Adverse drug reactions caused by drug-drug interactions reported to Croatian Agency for Medicinal Products and Medical Devices: a retrospective observational study

Potential of pharmacogenetics in minimizing drug therapy problems in cystic fibrosis

BACKGROUND

With advancements in CF drug development, people with cystic fibrosis (PwCF) now take a median of seven medications daily, increasing treatment complexity, risk of drug therapy problems (DTPs), and interference with treatment goals. Given that some of these DTPs can be prevented with preemptive pharmacogenetic testing, the overall goal of this study was to test the clinical utility of a multi-gene pharmacogenetics (PGx) panel in potentially reducing DTPs in PwCF.

METHODS

A population based retrospective study of patients with CF was conducted at the University of Utah Health Care System. The patients were genotyped for CYP450 enzymes using a pharmacogenomic assay, and their drug utilization information was obtained retrospectively. This pharmacogenomic information was combined with clinical guidelines to predict the number of actionable PGx interventions in this patient cohort.

RESULTS

A total of 52 patients were included in this study. In the patient sample, a minimum of one order of actionable PGx medication was observed in 75 % of the cases. Results revealed that 4.2 treatment modifications per 10 patients can be enabled with the help of a PGx intervention in this patient population. Additionally, our findings suggest that polymorphisms in CYP2D6 and CYP2C19 are most likely to be the primary contributors to DTP's within PwCF.

CONCLUSION

This study provides evidence that the PGx panel has the potential to help alleviate the clinical burden of DTPs in PwCF and can assist in informing pharmacotherapy recommendations. Future research should validate these findings and evaluate which subgroups of PwCF would most benefit from pharmacogenetic testing.

Risk of bleeding with concomitant use of oral anticoagulants and aspirin: A systematic review and meta-analysis

PURPOSE

Oral anticoagulants (OACs) and aspirin can trigger bleeding events when used alone or in combination. The purpose of this study was to compare the risk of any type of bleeding in individuals exposed to a combination of OAC and aspirin with the risk in those taking an OAC or aspirin alone.

METHODS

MEDLINE and Web of Science were queried in January 2021 for eligible articles. Studies were included if they were either randomized controlled trials (RCTs) or observational studies and evaluated the number of any bleeding events in two groups, one with exposure to both OAC and aspirin and one with exposure to OAC alone or aspirin alone. Pooled odds ratios were calculated using a random-effects model.

RESULTS

Forty-two studies were included. In an analysis of 15 RCTs and 19 observational studies evaluating OAC plus aspirin versus OAC alone, a significant difference in the risk of bleeding was observed in the combination groups, with an odds ratio [OR] of, 1.36 (95% CI, 1.15-1.59) for RCTs and an OR of 1.42 (95% CI-, 1.09-1.87) for observational studies. When OAC plus aspirin was compared to aspirin alone, a higher rate of bleeding was found in the combination group (OR, 2.36; 95%CI, 1.91-2.92) in the analysis of 15 RCTs, but no significant difference was found among 10 observational studies (OR, 1.93; 95% Cl, 0.99-3.75).

CONCLUSION

The risk of any type of bleeding was significantly increased among patients taking aspirin plus OAC compared to those taking OAC alone in both RCTs and observational studies. Evaluation of RCTs comparing OAC plus aspirin to aspirin alone suggests increased bleeding risk as well.

Drug-drug interactions and the risk of adverse drug reaction-related hospital admissions in the older population

AIMS

The aims of this study were to estimate potentially clinically important drug-drug interaction (DDI) prevalence, and the average causal effect of DDI exposure on adverse drug reaction (ADR)-related hospital admission, and to examine differences in health-related quality of life (HRQoL) and length of stay (LOS) per DDI exposure in an older (≥65 years) population acutely hospitalized.

