Pharmacoepidemiology and Drug Safety最新文献

Purpose: Pharmacoepidemiologic studies on deprescribing are challenging to implement, yet little guidance exists on methods to avoid bias and minimum reporting for replicability and appraisal. We developed consensus recommendations for the methods and reporting of observational studies that aim to examine the effects of deprescribing.

Methods: We formed candidate recommendations based on our prior systematic review that methodologically appraised observational studies on deprescribing. We then conducted a two-round modified Delphi process with researchers working in deprescribing pharmacoepidemiology to refine, select, and reach consensus on recommendations for a checklist based on > 70% agreement of their importance. We termed this list the REMROSE-D (Reporting and Methodological Recommendations for Observational Studies estimating the Effects of Deprescribing medications) guidance.

Results: Twenty-three candidate recommendations were presented to the Delphi panel. The round 1 survey was completed by 55 participants, and 18 of the 23 candidate recommendations were selected for inclusion. Five candidate recommendations without consensus plus two additional items suggested by participants were included in a round 2 survey of 25 deprescribing researchers. Five of these seven items garnered consensus for inclusion, and two were excluded. The final REMROSE-D guidance contains 23 recommendations for the methods and reporting of observational research on deprescribing.

Conclusion: To ensure rigor and reproducibility in observational studies of the effects of deprescribing, the REMROSE-D guidance provides recommendations for important reporting and methods considerations, including time zero, precise definitions of deprescribing, addressing confounding by indication, and careful consideration of follow-up to avoid immortal time bias.

Background: Long-term antidepressant use may reduce the risk-benefit profile due to the increased likelihood of withdrawal symptoms and higher incidence of side effects. This epidemiological study investigates historical trends in long-term antidepressant use, which was defined as maintaining continuous antidepressant use for at least 365 days, allowing for gaps in dispensing of up to 60 days in the Australian community from 2014 to 2023.

Method: A retrospective analysis was conducted using a 10% sample of data from the Australian Pharmaceutical Benefits Scheme (PBS), including patients aged over 10 years who had been dispensed a PBS-listed antidepressant between January 2014 and December 2023.

Results: From 2014 to 2023, the prevalence of long-term antidepressant use increased from 66.1 to 84.6 per 1000 population. Age-stratified analysis showed that the 10-24 age group had the highest relative increase in long-term user prevalence (110%) and in the proportion of long-term users (35%). The average duration of the treatment episode increased by 25% across all ages, with the 10-24 group showing the largest rise (56%). The percentage of long-term users with apparent dose reductions showed minimal change over time.

Conclusions: The study highlights a growing trend in long-term antidepressant use across all age groups, particularly among those aged 10-24, warranting further investigation into the underlying factors. The extended treatment duration, coupled with limited medicine apparent dose reduction efforts, may suggest overprescription and underuse of deprescribing strategies. A more comprehensive mental health approach is needed, integrating effective deprescribing practices and emerging technological interventions.

Objectives: To compare age- and sex-specific trends of psychotropic prescribing between Danish and US 3-17-year-old youths.

Methods: A consecutive annual cross-sectional study of trends in psychotropic prescribing from 2010 to 2020. Data sources included the Danish National Prescription Registry data and, for the US, a 25% random sample of the IQVIA PharMetrics Plus for Academics database. Psychotropic prescribing (i.e., ADHD medications, antidepressants, and antipsychotics), measured as annual prevalence, was estimated for each therapeutic class, by age group and sex, separately by country. We used Joinpoint models to calculate the average annual percentage change (AAPC).

Results: ADHD medication prescribing decreased for 5-9 year-olds in both countries from 2010 to 2020, while prescribing among 10-17 year-olds was stable in the US and increased in Denmark, particularly among females (AAPC = 4.2% versus 1.4% among males). Antidepressant prescribing increased in older US youths, especially among 14-17 year-olds (AAPC = 6.5%), and females (AAPC = 7.2%). In Denmark, however, prescribing was low and decreased over time, especially among females (AAPC = -4.2%). Antipsychotic prescribing decreased in both countries for all age groups, with the largest decrease among males (Denmark: AAPC = -5.2% and US: AAPC = -6.1%).

Conclusion: Pediatric antipsychotic prescribing generally decreased, whereas ADHD medication and antidepressant prescribing presented opposing patterns in the two countries. ADHD medication prescribing increased among Danish females and adolescents, but was stable in the US. Antidepressant prescribing decreased in Denmark, particularly among females, which opposed the marked rise for this group in the US. Future cross-national studies should examine the rationale underpinning variation in antidepressant prescribing.

Background: Rapid innovation and new regulations increase the need for post-marketing surveillance of implantable devices. However, complex multi-level confounding related to patient-level and surgeon or hospital covariates hampers observational studies of risks and benefits. We conducted two simulation studies to compare the performance of Causal Forests (CF) versus Inverse Probability of Treatment Weighting (IPTW) to reduce confounding bias in the presence of strong surgeon impact on treatment allocation.

