Pharmacoepidemiology and Drug Safety最新文献

Introduction: The COVID-19 pandemic caused unprecedented disruptions in healthcare delivery, and changes in medication utilization patterns. While previous studies examined specific therapeutic classes or populations, there is limited longitudinal evidence on medication trends among young adults throughout and beyond the pandemic.

Aim: To analyze trends in medication dispensation before, during, and after the COVID-19 pandemic among young adults.

Methods: We conducted a population-based, retrospective cohort study including active-duty Israeli Defense Forces personnel between January 2017 and August 2023. Monthly dispensing rates per 1000 persons were analyzed using an interrupted time series (ITS) design, implemented via generalized linear models with log link and population offsets. Models included linear time trends, month fixed effects to account for seasonality, and negative binomial fallback for overdispersion. Pre-pandemic data (January 2017-March 2020) were used to estimate baseline trends, from which counterfactual predictions were generated for March 2020-August 2022. Goodness-of-fit was evaluated with RMSE and MAPE.

Results: Pre-pandemic trends varied across therapeutic groups. Adrenergic inhalants (IRR 1.008, 95% CI 1.004-1.011, p = 0.0001), antidiarrheals (IRR 1.005, 95% CI 1.001-1.008, p = 0.004), and ADHD medications (IRR 1.024, 95% CI 1.020-1.027, p < 0.001) exhibited significant upward slopes, whereas antibacterials, antidepressants and hormonal contraceptives showed no significant baseline trend. Seasonality was significant for all groups (p < 0.001). During the pandemic, cumulative differences revealed excesses for adrenergic inhalants (+93.98 per 1000), antidepressants (+87.03), and hormonal contraceptives (+679.21), alongside deficits for antibacterials (-201.99), antidiarrheals (-112.89), and ADHD medications (-294.69).

Conclusions: Medication usage patterns can be classified into three classes: medications affected by the pandemic due to the inciting pathogen, disease symptoms, or pandemic social disruption; medications unaffected by the pandemic, affected by global disease trends; and medications with a trend change whose relation to the pandemic is unclear. These findings offer a novel framework for anticipating and managing medication needs in future pandemics.

Purpose: Evidence on head-to-head comparison between direct oral anticoagulants (DOACs) is lacking, and the reasons for choosing one type of DOAC and switching from one DOAC to another are scarce. This study investigated the use of DOACs in an unselected population in Northern Italy during a recent period.

Methods: Using the health administrative database of the Lombardy region, subjects aged 45 years and older who started DOAC therapy between 2019 and 2022 were included in the analysis. Logistic regression analysis was used to evaluate predictors associated with DOAC prescription, and results were presented as ORs with 95% CI. DOAC switching was assessed by estimating the prevalence and cumulative incidence according to the first prescribed DOAC.

Results: Overall, 159 993 new users for DOAC were identified. Apixaban users increased from 29.0% to 34.3%, whereas dabigatran users decreased from 20.7% to 11.5% over time. Across all pair-wise comparisons, older age and female sex were predictors for edoxaban prescription. Comorbidities were mainly associated with the use of apixaban; however, dabigatran was preferred in patients with a history of ischemic heart disease or myocardial infarction and rivaroxaban in those with peripheral artery disease. Both apixaban and edoxaban were preferentially prescribed to patients with a history of bleeding. The switching rate of DOACs was 5.6% with apixaban as the most preferred drug as a second choice. Dabigatran was mainly chosen as a second DOAC after a vascular ischaemic event.

Conclusion: Given the lack of evidence on factors influencing clinician behavior in the use of DOACs, our findings provide insight into this topic in a real-world setting. As the use of these agents increases, further evidence is needed to better explore this issue. Our data could contribute to the development of recommendations in clinical practice.

Background: The risk of congenital anomalies following first-trimester medication exposure is an important indicator of medication safety during pregnancy. Retrospective cohort studies using routinely collected data are commonly used to assess this risk, yet methodological inconsistencies-such as how cohorts, exposures, timings and outcomes are defined-can compromise reproducibility and validity. This scoping review examined the methodologies used in retrospective cohort studies assessing the association between first-trimester prenatal medication exposure and congenital anomalies.

Methods: Medline, PsycInfo, Embase, CINAHL and Global Health were searched for retrospective cohort studies published in English between 2014 and 2024 examining the association between first-trimester medication exposure and congenital anomalies. Screening and data extraction were performed by two reviewers, using Covidence.

Results: A total of 156 studies were included. Most were conducted in Europe (56%) using database or registry studies (87%). Common exclusions included stillbirths (58%), multiple pregnancies (41%) and exposure to teratogenic medications (39%). Exposure was typically defined as a minimum of one prescription dispensed during the first trimester (79%); however, the definition of pregnancy start varied across studies: 29% used the date of the last menstrual period, while 42% used the estimated day of conception. The end of the first trimester was defined as Week 12 (16%), Week 13 (30%) or Week 14 (15%). The types of included anomalies differed, with chromosomal anomalies (48%), minor anomalies (14.5%) and genetic anomalies (13.5%) commonly excluded. Comparison groups included untreated individuals without the condition (65%), untreated individuals with the condition (22%) or those receiving alternative treatments (23%).