METHODS

This was a cross-sectional study conducted among 798 older individuals acutely admitted to hospital in Ireland between 2016 and 2017. Medication (current/recently discontinued/over-the-counter) and clinical data (e.g., creatinine clearance) were available. DDIs were identified using the British National Formulary (BNF) and Stockley's Drug Interactions. Causal inference models for DDI exposure on ADR-related hospital admission were developed using directed acyclic graphs. Multivariable logistic regression was used to estimate the average causal effect. Differences in HRQoL (EQ-5D) and LOS per DDI exposure were examined non-parametrically. DDI prevalence, adjusted odds ratios (aOR), and 95% confidence intervals (CIs) are reported.

RESULTS

A total of 782 (98.0%) individuals using two or more drugs were included. Mean age was 80.9 (SD ± 7.5) years (range: 66-105); 52.2% were female; and 45.1% (n = 353) had an ADR-related admission. At admission, 316 (40.4% [95% CI: 37.0-43.9]) patients had at least one DDI. The average causal effect of DDI exposure on ADR-related hospital admission was aOR = 1.21 [95% CI: 0.89-1.64]. This was significantly increased by exposure to: DDIs which increase bleeding risk (aOR = 2.00 [1.26-3.12]); aspirin-warfarin (aOR = 2.78 [1.37-5.65]); and esomeprazole-escitalopram (aOR = 3.22 [1.13-10.25]. DDI-exposed patients had lower HRQoL (mean EQ-5D = 0.49 [±0.39]) compared those non-DDI-exposed (mean EQ-5D = 0.57 [±0.41]), (P = .03); and greater median LOS in hospital (8 [IQR5-16]days) compared those non-DDI-exposed (7 [IQR 4-14] days),(P = .04).

CONCLUSIONS

Potentially clinically important DDIs carry an increased average causal effect on ADR-related admission, significantly (two-fold) by exposure to DDIs that increase bleeding risk, which should be targeted for medicine optimization.

Indirect and Direct 65+ Patient Reporting of Non-Steroidal Anti-Inflammatory Drug-Induced Adverse Drug Reactions as a Source of Information on Polypharmacy and Polypharmacy-Related Risk

Background and Objectives: Non-steroidal anti-inflammatory drugs (NSAIDs), which have anti-inflammatory and analgesic properties, are commonly used in the treatment of various, particularly frequent, as well as chronic, conditions in older patients. Due to common polypragmasia in these patients and a high risk of adverse drug reactions (ADRs) and drug interactions, pain management poses a therapeutic challenge. This study describes the importance of ADR reports in the identification of polypharmacy and the ensuing interactions. Materials and Methods: Both healthcare professionals (HPs) and non-healthcare professionals (non-HPs) reports collected in the EudraVigilance database of NSAIDs, including most commonly co-reported medications and reported reactions, were analysed and differences between HPs and non-HPs reports were identified. Results: In the analysed period and group, non-HPs reported more reactions but indicated fewer drugs as suspect or concomitant. The outcomes of our analysis indicate more HP engagement and more detailed reports of serious ADRs when compared to non-serious individual case safety reports (ICSRs) by non-HPs, which appeared more detailed. Such reactions as kidney failure and increased risk of bleeding are known adverse reactions to NSAIDs and common symptoms of their interactions, which were described in the available literature. They were much more frequently reported by HPs than by non-HPs. Non-HPs more frequently reported reactions that may have been considered less significant by HPs. Conclusions: The differences between healthcare professionals' (HPs) and non-healthcare professionals' (non-HPs) reports may result from the fact that the reports from patients and their caregivers require a professional medical diagnosis based on symptoms described by the patient or additional diagnostic tests. This means that when appropriately classified, medically verified, and statistically analysed, the data may provide new evidence for the risks of medication use or drug interactions.