Methods: Two Monte Carlo simulation studies were carried out: (1) Parametric simulations with patients nested in clusters (ratio 10:1, 50:1, 100:1, 200:1, 500:1) and sample size n = 10 000 were conducted with patient and cluster level confounders; (2) Plasmode simulations generated from a cohort of 9981 patients admitted for pancreatectomy between 2015 and 2019 from the US PINC AT hospital research database. Different CF algorithms and IPTW were used to estimate binary treatment effects.

Results: Performance varied with the strength of cluster-level confounding. Under weak to moderate surgeon influence, CF and IPTW performed similarly. When confounding was strong (OR = 2.5), CF reduced bias compared with IPTW: in parametric simulations, relative bias averaged 11.2% for CF versus 19.9% for IPTW, with similar advantages observed in plasmode simulations.

Conclusions: CF shows promise as a method for estimating treatment effects in scenarios where cluster-level confounding strongly impacts treatment allocation. More research is needed to guide its use.

Purpose: Japanese traditional (Kampo) medicines containing ephedra are used to relieve symptoms of the common cold during pregnancy. The risks associated with perinatal outcomes, however, remain unclear. Thus, we evaluated the risk of adverse perinatal outcomes associated with the use of Kampo medicines containing ephedra during pregnancy using data from the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study).

Methods: Questionnaires were distributed to pregnant women who participated in the TMM BirThree Cohort Study at approximately weeks 12 and 26 of pregnancy. Adverse perinatal outcomes in women who used Kampo medicines containing ephedra or acetaminophen during pregnancy were assessed. Odds ratios (ORs) were estimated using weighted logistic regression analyses.

Results: Among 20 083 pregnant women, acetaminophen and Kampo medicines containing ephedra were used by 5.3% and 3.5% of women, respectively. The OR for caesarean section was 0.95 (95% confidence interval [CI], 0.75-1.20), for preterm birth (PTB) was0.99 (95% CI, 0.63-1.55), for low birth weight (LBW) was 1.04 (95% CI, 0.72-1.49), for small for gestational age (SGA) was 0.98 (95% CI, 0.58-1.65), and for low Apgar scores at 5 min was 0.85 (95% CI, 0.25-2.93) in the women who used Kampo medicines containing ephedra during pregnancy.

Conclusions: No statistically significant association was seen between the use of Kampo medicines containing ephedra during pregnancy and an increased risk of needing a caesarean section, PTB, LBW, SGA, or low Apgar scores. Although further research is needed, this study may assist in clinical decision-making.

Background: Inverse probability weighting (IPW) is a widely used method to estimate the causal effect of treatment from observational data. However, it can be unstable when extreme propensity score (PS) values lead to very large weights. Overlap weights (OW), which emphasize subjects in areas of covariate overlap, reduce the influence of extreme PS without excluding participants. While the OW method has shown strong performance in simulations with continuous outcomes, its utility in binary outcome settings-common in health research-has not been thoroughly evaluated.

Methods: We conducted simulation studies to evaluate the performance of OW in comparison to other PS weighting methods including IPW, trimmed IPW, and matching weights, in settings with extreme PS values and a binary outcome. Using simulated datasets with varying degrees of PS overlap and treatment prevalence, we assessed covariate balance and treatment effect estimation performance. The performance of the PS weighting methods was further illustrated through an application to data from a study on pancreatic ductal adenocarcinoma.

Results: In simulation studies, IPW's performance deteriorated markedly as the overlap in the covariate distribution decreased. In contrast, OW achieved exact covariate balance and consistently showed the highest efficiency among all methods evaluated. In the application to real-world data characterized by low treatment prevalence and substantial covariate imbalance, OW also outperformed the other methods in terms of both standard error and covariate balance.

Conclusion: These findings suggest superior performance of OW in terms of covariate balance and estimation efficiency in settings with extreme PS and a binary outcome.

Background: Despite testing of epidemiological methods in US Claims databases for signal detection, such data sources have not become a routine capability. The Self Controlled Case Series (SCCS) is one of the most promising methods for drug safety signal detection using Real World Data, and incorporating active comparators could potentially improve its performance by addressing confounding by indication.

Objectives: This study aims to evaluate the performance of the SCCS with and without active comparators for signal detection using US Merative MarketScan Commercial Claims and Medicare databases.

Methods: We applied the SCCS to macrolide and fluoroquinolone antibiotics, using amoxicillin and cefalexin as active comparators. In total, 7 drugs and 30 outcomes from all organ classes were selected. We developed a reference set of 104 positive controls and 58 negative controls, using a taxonomy framework to ensure the selected drug outcome pairs are theoretically well suited to the SCCS design. A two-year observation period with a 30-day risk window after each dispensing was used. Diagnostic performance was measured using sensitivity and specificity with respect to the product labels.

