Drug Safety最新文献

Introduction: In drug-safety monitoring systems, adverse events (AEs) associated with the use of medical products often consist of complex patterns of clinical events. Network analysis (NA) was used for pattern recognition and characterizing the Vaccine Adverse Event Reporting System (VAERS), but limited applications of NA to the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) left its network description incomplete.

Methods: In this analysis, the network properties of FAERS were characterized and leveraged to facilitate pattern discovery. Reported AE information in FAERS is represented using preferred terms (PTs) in Medical Dictionary for Regulatory Activities terminology. The FAERS subsets were analyzed with drugs and PTs as nodes and interconnections as edges. Global characteristics, like the scale-free nature of the distribution, were examined to explore theoretical and structural considerations. Metrics that assess connectivity and edge weighting algorithms based on report co-occurrence or clustering were applied.

Results: Serious AE reports from 2016 to 2023 (2,062,099) were represented as a network of 20,965 nodes (16,847 PTs and 4116 drugs) with more than four million interconnections. Characteristics of FAERS subnetworks were determined with heavy-tailed degree distributions, high local clustering, and low diameters. Complexities related to structural and evolutionary characteristics were revealed as the log-normal model fits the degree distribution better than the power law.

Conclusions: Network-based techniques identified clinically relevant patterns and clustering patterns representative of known adverse drug reactions. Comparisons to VAERS reveal similarities in networks of AE reporting systems. This initial systematic application of NA to FAERS describes the overall network characteristics of the FAERS database and provides insight into the use of network applications in drug safety research.

Introduction: Major congenital malformations (MCMs) are a primary outcome of interest in pregnancy safety studies.

Objective: This study aimed to identify and summarize algorithms used to identify MCMs in routinely collected healthcare data sources in the USA, Canada, and Europe by conducting a systematic literature review.

Methods: We developed a search strategy to identify studies containing algorithms for MCMs from January 1, 2010, to April 11, 2025. Search terms included those related to MCMs as an outcome, routinely collected healthcare data, epidemiologic designs likely to incorporate algorithms, and pregnant individuals and/or infants. Study review and data extraction was conducted in duplicate using a standardized data collection form.

Results: Among the initially identified 2242 studies, 974 were selected for full-text review. Of these, 70.3% were excluded, leaving 289 studies. Over half (58.1%) of the included studies were from Europe, predominantly from Nordic countries using national register data (N = 135; 80.4%). Studies using claims (18.0%) or hospital discharge data (16.3%) were also common. Although there was heterogeneity in the timing of MCM assessment, 55.7% of studies collected MCMs through the infant's first year of life. Overall, algorithms varied across data source type and geography in the codes specified, rules, utilization of maternal versus infant records, and coding system. There were 27 (9.3%) validation studies, 70.4% of which were based on claims and/or electronic health record data only. Most had positive predictive values >70%, though this varied according to MCM type or anatomical site.

Conclusion: We provide the first comprehensive systematic literature review of algorithms used to identify MCMs in routinely collected healthcare data, aiding researchers in their ability to generate reliable evidence in pregnancy safety pharmacoepidemiology.

Background: Piperacillin-tazobactam combined with vancomycin is widely employed for broad-spectrum empiric coverage but has been increasingly associated with acute kidney injury (AKI). The comparative renal safety of substituting vancomycin with teicoplanin remains uncertain.

Objective: This meta-analysis aimed to evaluate renal outcomes between piperacillin-tazobactam plus teicoplanin (TZP-TEI) versus piperacillin-tazobactam plus vancomycin (TZP-VAN).

Methods: PubMed, Scopus, and Cochrane Central were searched for studies comparing TZP-TEI versus TZP-VAN in hospitalized patients. The primary outcome was AKI incidence, defined by Kidney disease: Improving global outcomes (KDIGO) or RIFLE (Risk of renal dysfunction, Injury to kidney, Failure or Loss of kidney function, and End-stage kidney disease) criteria. Data were analyzed using Review Manager, with heterogeneity assessed via the I² statistic.

Results: A total of 908 patients were included from five cohort studies, four of which applied propensity-score matching (PSM), with reported ages ranging from 56.8 to 79 years. The TZP-TEI regimen was associated with a significantly reduced rate of AKI compared with TZP-VAN (odds ratio [OR] 0.52; 95% confidence interval [CI] 0.30-0.89; p = 0.02; I² = 51%). No statistically significant differences were observed between groups for AKI recovery (OR 0.68; 95% CI 0.41-1.12; p = 0.13; I² = 0%) or for 30-day all-cause mortality (OR 1.34; 95% CI 0.77-2.32; p = 0.30; I² = 0%). Subgroup analyses stratified by AKI severity (KDIGO stages 1-3 or RIFLE criteria) demonstrated consistent directionality across stages, with no significant differences observed within PSM or non-PSM cohorts.