In Silico Analyses of a Promising Drug Candidate for the Treatment of Amyotrophic Lateral Sclerosis Targeting Superoxide Dismutase I Protein

Amyotrophic lateral sclerosis (ALS) is the most prevalent motor neuron disorder in adults, which is associated with a highly disabling condition. To date, ALS remains incurable, and the only drugs approved by the FDA for its treatment confer a limited survival benefit. Recently, SOD1 binding ligand 1 (SBL-1) was shown to inhibit in vitro the oxidation of a critical residue for SOD1 aggregation, which is a central event in ALS-related neurodegeneration. In this work, we investigated the interactions between SOD1 wild-type and its most frequent variants, i.e., A4V (NP_000445.1:p.Ala5Val) and D90A (NP_000445.1:p.Asp91Val), with SBL-1 using molecular dynamics (MD) simulations. The pharmacokinetics and toxicological profile of SBL-1 were also characterized in silico. The MD results suggest that the complex SOD1-SBL-1 remains relatively stable and interacts within a close distance during the simulations. This analysis also suggests that the mechanism of action proposed by SBL-1 and its binding affinity to SOD1 may be preserved upon mutations A4V and D90A. The pharmacokinetics and toxicological assessments suggest that SBL-1 has drug-likeness characteristics with low toxicity. Our findings, therefore, suggested that SBL-1 may be a promising strategy to treat ALS based on an unprecedented mechanism, including for patients with these frequent mutations.

COVID-19 drugs: potential interaction with ATP-binding cassette transporters P-glycoprotein and breast cancer resistance protein

Background

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2, has resulted in acute respiratory distress, fatal systemic manifestations (extrapulmonary as well as pulmonary), and premature mortality among many patients. Therapy for COVID-19 has focused on the treatment of symptoms and of acute inflammation (cytokine storm) and the prevention of viral infection. Although the mechanism of COVID-19 is not fully understood, potential clinical targets have been identified for pharmacological, immunological, and vaccinal approaches.

Area covered

Pharmacological approaches including drug repositioning have been a priority for initial COVID-19 therapy due to the time-consuming nature of the vaccine development process. COVID-19 drugs have been shown to manage the antiviral infection cycle (cell entry and replication of proteins and genomic RNA) and anti-inflammation. In this review, we evaluated the interaction of current COVID-19 drugs with two ATP-binding cassette transporters [P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP)] and potential drug-drug interactions (DDIs) among COVID-19 drugs, especially those associated with P-gp and BCRP efflux transporters.

Expert opinion

Overall, understanding the pharmacodynamic/pharmacokinetic DDIs of COVID-19 drugs can be useful for pharmacological therapy in COVID-19 patients.

Adverse drug reactions and correlations with drug–drug interactions: A retrospective study of reports from 2011 to 2020

Introduction: Adverse drug reactions (ADRs) represent a public health problem worldwide that deserves attention due to the impact on mortality, morbidity, and healthcare costs. Drug–drug interactions (DDIs) are an important contributor to ADRs. Most of the studies focused only on potential DDIs (pDDIs), while the detailed data are limited regarding the ADRs associated with actual DDIs.

Methods: This retrospective study evaluated ADRs reported between 2011 and 2020 in a tertiary hospital. The causality and severity of ADRs were evaluated through the Naranjo Algorithm and Hartwig’s scale, respectively. Preventability classification was based on the modified Schoumock and Thornton scale. For ADRs with at least two suspected drugs, pDDIs were identified according to the Lexi-Interact. We further checked whether the ADR description in the reports corresponded to the clinical consequences of the pDDIs.

Results: A total of 1,803 ADRs were reported, of which 36.77% ADRs were classified as mild, 43.26% as moderate, and 19.97% as severe. The assessment of causality showed that the distributions of definite, probable, and possible categories were 0.33%, 58.68%, and 40.99%, respectively. A total of 53.97% of ADRs were identified as preventable ADRs, while 46.03% were recognized as unpreventable. The severity of ADRs was significantly correlated with age, the number of suspected drugs and preventability. Antimicrobial agents were the most common implicated pharmacological group, and the most frequently affected system was the gastrointestinal system. Considering individual drugs, aspirin was the most frequently reported drug. Among 573 ADRs with at least two suspected drugs, 105 ADRs were caused by actual DDIs, of which only 59 and 6 ADRs were caused by actual DDIs in category D and X, respectively. The most frequent drugs involved in actual DDIs of category D were aspirin and heparin, with the majority of ADRs being gastrointestinal bleeding.