Conclusion: Substantial methodological variation exists in studies examining first-trimester medication exposure and congenital anomalies. This variation may arise both from inherent differences in data sources and from discretionary methodological decisions made by investigators. Standardised definitions would be beneficial to improve consistency, reliability and interpretability of research in this field.

Background: Medications associated with acute liver injury (ALI) are primarily identified by case reports. High-throughput screening of real-world data could be leveraged to detect hepatotoxicity signals.

Objective: To apply tree-based scan statistics in real-world data to identify drugs associated with hospitalization for severe ALI among patients without liver/biliary disease and with chronic liver disease (CLD).

Methods: We implemented a self-controlled case-crossover design in Veterans Health Administration data (2000-2023) among patients hospitalized for laboratory-confirmed severe ALI. We identified all newly dispensed drugs within 365 days prior to their hospitalization and used conditional Bernoulli tree-based scan statistics to identify potential associations (p < 0.3). We performed analyses separately in patients without liver/biliary disease and with CLD.

Results: Among 12 860 patients without liver/biliary disease and 17 512 with CLD hospitalized for severe ALI, we evaluated associations with 450 and 543 drugs, respectively. Drugs associated with severe ALI among patients without liver/biliary disease included: acid-suppressives (ranitidine [p < 0.001], omeprazole [p = 0.004]), antiemetics (ondansetron [p < 0.001], promethazine [p = 0.06]), antibiotics (amoxicillin/clavulanate [p = 0.008], ciprofloxacin [p = 0.02], mupirocin [p = 0.032], ethambutol [p = 0.275]), anticoagulants (heparin [p = 0.015]), and chemotherapy (pazopanib [p = 0.275]). Drugs associated with severe ALI among CLD patients were: diuretics (spironolactone, furosemide [both p < 0.001]), antiemetics (ondansetron, metoclopramide, promethazine [all p < 0.001]), appetite stimulants (p < 0.001), analgesics (morphine, oxycodone, fentanyl [all p < 0.001]), chemotherapy (sorafenib [p < 0.001]), antibiotics (ciprofloxacin [p = 0.011], metronidazole [p = 0.020]), antipsychotics (prochlorperazine [p = 0.105]), vitamins (p = 0.134), acid-suppressives (omeprazole [p = 0.164]), and gastrointestinal/liver disease treatments (lactulose, senna, docusate, silicones, antiflatulents [all p < 0.001]; sucralfate [p = 0.005], albumin [p = 0.228]).

Conclusions: High-throughput screening using tree-based scan statistics detected potentially hepatotoxic drugs for investigation in future pharmacoepidemiology studies.

Background: Mounting evidence indicates that Type 2 diabetes mellitus (T2DM) is a public health challenge globally, and its occurrence is anticipated to surge in the forthcoming years. Dipeptidyl peptidase-4 (DPP-4) serves as a target for its treatment, with its inhibitors effectively preserving the levels of glucose-dependent insulinotropic peptide and glucagon-like peptide 1(GLP-1). This review presents an overview of the therapeutic possibilities of six frequently employed DPP-4 inhibitors (DPP-4is) (Sitagliptin, saxagliptin, vildagliptin, linagliptin, alogliptin and teneligliptin) in managing T2DM, focussing on their characteristics, mechanism of action, advantages and side effects in comparison with alternative oral antidiabetic drugs as well as the possibility of using in silico method in advancing its timely and cost-effective production.

Methods: A literature search was conducted using the major search engines such as PubMed/Medline, Scopus, and Google Scholar, etc. employing terms like 'Type 2 diabetes mellitus (T2DM), DPP-4 inhibitors, and Dipeptidyl peptidase-4', etc. to identify relevant studies.

Results: Our findings indicate that DPP-4is stimulate secretion of insulin and suppress secretion of glucagon by elevating endogenous GLP-1 concentrations without an intrinsic hypoglycaemia risk. Although these agents share a common mechanism of action, their considerable structural heterogeneity may lead to distinct pharmacological characteristics. Literature shows that DPP-4is have a promising safety profile in comparison with other oral antidiabetic medications, however, certain safety aspects require additional exploration. Different DPP-4is have demonstrated comparable safety and tolerability, whether used alone or in combination with other antidiabetic medications. Besides, it has been shown that in silico method could be employed in development of DPP-4is. Further research is necessary to ascertain whether differences among DPP-4 inhibitors might influence the occurrence of specific adverse effects.