Conclusion: The TZP-TEI combination was associated with a significantly lower incidence of AKI than was TZP-VAN. Further studies are warranted to validate these findings, optimize teicoplanin dosing within the TZP-TEI combination, and inform therapeutic drug monitoring implementation in high-risk hospitalized patients.

Introduction: At times it is necessary to withdraw drugs after they have been approved because of lack of effectiveness or safety concerns. Health Canada does not keep a list of withdrawn drugs.

Objective: The aim of this study was to generate a list of all drugs approved since 1990 and subsequently withdrawn from the Canadian market for safety or effectiveness reasons until the end of 2024. This list was used to examine trends in the number of withdrawals and the percent of new drugs that are approved but eventually withdrawn.

Methods: A list of withdrawn drugs was developed based on previous published research and supplemented by examining lists of withdrawn drugs in other jurisdictions. The time, in years, was calculated between the date of approval and withdrawal. The reasons for withdrawal came from either Health Canada documents or, if unavailable, from international sources. Withdrawals for commercial reasons were not included in the analysis.

Results: Of the 1094 drugs approved from January 1, 1990, to December 31, 2024, a total of 37 were withdrawn: 32 were new active substances (molecules never marketed before in any form) and five were other types of new drugs. The median time to withdrawal was 3.60 years (interquartile range 2.45-9.50). Approximately 5% of all new active substances approved in a 5-year period were eventually withdrawn over the period 1990-2009. Between 2010 and 2019, the withdrawal rate was < 2%. The most common reasons for withdrawal were cardiac and liver complications.

Conclusion: As a percent of all drugs approved, relatively few drugs are withdrawn, and the number of drug withdrawals as a percent of approvals declined between 2010 and 2019.

Background: Problems with medication management are consistently identified as key concerns for the quality of residential aged care (RAC). Incident reports can provide valuable information on key issues related to medication management; however, few studies have explored medication incidents in RAC settings.

Objectives: To investigate the characteristics of medication incidents at different stages of medication management and identify the risk factors associated with incidents.

Methods: A retrospective longitudinal cohort study was conducted using medication incidence data from 25 RAC facilities in New South Wales, Australia. All medication incidents between 1 July 2014 and 31 August 2021 relating to 5709 aged care residents aged ≥ 65 years were included. The outcome measure was the medication incidence rate (IR), quantified as the number of medication incidents per 1000 resident days. A multilevel Poisson regression model was performed to identify risk factors associated with exposure to medication incidents.

Results: A total of 5708 medication incidents were analysed. The overall medication IR was 1.81 per 1000 resident days (95% CI 1.76, 1.86). Of 5709 residents, 35% (n = 2016) had at least one recorded medication incident, of which 1095 (> 50%) had more than one. The majority of the incidents were associated with medication administration (3023 incidents, 53%), followed by supply (n = 1546, 27%) and monitoring the response to the medication (n = 548, 9.6%). The outcome of the incident on residents was reported in 5165 (90%) incidents, with 724 (14%) requiring the resident to be monitored by the hospital, general practitioner (GP), or staff. Respite admissions were associated with a higher risk of medication incidents including potentially harmful incidents, compared with permanent admissions (rate ratio (RR) = 1.908, 95% CI 1.646, 2.211, p < 0.01). Residents with Parkinson's disease had a 1.5-fold greater risk of a medication incident (RR = 1.586, 95% CI 1.318, 1.908) compared with residents without Parkinson's. The administration of more than five medications (polypharmacy) was associated with an increased risk of medication incidents (RR = 2.019, 95% CI 1.930, 2.111).

Conclusions: Medication incidents affected more than one-third of older adults in RAC facilities. Improvement strategies should focus on medication administration, supply and monitoring, with particular attention given to respite residents and those with multimorbidity and polypharmacy.

Introduction: Adverse drug reactions (ADRs), including those resulting from drug interactions, remain a leading cause of morbidity and mortality. Structured product labels (SPLs) serve as a primary source for drug safety information. Having machine-readable product labels, including adverse reactions (ARs) and drug interactions, readily available would allow researchers to streamline medication safety studies. However, extracting this information is complex and requires the use of natural language processing (NLP) methods.

Objective: In this study, we explored the application of generative language models in the extraction of drug safety information from SPLs.

