Prevalence of drug-drug interaction in atrial fibrillation patients based on a large claims data

Negative effects of rivaroxaban observed in a patient with multiple common risks triggered by a bicycle accident

The negative effects of anticoagulants are well-known in patients with renal impairment, drug-drug interaction, lower physical conditions, and multiple comorbidities. We highlight that even in patients with controllable multiple risks for rivaroxaban use, add-on inevitable risks will lead to negative effects greater than those expected.

Real-world data: a brief review of the methods, applications, challenges and opportunities

Background

The increased adoption of the internet, social media, wearable devices, e-health services, and other technology-driven services in medicine and healthcare has led to the rapid generation of various types of digital data, providing a valuable data source beyond the confines of traditional clinical trials, epidemiological studies, and lab-based experiments.

Methods

We provide a brief overview on the type and sources of real-world data and the common models and approaches to utilize and analyze real-world data. We discuss the challenges and opportunities of using real-world data for evidence-based decision making This review does not aim to be comprehensive or cover all aspects of the intriguing topic on RWD (from both the research and practical perspectives) but serves as a primer and provides useful sources for readers who interested in this topic.

Results and Conclusions

Real-world hold great potential for generating real-world evidence for designing and conducting confirmatory trials and answering questions that may not be addressed otherwise. The voluminosity and complexity of real-world data also call for development of more appropriate, sophisticated, and innovative data processing and analysis techniques while maintaining scientific rigor in research findings, and attentions to data ethics to harness the power of real-world data.

Quantitative Prediction of Adverse Event Probability Due to Pharmacokinetic Interactions

INTRODUCTION

Iatrogeny due to drug-drug interactions is insufficiently documented, due to the high number of possible combinations.

OBJECTIVE

This study aimed to design a simple but general method to predict the variation of adverse events (AE) frequency due to a pharmacokinetic or pharmacodynamic interaction.

METHODS

Three prediction models were designed using a logistic probability density function. Each prediction model was based on three components: the AE odds ratio of each drug in the combination, and the area under the curve ratio (Rauc) of the pharmacokinetic interaction, if any. Pharmacodynamic interaction was assumed to be additive on logit scale. Rauc was predicted using a well-validated mechanistic static model, freely available online. No combination study is required. The method was evaluated against a wide range of AEs (28 High Level Terms) and 211 drug combinations (involving 43 victim drugs and 55 perpetrators), by comparing the observed and predicted frequencies. The observed odds ratios were estimated with a disproportionality analysis from the FDA Adverse Event Reporting System, using an approach that minimizes biases.

RESULTS

With the best model, the rate of prediction considered as correct (within 50-200% of the observed value) was 72%, and the bias was negligible (-5%). The AE odds ratio due to pharmacokinetic and pharmacodynamic interactions was equally well predicted.

CONCLUSIONS

A simple workflow to implement the method in practice is proposed. This method may help to foresee and to anticipate the harmful consequences associated with drug-drug interactions, at virtually no experimental cost, when the odds ratio of an AE is known for each drug alone and the AUC ratio is known or predicted by a suitable model.

Drug-drug interactions in atrial fibrillation patients receiving direct oral anticoagulants

Polypharmacy is common in patients with atrial fibrillation (AF), making these patients vulnerable to the occurrence of potential drug-drug interactions (DDIs). We assessed the risk of ischemic stroke and major bleeding in the context of concomitant treatment with potential DDIs in patients with AF prescribed direct oral anticoagulants (DOACs). Using the common data model (CDM) based on an electronic health record (EHR) database, we included new users of DOACs from among patients treated for AF between January 2014 and December 2017 (n = 1938). The median age was 72 years, and 61.8% of the patients were males, with 28.2% of the patients having a CHA₂DS₂-VASc score in category 0–1, 49.4% in category 2–3, and 22.4% in category ≥ 4. The CHA₂DS₂-VASc score was significantly associated with ischemic stroke occurrence and hospitalization for major bleeding. Multiple logistic regression analysis showed that increased risk of ischemic stroke and hospitalization for major bleeding was associated with the number of DDIs regardless of comorbidities: ≥ 2 DDIs was associated with ischemic stroke (OR = 18.68; 95% CI, 6.22–55.27, P < 0.001) and hospitalization for major bleeding (OR = 5.01; 95% CI, 1.11–16.62, P < 0.001). DDIs can cause reduced antithrombotic efficacy or increased risk of bleeding in AF patients prescribed DOACs.