Conclusion: This study analyzed the pattern of ADRs in detail and obtained clinical evidence about ADRs associated with actual DDIs. These findings may be useful to compare patterns between different centers and to design preventive strategies for ADRs. Continuous education and training should be provided for physicians regarding the knowledge and recognition of ADRs associated with DDIs.

Prediction of potential drug interactions between repurposed COVID-19 and antitubercular drugs: an integrational approach of drug information software and computational techniques data

Introduction:

Tuberculosis is a major respiratory disease globally with a higher prevalence in Asian and African countries than rest of the world. With a larger population of tuberculosis patients anticipated to be co-infected with COVID-19 infection, an ongoing pandemic, identifying, preventing and managing drug–drug interactions is inevitable for maximizing patient benefits for the current repurposed COVID-19 and antitubercular drugs.

Methods:

We assessed the potential drug–drug interactions between repurposed COVID-19 drugs and antitubercular drugs using the drug interaction checker of IBM Micromedex®. Extensive computational studies were performed at a molecular level to validate and understand the drug–drug interactions found from the Micromedex drug interaction checker database at a molecular level. The integrated knowledge derived from Micromedex and computational data was collated and curated for predicting potential drug–drug interactions between repurposed COVID-19 and antitubercular drugs.

Results:

A total of 91 potential drug–drug interactions along with their severity and level of documentation were identified from Micromedex between repurposed COVID-19 drugs and antitubercular drugs. We identified 47 pharmacodynamic, 42 pharmacokinetic and 2 unknown DDIs. The majority of our molecular modelling results were in line with drug–drug interaction data obtained from the drug information software. QT prolongation was identified as the most common type of pharmacodynamic drug–drug interaction, whereas drug–drug interactions associated with cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp) inhibition and induction were identified as the frequent pharmacokinetic drug–drug interactions. The results suggest antitubercular drugs, particularly rifampin and second-line agents, warrant high alert and monitoring while prescribing with the repurposed COVID-19 drugs.

Conclusion:

Predicting these potential drug–drug interactions, particularly related to CYP3A4, P-gp and the human Ether-à-go-go-Related Gene proteins, could be used in clinical settings for screening and management of drug–drug interactions for delivering safer chemotherapeutic tuberculosis and COVID-19 care. The current study provides an initial propulsion for further well-designed pharmacokinetic-pharmacodynamic-based drug–drug interaction studies.

Plain Language Summary

Potential Drug Interactions of Repurposed COVID-19 Drugs with Lung Cancer Pharmacotherapies

Lung cancer patients are at heightened risk for developing COVID-19 infection as well as complications due to multiple risk factors such as underlying malignancy, anti-cancer treatment induced immunosuppression, additional comorbidities and history of smoking. Recent literatures have reported a significant proportion of lung cancer patients coinfected with COVID-19. Chloroquine, hydroxychloroquine, lopinavir/ritonavir, ribavirin, oseltamivir, remdesivir, favipiravir, and umifenovir represent the major repurposed drugs used as potential experimental agents for COVID-19 whereas azithromycin, dexamethasone, tocilizumab, sarilumab, famotidine and ceftriaxone are some of the supporting agents that are under investigation for COVID-19 management. The rationale of this review is to identify potential drug-drug interactions (DDIs) occurring in lung cancer patients receiving lung cancer medications and repurposed COVID-19 drugs using Micromedex and additional literatures. This review has identified several potential DDIs that could occur with the concomitant treatments of COVID-19 repurposed drugs and lung cancer medications. This information may be utilized by the healthcare professionals for screening and identifying potential DDIs with adverse outcomes, based on their severity and documentation levels and consequently design prophylactic and management strategies for their prevention. Identification, reporting and management of DDIs and dissemination of related information should be a major consideration in the delivery of lung cancer care during this ongoing COVID-19 pandemic for better patient outcomes and updating guidelines for safer prescribing practices in this coinfected condition.

