Drug Safety最新文献

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: The US Food and Drug Administration (FDA)-mandates Risk Evaluation and Mitigation Strategy (REMS) programs for certain drugs with serious side effects help ensure that the benefits of use outweigh the risks. REMS materials-including enrollment forms, fact sheets, and medication guides-inform patients and caregivers about drug risks and program requirements.

Objective: To explore how effectively REMS materials communicate drug risk information and program requirements to patients and caregivers and to identify patients' and caregivers' preferences for risk communication.

Methods: Interviews with patients and caregivers of patients prescribed REMS-covered drugs focused on REMS materials. Transcripts were coded manually, with answers to closed-ended questions tabulated in Excel.

Results: The study included 43 patients and six caregivers across eight REMS-covered drugs: alemtuzumab, ambrisentan, clozapine, isotretinoin, lenalidomide, pegvaliase, pomalidomide, and sodium oxybate. Most participants were female (N = 42, 86%), white/non-Hispanic (N = 40, 82%), and college educated (N = 37, 76%). The average age was 40 years, with 27 (55%) having annual family incomes over $100,000. Most participants learned about REMS-covered drugs via printed information (N = 36, 73%), mostly REMS materials; conversations with providers about drug risks and benefits (N = 29, 59%); and websites found on their own (N = 42, 86%). Nearly all participants (N = 47, 96%) felt well-informed about drug risks and benefits, and most participants taking self-administered drugs (N = 28, 67%) reported understanding safe use "very well." However, knowledge gaps emerged around REMS-related risks and reasons for safe use measures; some participants misunderstood REMS enrollment forms as legal protections, not safety measures. Patients also widely varied in their valuations of REMS materials, with some feeling informed and empowered and others confused or intimidated. Preferences for risk communication varied; most participants (N = 36, 73%) wanted to receive information verbally from providers, with several wanting visual aids, summaries, and other resources.

Discussion: Gaps in patients' and caregivers' understanding of REMS programs and drug risks highlight the merits of reviewing communication materials and strategies. Clear, concise, and comprehensive educational documents could promote understanding and adherence to REMS requirements.

Background: Medicine shortages are an increasing threat to medicine safety and access. In Australia, a 7-month shortage of Coumadin 5-mg tablets (Dec 2022-Jul 2023) prompted Therapeutic Goods Administration (TGA) intervention via the Serious Scarcity Substitution Instrument (SSSI), allowing pharmacists to substitute 5-mg warfarin tablets with lower-strength tablets. Understanding the impact of this shortage on anticoagulant use and safety is essential for informing future regulatory responses.

Aims: The aim of this study was to assess the impact of the 2023 warfarin shortage in Australia on dispensing of warfarin and direct oral anticoagulants (DOACs), International Normalised Ratio (INR) testing, and adverse event reporting.

Methods: Monthly national dispensing data (January 2020-August 2024) were obtained from Pharmaceutical Benefits Scheme (PBS) Date of Supply data. INR pathology data were sourced from Services Australia. The TGA Medicines Shortages Database identified relevant shortage periods. Warfarin-related adverse events were extracted from the TGA Database of Adverse Event Notifications. Interrupted time series assessed changes in dispensing and INR testing trends over time.

Results: Warfarin dispensing declined by 1094 prescriptions per month prior to March 2023 (p < 0.0001). A short-term increase occurred in March 2023 (+ 8625 prescriptions; p = 0.0017) following implementation of the SSSI, although this was not sustained. At the warfarin strength level, dispensing rose for warfarin 1 mg and 2 mg but fell for 5 mg, with subsequent compensatory increases; 3 mg remained stable. DOAC dispensing increased steadily before March 2023 (+ 3771 prescriptions per month; p < 0.0001) but declined thereafter (- 3056 per month; p < 0.0001), most notably for rivaroxaban and dabigatran, while apixaban decreased non-significantly. INR testing briefly increased during the shortage and SSSI. A modest rise in haemorrhage-related adverse events was observed.

Conclusion: Warfarin supply was maintained during the 2023 shortage through strength-based substitution under the SSSI, with limited impact on DOAC dispensing.

BACKGROUND AND OBJECTIVES: SCORe of Toxic Epidermal Necrolysis (SCORTEN) and ABCD-10 have been developed as scoring systems for predicting mortality associated with Stevens-Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN). These scores were developed based on a small number of patients; hence, their generalizability requires further exploration. The present study used three algorithms, including a machine learning method, to construct a mortality prediction model for SJS/TEN and to identify new candidate predictors of mortality from severe drug eruptions.

Methods: Data from 5966 patients with SJS or TEN were extracted from the Japanese Adverse Drug Event Report Database. A mortality prediction model was then constructed using stepwise regression, L1 regularized-logistic regression, and random forests based on the patient characteristics (e.g., age, sex, primary disease, adverse events, drug classification, route of administration) and outcomes (death).

Results and discussion: The mortality prediction models for SJS/TEN identified sex (men), primary disease (hyperlipidemia, diabetes mellitus, renal dysfunction, and malignant tumors), adverse events (renal dysfunction, liver dysfunction, respiratory dysfunction, bacteremia/sepsis, disseminated intravascular coagulation syndrome, shock, and multiple organ failure), number of concomitant drugs, and route of administration (injection) as common factors associated with mortality.

Conclusions: Our findings showed that sex, hyperlipidemia as the primary disease, number of concomitant drugs, use of antipyretic analgesics, and route of administration may be considered as predictors of mortality in patients with SJS/TEN. The external validity of these factors needs to be examined in the future.