Drug Safety最新文献

Introduction: Medication errors continue to cause inpatient harm in children and can be difficult to both identify and classify. Medication error studies often focus on assessing potential harm and there is little published data on actual harm from medication errors in children.

Objective: Our aim was to use multidisciplinary panels to identify and describe the actual harm resulting from prescribing and administration medication errors occurring at a major paediatric hospital.

Methods: We reviewed medication error data collected from retrospective medication record reviews to identify prescribing errors (26,369 orders, 19,692 errors and 3782 patients) and prospective direct observations (5137 dose administrations, 3663 errors and 1530 patients) to identify administration errors. Errors with the potential to cause serious harm and with evidence that the error reached the patient formed the dataset for our study. Case studies (n = 566) describing the prescribing and administration errors and a brief clinical summary were reviewed by multidisciplinary panels to determine whether there was evidence in patients' records of actual harm and to rate the severity of the harm identified.

Results: Actual harm was identified in 89 case studies and rated as minor in 43% (n = 38), moderate in 48% (n = 43) and serious in 9% (n = 8). There were no cases of harm rated as severe resulting in death. Antibacterials were the most common medications in cases with harm (n = 38/89 cases), and dosing errors (n = 32/89) the most common error type associated with harm. Younger patients had a significantly (t = 2.4, df = 198, p = 0.017) greater risk of actual harm from medication errors, and children aged under 12 months formed a higher proportion of those with actual harm (χ² (1, N = 566) = 10.5, p = 0.001). The most frequent type of administration errors leading to harm were wrong infusion rates of intravenous antibiotics (19/67 cases); 12 of these instances occurred in children under 12 months. Administration errors were more likely to result in actual harm (1.83%; 67 /3663 errors) compared with prescribing errors (0.21%; 42/19,692).

Conclusions: We found higher rates of actual harm associated with medication errors in younger patients, wrong dose prescribing errors and intravenous antibiotic administration errors. These important findings provide opportunities for developing tailored interventions targeting identified high-risk areas to enable the successful reduction of preventable harms in paediatric patients.

Background and objective: Selecting an index date (also called time zero or baseline) can be challenging for External Comparator (EC) studies when comparing against untreated patients. Existing literature addresses methods for defining an index date for untreated patients in observational studies generally, but not for EC studies specifically, which are likely to benefit from customized approaches.

Methods: A simulation study was performed to assess different index date assignments and analytical approaches in terms of bias and other performance characteristics: The first approach took the time from a major clinical event (say, diagnosis date) to treatment start as observed in the treated cohort and randomly assigned these times to the untreated cohort to derive the index dates. This approach was applied without and with the condition that the emulated index dates in the untreated cohort needed to be before the observed event times (index date emulation [IDE] and modified index date emulation approach [mIDE]). The second approach was to start the follow-up period at the diagnosis date (early index date approach [EID]) and to perform an analysis according to a time-dependent Cox model (or its generalization, e.g., a Marginal Structural Cox Model). This model was applied both in a traditional but also in a modified manner (modified early index date approach, mEID), where the modified model coded the treatment cohorts before the true (treated patients) and emulated (untreated patients, using IDE) treatment start dates to belong to a third treatment category. This allowed the treatment comparison of interest to be restricted to the time after the true and emulated treatment start dates.

Results: The IDE and mEID approaches were shown to be unbiased with identical performance, while mIDE and EID exhibited significant bias.

Conclusions: We showed that our EC analysis approach based on emulated index dates for untreated patients constitutes a valid concept, which may be advantageous for many external comparator studies.

Background: In Australia, surveillance of adverse events following immunisation is primarily conducted by states and territories, with each jurisdiction only able to view and analyse reports originating from their own population. Distributed data models (aka federated data models) are a form of decentralised collaboration, with each site maintaining ownership of its data from end-to-end including data collection, storage and analysis. The primary benefit of this model is that it maintains independence and autonomy while enabling interdependence, collaboration and scalability.

Objective: We aimed to investigate statistical methods for a multi-jurisdictional collaboration when conducting a rigorous assessment of rare adverse events following immunisation at a national level.

