Drug Safety最新文献

Background: Affective disorders, particularly depression, are common among women of childbearing age, and pregnancy often exacerbates symptoms. Antidepressants are often required for treatment, but adherence during pregnancy is variable. Although some studies suggest potential risks to the foetus, many cannot rule out confounding by indication. In this context, understanding real-world patterns of antidepressant prescription and adherence during pregnancy is essential to inform clinical practice and ensure adequate mental healthcare.

Objective: The aim of the present study was to characterise the use of antidepressants in a cohort of pregnant women using electronic health records.

Methods: This observational cohort drug-utilisation study assessed antidepressant prescription patterns, adherence and persistence among pregnant women using data from the SIDIAP (Information System for the Development of Research in Primary Care) database in Catalonia from January 2011 to June 2020.

Results: Among 99,605 pregnancies, 14.9% involved antidepressant prescriptions, but only 5.8% of these were collected from pharmacies. The median pregnancy duration was 38.4 weeks, and the median maternal age was 33.5 years. Anxiety was the most common health issue associated with an antidepressant prescription. Paroxetine was the most frequently prescribed antidepressant, although sertraline usage increased over time. Antidepressant prescriptions and adherence decreased during pregnancy, with an increase in the postpartum period. About 11.6% of pregnancies involved a concurrent prescription of another antidepressant, and 29.2% of women resumed antidepressant use after pregnancy. Women who initiated antidepressants during pregnancy were more likely to persist with treatment than those with pre-existing prescriptions.

Conclusions: Our study describes antidepressant use during pregnancy in Catalonia. It is remarkable that there is a notable gap between antidepressant prescriptions and dispensations. Given the risks of untreated maternal depression, strengthening primary care with adequate resources and personalised support is essential for improving perinatal mental healthcare.

Background: Understanding changes over time in the quantity and characteristics of reports submitted to pharmacovigilance centres is crucial for accurately interpreting safety signals associated with exposure during pregnancy.

Objective: We aimed to assess temporal changes in the outcome measures for signal detection, specifically the number and clustering of reported adverse events concerning maternal valproate exposure and neurodevelopmental outcomes in offspring.

Methods: An observational study using VigiBase analysed changes in the number of reports and event clustering related to neurodevelopmental outcomes in offspring following valproate exposure during pregnancy. Reports from the start of VigiBase till 3 April, 2023 were identified using the VigiBase pregnancy algorithm. Time trend graphs illustrated reporting behavioural changes, with particular focus on the impact of major scientific publications and regulatory decisions. Report clusters, identified by the vigiGroup method, were randomised and independently reviewed by three qualified reviewers for clinical relevance to neurodevelopmental outcomes, morphological disorders or other entities.

Results: Over time, an increase in reports mentioning neurodevelopmental outcomes and a more diverse pattern of adverse events for valproate has been reported. An increase in the number of reports following key publications and international regulatory guidelines was visible.

Conclusions: Our study revealed an increase over time in reporting and awareness of neurodevelopmental outcomes and valproate exposure during pregnancy, following important publications and regulatory decisions. However, the extent to which these developments contributed to the observed increase remains unclear.

Introduction: Yellow Card Vaccine Monitor (YCVM) was established by the UK Medicines and Healthcare products Regulatory Agency (MHRA) to facilitate active monitoring of adverse drug reactions following COVID-19 vaccination and further characterise safety in populations under-represented in clinical trials.

Objective: This study explored the profile of individuals registered to the YCVM platform and the suspected adverse drug reactions reported following a COVID-19 vaccination on this data platform.

Methods: Using a stratified random selection approach, individuals were invited to register and actively contacted to seek further information on the vaccines received and adverse reactions they experienced. Exploratory analyses were conducted to characterise the demographics of individuals registered in the YCVM, and to summarise the adverse drug reaction data reported by recruited individuals between November 2020 and December 2022. Detailed analyses of the sub-cohort of pregnant and breastfeeding females were conducted to characterise these individuals. Data for two suspected adverse reactions, menstrual disorders and tinnitus, were extracted and analysed to demonstrate how YCVM supported regulatory assessment of these safety signals which originally arose from other data sources.

Results: 36,604 individuals registered, with 30,281 reporting vaccination. Median (interquartile range) follow-up was 184 days (14-367). Demographics of the recruited cohort reflected the vaccinated population and timing of invitations. 15,764 (52.1%) of those reporting vaccination reported experiencing at least one adverse reaction. However, nearly all were expected acute reactions and 4134 (13.7%) reported an event considered medically serious. The data raised no safety concerns in pregnant and breastfeeding females. Reporting of menstrual disorders appeared stimulated by media interest, as seen in spontaneous reporting systems. Data on the incidence of tinnitus were used to support regulatory action on this signal.

Conclusion: Active surveillance using the YCVM provided a complementary data source for monitoring the safety of COVID-19 vaccines. However, further efforts are needed to recruit ethnic minorities. The technology developed has enhanced regulatory vigilance options and could be valuable in the future for actively monitoring the safety of innovative products used in small populations.

Background and objective: Missing data and unmeasured confounding may bias results of external comparator (EC) studies. Previous research quantified these effects, but there were still knowledge gaps in terms of studying a broader set of missing data-handling approaches. This knowledge gap is addressed by investigating four different ways to handle missing data for a set of four distinct marginal estimators.