Spontaneous Reports of Serious Adverse Drug Reactions Resulting From Drug-Drug Interactions: An Analysis From the French Pharmacovigilance Database

Few data are available on the clinical impact of drug-drug interactions (DDIs). Most of the studies are limited to the analysis of exposure to potential DDI or the targeted impact of the combination of a few drugs or therapeutic classes. The analysis of adverse drug reaction (ADR) reports could be a mean to study generally the adverse effects identified due to a DDI. Our objective was to describe the characteristics of ADRs resulting from DDIs reported to the French Pharmacovigilance system and to identify the drugs most often implicated in these ADRs. Considering all ADR reports from January 01, 2012, to December 31, 2016, we identified all cases of ADR resulting from a DDI (DDI-ADRs). We then described these in terms of patients' characteristics, ADR seriousness, drugs involved (two or more per case), and ADR type. Of the 4,027 reports relating to DDI-ADRs, 3,303 were related to serious ADRs. Patients with serious DDI-ADRs had a median age of 76 years (interquartile range: 63-84); 53% were male. Of all serious DDI-ADRs, 11% were life-threatening and 8% fatal. In 36% of cases, the DDI causing the ADR involved at least three drugs. Overall, 8,424 different drugs were mentioned in the 3,303 serious DDI-ADRs considered. Altogether, drugs from the "antithrombotic agents" subgroup were incriminated in 34% of serious DDI-ADRs. Antidepressants were the second most represented therapeutic/pharmacological subgroup (5% of serious DDI-ADRs). Among the 3,843 ADR types reported in the 3,303 serious DDI-ADRs considered, the most frequently represented were hemorrhage (40% clinical hemorrhage; 6% biological hemorrhage), renal failure (8%), pharmacokinetic alteration (5%), and cardiac arrhythmias (4%). Hemorrhagic accidents are still an important part of serious ADRs resulting from DDIs reported in France. The other clinical consequences of DDIs seem less well identified by pharmacovigilance. Moreover, more than one-third of serious DDI-ADRs involved at least three drugs.

Safety and Tolerability of Mass Diethylcarbamazine and Albendazole Administration for the Elimination of Lymphatic Filariasis in Kenya: An Active Surveillance Study

Preventive chemotherapy with diethylcarbamazine citrate (DEC) and albendazole (ALB) is the core intervention strategy to eliminate lymphatic filariasis (LF). We conducted a large-scale prospective active safety surveillance study to identify the incidence, type, severity, and risk factors for adverse events (AEs) following mass drug administration (MDA) of single-dose DEC and ALB in 10,010 participants from Kilifi County, Kenya. AEs were actively monitored and graded at 24 h, 48 h, and on day 7 Post-MDA. Out of 10,010 enrolled study participants, 1621 participants reported a total of 3102 AEs during a seven-day follow-up. The cumulative incidence of AEs was 16.2% (95% CI, 15.5–16.9%). The proportion of participants who experienced one, two, or ≥three types of AEs was 9.2%, 4.6%, 2.4%, respectively. AEs were mild (87.3%), moderate (12.4%), and severe (0.3%) and resolved within 72 h. The five most common AEs were dizziness (5.9%), headache (5.6%), loss of appetite (3.3%), fever (2.9%), and drowsiness (2.6%). Older age, taking concurrent medications, ≥three tablets of DEC, and type of meal taken before MDA were significant predictors of AEs. One in six participants experienced systemic mild-to-moderate severity grading and transient AEs. DEC and ALB co-administration for the elimination of LF is generally safe and well-tolerated.

Assessment of Potential Drug–Drug Interactions and Their Predictors in Chronic Outpatient Department of Dessie Referral Hospital, Dessie, Northeast Ethiopia

Objective

To assess the prevalence and predictors of Potential drug–drug interactions (DDIs) at the chronic outpatient department of Dessie Referral Hospital, Dessie, Northeast Ethiopia.