Methods: Victoria and Western Australia have independently established routine data linkage for vaccine safety surveillance. A data collaboration model is proposed, whereby each jurisdiction can generate de-identified population-level data for adverse events following immunisation, using agreed case definitions and analytical methods. To demonstrate its utility, Victoria and Western Australia combined data from a self-controlled case series via a meta-analysis approach using aggregate data and a pooled approach using individual-level data to investigate the association between coronavirus disease 2019 vaccines and Guillain-Barré syndrome.

Results: There were 519 and 176 new Guillain-Barré syndrome International Classification of Diseases, Tenth Revision, Australian Modification coded admissions in Victoria and Western Australia, respectively, between 01/01/2020 and 31/12/2023. Combining data using a fixed-effect meta-analysis method (relative incidence: 2.64, 95% confidence interval 1.90, 3.66) and a pooled method (relative incidence: 2.45, 95% confidence interval 1.76, 3.41) confirmed the known increased incidence in the 42 days following a coronavirus disease 2019 Vaxzevria^® vaccination. Both methods resulted in a decreased standard error when compared with either state alone.

Conclusions: This project represents an ongoing successful collaboration between two Australian jurisdictions using data linkage to investigate rare adverse events following immunisation and inform accurate benefit-risk analyses. The decision to use meta-analysis and pooled analysis methods should be considered on a case-by-case basis and may depend on data-sharing agreements, the ease of pooling potentially discordant data variables and underlying population characteristics.

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.

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.

Post-authorization studies (PAS) are often mandated by regulatory authorities as a condition of marketing authorization of pharmaceutical products. This article explores specific regulations and trends in China, Japan, and South Korea, highlighting the scientific and operational limitations that such PAS pose to the stakeholders in these regions including significant variations in regulatory requirements. Pharmacovigilance guidelines and publications on regional regulatory trends were reviewed. Active surveillance studies are widely adopted to fulfill post-authorization requirements in East Asia countries. These are primary data collection studies, i.e., traditional site-based studies that monitor the frequency of all adverse events (and clinical outcomes when requested) of the newly approved pharmaceutical product during a predefined treatment period. Such studies generally present limitations regarding the product's safety profile characterization, including the absence of a comparator group, selection bias, limited sample size, and considerable resources needed to conduct the studies. These limitations explain the trend toward hypothesis testing studies, conducted with secondary data (e.g., large electronic database studies) as preferred over traditional active surveillance studies. Harmonizing regulatory approaches and enhancing access to comprehensive data sources are critical for generating fit-for-purpose evidence to support regulatory decision making in these regions. Therefore, we propose a decision tool to assist with the planning of PAS in China, Japan, and South Korea. This article is endorsed by the International Society for Pharmacoepidemiology (ISPE).

Introduction: Under Section 564 of the Federal Food, Drug and Cosmetic Act, the United States (US) Food and Drug Administration (FDA) may, pursuant to a declaration by the US Department of Health and Human Services Secretary, based on one of four types of determinations, authorize an unapproved product or unapproved uses of an approved product for emergency use. Although sponsors are not prohibited from promoting products with Emergency Use Authorizations (EUAs), little is known about how they promote these products.

Objectives: The aim of this study was to investigate how EUAs are being described in promotional materials disseminated to health care providers (HCPs) and consumer audiences.

Methods: A content analysis was conducted on promotional materials for drugs authorized under an EUA that were submitted to the FDA between April 2020 and April 2023. Each material was coded for the presence or absence and location of certain words, phrases, or resources relating to EUAs and product risk information. Statistical analyses include descriptive statistics and bivariate analyses comparing materials created for consumer and HCP audiences. Readability statistics were also conducted for consumer materials.

Results: The sample included 423 promotional materials. Most materials included risk information; however, few included a formal definition of an EUA. Materials for HCPs were more likely to contain links to fact sheets and other information and resources related to EUAs. The reading level of consumer materials was very difficult (requiring graduate-level education).

Conclusion: Although most of the materials contained risk and benefit information in promotional materials about EUAs, improvements could be made through the inclusion of a specific definition of "EUA" and more prominent information about limitations of use in consumer materials. Readability could also be improved for consumer materials by applying plain language principles.

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.