Conclusion: DPP-4 inhibitors remain effective and well-tolerated options for managing T2DM.

Background: The US Food and Drug Administration proposed a five-level disease severity categorization for baseline COVID-19 (asymptomatic, mild, moderate, severe, critical).

Aims: We conducted a pilot study aimed to validate the performance of the ICD-10-CM diagnosis code for COVID-19 (U07.1) and operational definitions (code-based algorithms) for each disease severity category in Medicare administrative data.

Materials & methods: We sampled 250 community-dwelling beneficiaries aged ≥ 18 years with a U07.1 code on an inpatient hospital or ambulatory claim between April 1, 2020 and June 18, 2022. We used stratified sampling based on care setting and COVID-19 treatment status and adjusted results using sampling weights. Using medical records as the reference standard, we calculated positive predictive values (PPV) and 95% confidence intervals (CI). We conducted prespecified secondary analyses to improve algorithm performance by using refined disease definitions.

Results: We received medical records for 190 (77%) beneficiaries. Of these, 171 had a positive SARS-CoV-2 test result. The PPV of the COVID-19 diagnosis code was 89% (CI: 83%-93%) overall, 88% (CI: 80%-93%) in the ambulatory setting, and 93% (CI: 82%-97%) in the inpatient setting. The operational definition for disease severity varied in performance by severity level and measurement strategy. The best performance was: PPV for asymptomatic and mild combined 69% (CI: 59%-77%), PPV for moderate 58% (CI: 34%-78%); PPV for severe 42% (CI: 27%-59%); and PPV for critical 85% (CI: 57%-96%).

Discussion: The code, U07.1, reliably identified beneficiaries with COVID-19 in both ambulatory and inpatient settings. The operational definition to classify COVID-19 disease severity notably improved performance when we implemented selected refinements.

Conclusion: Researchers should consider the moderate performance of the proposed operational definitions when using administrative claims data to assess COVID-19 disease severity.

Purpose: Drug-related admissions (DRAs) remain highly prevalent and are linked with increased morbidity and mortality. Rapid and accurate identification is key to both their acute management and secondary prevention. To this end, two clinical decision rules (CDRs) were recently developed to identify the causal adverse drug event (ADE-CDR) or the underlying adverse drug reaction (ADR-CDR). The aim of this study was to assess the diagnostic accuracy of both CDRs in a new patient cohort.

Methods: A prospective, cross-sectional study was conducted at the emergency department (ED) of the University Hospitals Leuven in Belgium. Adult patients were included if admitted to the hospital via the ED. DRA was adjudicated by team consensus and compared to both ADE-CDR and ADR-CDR. Diagnostic accuracy was determined, and multivariable logistic regression was used to explore risk factors for DRAs.

Results: From 1 October 2018 to 26 September 2019, 438 patients were included, 58 (13.2%) of whom incurred a DRA. ADE-CDR had a sensitivity of 89.7% and a specificity of 22.4%. The sensitivity and specificity of ADR-CDR were 46.6% and 60.8%, respectively. Two risk factors were found for DRA: the presence of ≥ 1 comorbidity (odds ratio (OR) 4.71, 95% confidence interval (CI): 1.42-15.49) and ambulance transport (OR 2.16, 95% CI: 1.21-3.82).

Conclusion: ADE-CDR showed a high sensitivity. In terms of specificity, both CDRs were unable to rule in DRAs in our setting. Conversely, the ADE-CDR showcased the potential to rule out DRAs.

Purpose: This study aimed to assess the risk of Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS/TEN) among patients treated with immune checkpoint inhibitors (ICIs), compared to those receiving molecularly targeted therapies or conventional chemotherapy, using real-world data.

Methods: We conducted a nationwide study involving all patients treated with antineoplastic agents in Denmark from May 2018 to December 2024, identified through the Danish National Hospital Medication Registry. SJS/TEN cases were identified within 3 months of each administration using the International Classification of Diseases, 10th Revision codes L51.1 and L51.2, as recorded in the Danish National Patient Register. Incidence rates of SJS/TEN were calculated per 10 000 patients treated, and incidence rate ratios (IRRs) were estimated to compare treatment modalities.

Results: Among 91 424 patients treated with antineoplastic agents, 19 developed SJS/TEN. The incidence rates per 10 000 patients treated were 6.89 for ICIs, 1.79 for molecularly targeted therapies, and 1.51 for conventional chemotherapy. Patients receiving ICIs had a higher risk of developing SJS/TEN compared with those receiving molecularly targeted therapies (IRR 3.84, 95% CI 1.39-10.60, p = 0.009) or conventional chemotherapy (IRR 4.57, 95% CI 1.52-11.57, p = 0.001).

Conclusion: While the risk of SJS/TEN is higher among patients treated with ICIs compared to those receiving other types of antineoplastic agents, the overall incidence in the real-world setting remains low.