Methods: We compared multiple generative LLMs (GPT, Llama, and Mixtral) to two baseline methods in the task of extracting adverse reactions (ARs) from SPLs. We explored various factors, such as prompting strategies and term complexity, that impact the performance of these models in the extraction of ARs. Finally, we explored the generative models' capacity to extract drug interactions from a separate section of SPLs without additional fine-tuning or training, demonstrating their flexibility and adaptability for information retrieval.

Results: We found that generative language models, specifically GPT-4, are able to match or exceed the performance of previous state-of-the-art models without additional training or fine-tuning. Additionally, we found that the specific SPL section, surrounding context, and complexity of the AR term impacted the extraction performance. Finally, we demonstrated the generalizability of these models by applying them to a separate task of extracting drug names from the drug interaction section where curated training data are not available.

Conclusion: Generative language models demonstrate significant potential for automating drug safety information extraction from SPLs, offering a promising avenue for improving post-market surveillance and reducing ADRs. Future work should focus on refining prompting strategies and expanding the models' capabilities to handle increasingly complex and nuanced drug safety information.

Background: Adverse event reporting systems are an important source of safety signals for drug use in pregnancy, but their usefulness in the identification of potential drug-drug interactions (DDIs) remains unclear.

Objective: Our objective was to explore the reliability of signal detection for pharmacokinetic DDIs during pregnancy in adverse event reporting systems, focusing on potential interactions between antipsychotics (APs) or antidepressants (ADs) and drugs modifying cytochrome P450 (CYP450) activity, increasing the occurrence of gestational diabetes mellitus (GDM).

Methods: Reports related to the use of drugs during pregnancy were identified in VigiBase, the World Health Organization (WHO) global database of adverse event reports. Potential interacting drugs were selected based on WHO Drug Standardised Drug Groupings for CYP450 isoenzymes involved in the metabolic pathway of the AP or AD of interest. We conducted statistical interaction analysis using the omega disproportionality measure and including concomitant medication to identify potential DDIs, followed by a case series review for supporting evidence. Evaluation was subjective by author consensus.

Results: Of the 30 drug-drug-event combinations considered, statistical signals emerged for escitalopram, citalopram, and sertraline and the simultaneous use of CYP2D6 inhibitors with a higher relative reporting rate of GDM. However, case series review of reports did not support the existence of these DDIs because of uncertainties regarding the actual timing of medication use reported as concomitant.

Conclusion: Statistical signals of DDIs between ADs and potential interacting drugs during pregnancy were identified but not pursued further after case reviews. Uncertainty around medication use and event timing affected the reliability of the outcomes. These findings highlight the need to validate signals using detailed report data and stress the importance of accurate medication reporting.

Background: Risk management plans (RMPs) are a critical element of pharmacovigilance. However, few studies have examined the quality and type of information included in RMPs, and none has examined the RMPs in the Australian medicines regulatory context.

Objectives: This study aims to characterise safety concerns, particularly missing information listed in the current Australian RMPs for commonly used biologic medicines, and identify additional pharmacovigilance and risk minimisation activities proposed to address identified gaps.

Methods: A descriptive review of RMPs included in the Australian Public Assessment Reports (2009-2024) was performed for 15 biologic medicines approved for use and universally funded in Australia for inflammatory arthropathies, inflammatory bowel diseases and inflammatory skin conditions. We extracted and quantified safety concerns (important identified risks, important potential risks and missing information) from the latest Australian Public Assessment Reports, and further categorised missing information by specific populations and conditions. We then qualitatively described the additional activities proposed.

Results: There were 246 safety concerns listed for the 15 medicines of interest: 85 important identified risks (34.6%), 81 important potential risks (32.9%) and 80 instances of missing information (32.5%). More than half (n = 9, 60%) of the reviewed medicines listed children and adolescents as the most common populations with missing information. Pregnant women (n = 8, 53%) and those with hepatic and renal impairment (n = 7, 47%) were also commonly listed as having missing information. Additional pharmacovigilance activities were proposed for two thirds of the medicines (n = 10, 77%) where missing information was listed. Only one third of the reviewed medicines (n = 5, 33%) had specific proposals or protocols listed in the current Australian Public Assessment Reports to address missing information.

Conclusions: Our study identified important gaps in RMPs for commonly used biologic medicines at the post-market phase. Despite some medicines having an extensive market history, these safety concerns remain unaddressed. Regular monitoring and critical review of RMPs are recommended to prioritise post-market studies and address outstanding safety concerns.