Pharmacoepidemiology and Drug Safety最新文献

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.

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.