Results: The SCCS without active comparators achieved sensitivities of 0.73 and 0.72 and specificities of 0.68 and 0.62 in commercial and Medicare claims, respectively, for pairs with sufficient power. Active comparators increased specificity up to 0.84 and 0.86, respectively, in Commercial Claims and Medicare but decreased sensitivity to 0.45 and 0.36.

Conclusions: MarketScan databases are potentially suitable for drug safety signal detection due to their large size and information contained. Using a carefully designed reference set of drug-outcome pairs well suited to the study design, the SCCS, while imperfect, performed comparably to optimal settings identified in previously published studies. Active comparators did not enhance overall performance but showed improved specificity by better controlling confounding by indication at the cost of reduced sensitivity.

Purpose: Self-medication carries the potential for significant adverse events when practiced irresponsibly. The indiscriminate use of medicines notably intensified during the COVID-19 pandemic. This study aimed to investigate the epidemiological profile of exogenous intoxications due to self-medication among Brazilians from 2014 to 2023.

Methods: This was a cross-sectional, descriptive, and exploratory study utilizing secondary data from the Brazilian Ministry of Health's Notifiable Diseases Information System. Confirmed cases of self-medication intoxication reported between 2014 and 2023 were included. Descriptive analysis, incidence and lethality rate calculations, chi-squared tests (p ≤ 0.05), and Multiple Correspondence Analysis (MCA) were performed to explore potential associations between sociodemographic and clinical variables.

Results: A total of 23 859 cases were analyzed. The study observed a predominance of adults (20-59 years), women (70.8%), and individuals self-identifying as White or Brown (mixed-race). Most cases resulted from an acute-single exposure to the medication and resolved with complete recovery without sequelae. There was a national increase in incidence, particularly in 2022 and 2023, and significant variations among Brazilian Federative Units. The MCA identified associations between advanced age and the type of exposure (repeated or chronic) and the severity of outcomes. It also revealed changes in the sociodemographic profile of self-medication intoxications during the COVID-19 pandemic.

Conclusions: These findings underscore the pandemic's impact on self-medication patterns and intoxication notifications. The study highlights the need for public policies focused on health education, appropriate medicine use, and strengthening the culture of reporting in Brazil.

Purpose: Combined oral contraceptives (COCs) are contraindicated in migraine with aura due to stroke risk, and some hormone therapy for menopause guidelines recommend caution in this population. However, this guidance is informed by sparse or older evidence reflective of higher doses than typically prescribed today. This study aimed to describe modern-day utilization of COCs and hormone therapy among female individuals with migraine with aura from 2000 to 2024.

Methods: Using United Kingdom medical record data, this study evaluated the use of COCs and progestogen-only pills (POPs) among reproductive-age individuals and hormone therapy among post-reproductive age individuals, before and after migraine with aura diagnosis. Post-diagnosis medication utilization was described relative to baseline characteristics and pre-diagnosis use of each medication, overall and longitudinally.

Results: Among 142 867 individuals of reproductive age, 84 374 (59%) used oral contraceptives on or after migraine with aura diagnosis, predominantly POPs (n = 75 823, 53% of those with any oral contraceptive) over COCs (n = 21 968, 15%). Most oral contraceptive users in the year pre-diagnosis used COCs (n = 36 909/56760, 66%). Among 46 913 individuals of post-reproductive age, 20 990 (45%) had a prescription for hormone therapy after migraine with aura diagnosis, with transdermal formulations used increasingly over calendar time.

Conclusions: Utilization of COCs declined but did not fully cease after migraine with aura diagnosis. Post-diagnosis utilization of hormone therapy for menopause was common. Given this utilization among individuals with migraine with aura, high-quality evidence quantifying the risk of stroke associated with modern-day use of these medications in this population is needed to inform patient and provider decision making.

Purpose: Pharmacotherapy during pregnancy should be approached with caution due to the potential risk of adverse effects, including birth defects, in the fetus. Appropriate post-marketing surveillance and perinatal pharmacoepidemiology are essential to ensure the safety of pharmacotherapy during pregnancy. However, due to limited research infrastructure in pharmacoepidemiology, collecting reliable data on drug safety in pregnant women and infants remains a challenge in Japan. Thus, we examined the suitability (fitness for purpose) of Japanese medical databases for perinatal studies to establish infrastructure in this field.

Methods: We assessed seven available databases in Japan: the DeSC database, EBM provider, Japanese Adverse Drug Event Report database, JMDC claims database, MDV analyzer, the National Database of Health Insurance Claims, and Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study). To assess the quality of databases for maternal studies, we evaluated the content of each mother-infant linkable database based on the core data elements recommended for perinatal pharmacoepidemiology.

Results: Three of the databases were found to be mother-infant linkable: the DeSC database, JMDC claims database, and the TMM BirThree Cohort Study. The coverage of core data elements in perinatal pharmacoepidemiology was 73.5% in the DeSC and JMDC claims databases and 92.9% in the TMM BirThree Cohort Study.

Conclusion: Some representative medical databases in Japan are well suited for use in perinatal pharmacoepidemiologic research on infant outcomes.