs; median onsets, 8 days for triple combination, 7 days for NSAIDs added to renin-angiotensin system inhibitors, 9 days for NSAIDs added to diuretics, 6 days for diuretics added to NSAIDs, and 9 days for NSAIDs alone. AKI associated with Triple Whammy drugs is likely to occur in the early stages of treatment, especially with concomitant NSAIDs. Patients should be monitored for the occurrence of AKI within the first 2 weeks.