Methods: An extensive simulation study was conducted based on two real EC case studies. Four different variants of missing data-handling approaches were assessed in terms of bias and other performance characteristics. Specifically, multiple imputation (MI) for the trial and EC cohorts was conducted by applying within-cohort MI, across-cohort MI and a mixed within-across-cohort MI scheme. Dropping a covariate from the analysis model if missingness exceeded a certain threshold was also added as an analysis strategy. All simulation results were generated for a set of four marginal estimators: the average treatment effect of the untreated (ATU), the average treatment effect (ATE), the average treatment effect of the treated (ATT), and the average treatment effect in the overlap population (ATO). Missingness was simulated to occur only in the EC cohort, and propensity score weighting was applied as causal inference method.

Results: Overall, within-cohort MI and the ATU showed best performance in terms of mitigating bias, while the strategy of leaving out prognostic factors (covariates) due to a higher percentage of missingness performed worst.

Conclusions: Performances of four missing data-handling strategies were assessed for a set of four different marginal estimators. Our results add clarity with regard to potential residual bias for researchers conducting EC studies when using propensity score weighting in the case of missing data or unmeasured confounding. This enables researchers to select most appropriate statistical approaches to minimise bias, potentially by including an additional bias estimation and correction step.

The evaluation of safety data by the US Food and Drug Administration (FDA) is a critical step in the review of marketing applications for drugs and biologics. It can be difficult to identify a safety signal, and important signals can be missed if not evaluated comprehensively. Adverse events reported by study participants constitute a major source of safety data, and while previously established standard term groupings have been useful for analysis (e.g., Standardised MedDRA^® Queries), the Office of New Drugs (OND) at the FDA determined a need for more clinically meaningful groupings specifically designed for use in premarket drug safety evaluation. To improve safety signal detection and analyses of adverse reactions, OND developed standard groupings of adverse event terms known as OND Custom Medical Queries (OCMQs). OCMQs are intended to capture clinically meaningful groupings (i.e., safety signals) represented in premarketing data. OND has seen great utility in OCMQs during premarket drug safety evaluations, as they have improved OND's ability to detect safety signals and to distinguish and quantify adverse reactions in clinical trial data.

Background: Preventing fetal exposure to teratogenic medications is an important target for risk mitigation efforts. Decisions about risk mitigation efforts specific to teratogenic medications are complex.

Objectives: The Teratogenic Risk Impact and Mitigation (TRIM) tool was developed as an innovative decision support tool to facilitate prioritization of teratogenic medications for risk mitigation strategies.

Methods: We employed a modified Delphi study design involving experts across teratology, obstetrics/gynecology, and medication safety. Panelists proposed decision criteria in three focus groups, followed by e-Delphi rounds to reach a consensus on criteria regarding three dimensions: (1) completeness; (2) relevance; and (3) distinctiveness. Aggregated feedback from each round was used to inform revision of the criteria in subsequent rounds.

Results: A total of 33 candidate criteria proposed by 32 focus group participants were organized into ten distinct criteria for the Delphi process. Consensus (defined as > 85% agreement on all three dimensions) was reached after three e-Delphi rounds, resulting in six criteria: (1) background use among persons of reproductive potential; (2) overall medication benefit considering severity of the indication and availability of alternatives; (3) seriousness of the teratogenic outcome; (4) risk of the teratogenic outcome; (5) certainty regarding teratogenicity; and (6) the risk of exposure during pregnancy.

Conclusions: We established measurable criteria to inform decisions when prioritizing teratogenic medications for risk mitigation programs. Criteria are consensus based and consistent with relevant regulatory guidance. Future work will operationalize these criteria and determine specific weights to facilitate medication-specific TRIM scores. Through its explicit framework, the TRIM tool may support consistent, transparent, and rational decision making and help optimize the contribution of risk mitigation programs to public health.

Background: Functional active safety surveillance is essential for post-authorization assessment and life-cycle safety evidence generation of vaccines and medicines. Data collected through active surveillance methods are routinely used for post-approval surveillance of novel vaccines and medicines. Implementing these methods in low- and middle-income countries remains challenging.

Objective: This systematic review identified and assessed existing active safety surveillance in low- and middle-income countries, including key features, strengths, and limitations.

Methods: A search of EMBASE and PubMed Google Scholar databases was conducted. The protocol was registered with PROSPERO and adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Findings were synthesized narratively and categorized by surveillance systems characteristics.

Results: Of 13,027 records identified, 423 publications met inclusion criteria. Articles spanned 96 low- and middle-income countries, with India (96), China (57), Brazil (30), Iran (26), Ethiopia (21), Indonesia (20), Uganda (18), Kenya (17), and Ghana (16), most represented. The majority focused on vaccines (211). A total of 127 articles utilized mobile technologies for follow-up, online data collection, and/or adverse event reporting. Fifteen percent of vaccine surveillance systems described in articles demonstrated flexibility to incorporate new vaccines, 34% reported multi-sectoral collaborations, and 10% involved multiple countries. Gaps identified include small sample sizes, lack of sustainability, limited flexible surveillance, staffing challenges, and limited use of standard case definitions and digital technologies.

Conclusions: Active safety surveillance in low- and middle-income countries has made progress but still faces challenges. The capture and management of safety data through harmonized digital tools that promote consistency in recording and reporting and cross-country collaborations are crucial in further strengthening active safety surveillance in low- and middle-income countries.