[Potential Drug-Drug Interactions among Three or More Drugs: A Retrospective Multi-center Study in Pharmacies in the Kojima Region, Okayama]

Drug-drug interactions (DDIs) are responsible for an increase in the incidence of adverse drug reactions. Although CYP is known to be involved in metabolic processes, the DDIs among three or more drugs that involve the same CYP molecular species have not been fully investigated. In this study, we retrospectively examined the relationship between the number of drugs and potential DDIs in metabolic processes involving CYPs in patients who picked up their prescribed drugs at 11 pharmacies in the Kojima Branch of the Okayama Pharmaceutical Association. We found that 66.5% of the 924 patients had potential DDIs; more than half of the patients who took six or more drugs had potential DDIs among three or more drugs. The mean number of CYP3A4-related drugs involved in potential DDIs was 3.52±1.56 in patients who took seven drugs, suggesting the need for careful monitoring of specific symptoms and blood test results for the early detection of adverse drug reactions caused by DDIs among three or more drugs.

[Development and Application for Drug-safety and Efficacy Using a Large Claims Data]

Recent years, evidences for medical safety and efficacy are accelerated-developing using medical big data. Medical big data were adequate for analyzing 1) rare events that difficult for finding in each hospital, 2) for comparison of bench marks obtained routine work between average data in large number of hospitals and specific hospital data and 3) prescription surveys etc. As so far, these analyses using medical big data were conducted by academia and/or researcher. However, in these days, evidences using medical big data were focused on hospital pharmacists little by little. In this review, we show 3 researches using large claims data such as 1) risk factors assessing for failed low-density lipoprotein level achievement in members of the working-age population, 2) prevalence of drug-drug interaction in atrial fibrillation patients and 3) assessment of "look-alike" packaging designs related to medication errors using information technology and large claims data. Medical big data such as large claims data analysis is useful and suitable for building evidences according to medical staffs-needs.

Predictive factors associated with bleeding in atrial fibrillation patients treated with anti-coagulant drugs using a large claims database

Objective

To identify risk factors for bleeding in atrial fibrillation (AF) patients treated with anti-coagulants such as warfarin, apixaban, edoxaban, dabigatran, rivaroxaban using a large claims database.

Methods

A claims database for 8926 AF patients from 2004 to 2016 was obtained from JMDC. Inc. We performed a retrospective cohort study in 2796 Japanese AF patients with 4-month screening and 12-month observation periods. Polypharmacy was defined as prescription of over six drugs. Logistic regression analysis was conducted after stratification based on the presence and absence of cerebrovascular diseases to detect the predictive factors for bleeding.

Results

Polypharmacy was observed in 815 of 2796 (29.1%) patients. A total of 371 AF patients (13.3%) experienced bleeding in the 12-month observation period. Bleeding risk assessment using multiple logistic regression analysis revealed that the odds ratio for the number of co-administered drugs in the elderly (age for ≥60, ≤74) was not significant in those without and with cerebrovascular diseases (1.05 [0.99–1.12], N.S. and 1.10 [0.96–1.27], N.S.). In contrast, in the young (age for <60), the number of co-administered drugs was a significant predictive factor in those without and with cerebrovascular diseases (1.09 [1.03–1.16], p = 0.0054 and 1.20 [1.05–1.36], p = 0.0059). Other observed predictors were”history of bleeding” in young and elderly, but “polypharmacy” and “start from warfarin” were observed in only young.

Conclusion

We determined the bleeding risk in the clinical setting using a large claims database. Physicians and pharmacists need to monitor patients for the initial bleeding signs, particularly in those with these predictive risk factors.

Association of the ward pharmacy service with active implementation of therapeutic drug monitoring for vancomycin and teicoplanin-an epidemiological surveillance study using Japanese large health insurance claims database

Background

Ward pharmacists are required for the active implementation of therapeutic drug monitoring (TDM). This epidemiological study verified whether Japanese ward pharmacists contribute to improving the TDM implementation proportions of anti-methicillin-resistant Staphylococcus aureus (MRSA) agents using the large health insurance claims database.

Methods

The patients who received intravenous anti-MRSA agents from April 2012 to March 2017 were enrolled. We defined ward pharmacy service as the “drug management and guidance fee” and/or “inpatient pharmaceutical services premium”. In addition, implementation of TDM was identified by “the specific drug treatment management fee”. We compared the proportions of TDM implementation for vancomycin (VCM), teicoplanin (TEIC), and arbekacin (ABK) in the ward and non-ward pharmacy service groups. To avoid confounding, the propensity score method was employed. Moreover, the clinical variables affecting TDM implementation in each anti-MRSA agent were analyzed by using a multiple logistic regression model.