Patients and Methods

A cross-sectional study was carried out on the medical records of patients treated in the chronic ambulatory department of Dessie Referral Hospital (DRH), from March 1/2019 to May 30/2019. Ethical clearance was granted from the department of pharmacy, college of medicine, and health sciences, Wollo University. Lexi-comp computer program database was used to detect pDDIs. SPSS version 22 was used to produce a descriptive analysis of the background data and logistic regression to identify predictors of pDDIs.

Results

In this study, the medical record of 300 patients has been reviewed and 489 pDDIs have been identified. The prevalence of pDDIs per patient was 1.63. Of all the identified pDDIs, the moderate severity interactions were the majority, 88.55% (n=433) followed by 8.38% (n=41) of minor, 2.66% (n=13) of major, and 0.41% (n=2) of contraindicated drug interactions. Taking three or more drugs at a time has been found as a statistically significant predictor of the occurrence of pDDIs.

Conclusion

A high rate of moderate severity pDDIs have been recorded. A system of checks and balances should be developed and executed for all those who are involved in prescribing, dispensing, and administration of medications for effective identification and prevention of pDDIs.

Identifying and Characterizing Serious Adverse Drug Reactions Associated With Drug-Drug Interactions in a Spontaneous Reporting Database

Background: Drug-drug interactions (DDIs) are an important cause of adverse drug reactions (ADRs). In literature most of studies focus only on potential DDIs, while detailed data on serious ADRs associated with DDIs are limited. Our aim is to identify and characterize serious ADRs caused by DDIs using a spontaneous reporting database.

Methods: All serious ADR reports, not related to vaccines and with a “definite”, “probable” or “possible” causality assessment, inserted into the National Pharmacovigilance database from Veneto Region (January 1, 2015 to May 31, 2020) were analyzed. A list of drug pairs was created by selecting the reports containing at least two suspected or concomitant drugs. We verified which drug pairs potentially interacted according to the online version of DRUGDEX^® system. For each potential DDI we controlled whether the ADR description in the report corresponded to the interaction effect as described in Micromedex. A detailed characterization of all serious reports containing an occurring DDI was performed.

Results: In the study period a total of 31,604 reports of suspected ADRs from the Veneto Region were identified, of which 2,195 serious reports (6.9% of all ADR reports) containing at least two suspected or concomitant drugs were analyzed. We identified 1,208 ADR reports with at least one potential DDI (55.0% of 2,195) and 381 reports (17.4% of 2,195 reports) with an occurring ADR associated with a DDI. The median age of patients and the number of contraindicated or major DDIs were significantly higher in reports with an occurring DDI. Warfarin was the most frequently reported interacting drug and the most common ADRs were gastrointestinal or cerebral hemorrhagic events. The proton pump inhibitors/warfarin, followed by platelet aggregation inhibitors/warfarin were the drug-drug combinations most frequently involved in ADRs caused by DDIs. The highest proportion of fatal reports was observed with platelet aggregation inhibitors/warfarin and antidepressants/warfarin.

Conclusion: Our findings showed that about one-third of patients exposed to a potential DDI actually experienced a serious ADR. Furthermore, our study confirms that a spontaneous reporting database could be a valuable resource for identifying and characterizing ADRs caused by DDIs and the drugs leading to serious ADRs and deaths.

Spontaneous reports of adverse drug reactions related to oral anticoagulants in the Czech Republic