Results

The following number of patients were included in the study: VCM (n = 2138), TEIC (n = 596), and ABK (n = 142). After propensity score matching, the proportions of TDM implementation for VCM and TEIC were higher in the ward pharmacy service group than in the non-ward pharmacy service group (VCM: 69.2% vs 60.3%, TEIC: 51.4% vs 34.7%), while no significant difference was observed for ABK (21.2% vs 23.1%). As independent clinical variables affecting TDM implementation for VCM and TEIC, several clinical variables, including ward pharmacy services, were extracted. In contrast, no clinical variables were extracted for ABK.

Conclusions

We found that the ward pharmacy service is associated with the active implementation of TDM for anti-MRSA agents, such as VCM and TEIC.

Comparison of interactions between warfarin and cephalosporins with and without the N-methyl-thio-tetrazole side chain

Cephalosporins with an N-methyl-thio-tetrazole (NMTT) side chain interact with warfarin by reducing the production of blood clotting factors. However, cephalosporins without the NMTT side chain also enhance the effects of warfarin. Thus, we aimed to compare the effects of warfarin modified by cephalosporins with and without the NMTT side chain, using a Japanese health insurance claims database. The inclusion criteria were patients who (1) intravenously received second- or third-generation cephalosporins between April 2010 and March 2017 and (2) received warfarin during cephalosporin therapy. Patients were administered either cephalosporins with the NMTT side chain (NMTT group) or those without NMTT (non-NMTT group). After matching patient data by propensity score, the following outcomes were compared between the two groups: (1) proportion of patients administered vitamin K, (2) proportion of bleeding events, and (3) changes in the daily dose of warfarin. Among 203 patients, 100 patients (50 per group) were matched by the propensity score. The proportion of patients administered vitamin K was 6.0% in both groups. These patients intravenously received a single dose of menatetrenone; no bleeding was observed. The proportion of patients subjected to a reduction in the daily dose of warfarin was 6.5% and 4.3% in the NMTT and non-NMTT groups, respectively. As our study had a small sample size, we could not determine whether the risk of over anticoagulation of warfarin is affected by cephalosporins with or without NMTT side chain. However, we showed the bleeding risk was sufficiently low regardless of the presence/absence of the NMTT side chain.

Cardiac Arrhythmias in Critically Ill Patients With COVID-19: A Brief Review

Coronavirus disease 2019, caused by severe acute respiratory syndrome coronavirus 2, is now a global pandemic affecting more than 12 million patients across 188 countries. A significant proportion of these patients require admission to intensive care units for acute hypoxic respiratory failure and are at an increased risk of developing cardiac arrhythmias. The presence of underlying comorbidities, pathophysiologic changes imposed by the disease, and concomitant polypharmacy, increase the likelihood of life-threatening arrhythmias in these patients. Supraventricular, as well as ventricular arrhythmias, are common and are associated with significant morbidity and mortality. It is important to understand the interplay of various causal factors while instituting strategies to mitigate the impact of modifiable risk factors. Furthermore, avoidance and early recognition of drug interactions, along with prompt treatment, might help improve outcomes in this vulnerable patient population.

Guidance on Short-Term Management of Atrial Fibrillation in Coronavirus Disease 2019

Atrial fibrillation is a common clinical manifestation in hospitalized patients with coronavirus disease 2019 (COVID‐19). Medications used to treat atrial fibrillation, such as antiarrhythmic drugs and anticoagulants, may have significant drug interactions with emerging COVID‐19 treatments. Common unintended nontherapeutic target effects of COVID‐19 treatment include potassium channel blockade, cytochrome P 450 isoenzyme inhibition or activation, and P‐glycoprotein inhibition. Drug‐drug interactions with antiarrhythmic drugs and anticoagulants in these patients may lead to significant bradycardia, ventricular arrhythmias, or severe bleeding. It is important for clinicians to be aware of these interactions, drug metabolism changes, and clinical consequences when choosing antiarrhythmic drugs and anticoagulants for COVID‐19 patients with atrial fibrillation. The objective of this review is to provide a practical guide for clinicians who are managing COVID‐19 patients with concomitant atrial fibrillation.