Background Oral anticoagulants are established drugs of choice for the prevention and treatment of thromboembolic events. However, monitoring their safety remains warranted. Objective The aim was to analyze spontaneous reports of adverse drug reactions related to oral anticoagulants in the Czech Republic. Setting Retrospective observational pharmacovigilance study. Methods Adverse drug reaction reports were obtained from the State Institute for Drug Control between January 2005 and November 2017. Reports related to warfarin, dabigatran, apixaban, and rivaroxaban received from healthcare professionals and patients were analyzed. Main outcome measure Frequency and nature of adverse drug reactions reported to oral anticoagulants. Results In total, 297 reports containing 672 adverse drug reactions were received; 269 reports were sent by healthcare professionals (85% by physicians). In 65% of all reports, reactions were due to direct oral anticoagulants. A higher total number of adverse drug reactions was associated with direct oral anticoagulants than with warfarin [reporting odds ratio (ROR): 10.76; confidence interval (CI): 8.70-13.32; p < 0.001]. Along with the increasing utilization of direct oral anticoagulants, the reporting rate gradually declined over time, especially for rivaroxaban and apixaban. Fatal outcomes were reported in 7%, mostly for dabigatran. Hemorrhagic reactions were the most frequently reported adverse drug reactions (37% associated with dabigatran, 28% with apixaban, 24% with warfarin, and 23% with rivaroxaban), and compared to warfarin, they were significantly more often associated with direct oral anticoagulants (ROR: 14.36; CI: 9.57-21.54; p < 0.001). Conclusion The number of adverse drug reaction reports related to oral anticoagulants in the Czech Republic was relatively low, compared to other studies, but 96% of the cases were serious. Data from spontaneous adverse drug reactions reporting should be further analyzed in order to obtain additional information on the safety profile of oral anticoagulants.

Prevalence of clinically manifested drug interactions in hospitalized patients: A systematic review and meta-analysis

AIMS

This review aims to determine the prevalence of clinically manifested drug-drug interactions (DDIs) in hospitalized patients.

METHODS

PubMed, Scopus, Embase, Web of Science, and Lilacs databases were used to identify articles published before June 2019 that met specific inclusion criteria. The search strategy was developed using both controlled and uncontrolled vocabulary related to the following domains: "drug interactions," "clinically relevant," and "hospital." In this review, we discuss original observational studies that detected DDIs in the hospital setting, studies that provided enough data to allow us to calculate the prevalence of clinically manifested DDIs, and studies that described the drugs prescribed or provided DDI adverse reaction reports, published in either English, Portuguese, or Spanish.

RESULTS

From the initial 5,999 articles identified, 10 met the inclusion criteria. The pooled prevalence of clinically manifested DDIs was 9.2% (CI 95% 4.0-19.7). The mean number of medications per patient reported in six studies ranged from 4.0 to 9.0, with an overall average of 5.47 ± 1.77 drugs per patient. The quality of the included studies was moderate. The main methods used to identify clinically manifested DDIs were evaluating medical records and ward visits (n = 7). Micromedex® (27.7%) and Lexi-Comp® (27.7%) online reference databases were commonly used to detect DDIs and none of the studies evaluated used more than one database for this purpose.

CONCLUSIONS

This systematic review showed that, despite the significant prevalence of potential DDIs reported in the literature, less than one in ten patients were exposed to a clinically manifested drug interaction. The use of causality tools to identify clinically manifested DDIs as well as clinical adoption of DDI lists based on actual adverse outcomes that can be identified through the implementation of real DDI notification systems is recommended to reduce the incidence of alert fatigue, enhance decision-making for DDI prevention or resolution, and, consequently, contribute to patient safety.

Methodological Errors in Clinical Studies Published by Medical Journals of Ex-Yugoslav Countries

INTRODUCTION

Certain methodological principles should be inexcusably followed when designing clinical or observational research to avoid bias and presentation of results that do not reflect the truth about the phenomenon that is the object of the study.

AIM

The aim of this study was to compare the methodological quality of clinical trials and observational studies published in medical journals from ex-Yugoslav countries indexed in Pubmed/MEDLINE.

METHODS

Clinical studies published in medical journals of ex-Yugoslav countries were retrieved from the Pubmed/MEDLINE database, and the sample for analysis was randomly chosen from the retrieved publications. The rate of the most common errors in the design of clinical/observational studies was established by a careful reading of the sampled publications and their checking against predefined criteria.

RESULTS

The studies published in two countries that are now member states of the European Union (Slovenia and Croatia) have significantly higher citation rates, impact factor, and methodological quality scores than studies from other ex-Yugoslav countries. While publications from Croatia show clear improvement trend throughout the last two decades, which is visible also in the last 10 years in Slovenia and Bosnia and Herzegovina, quality of clinical research published in journals from Serbia was stagnating in the same period.

CONCLUSIONS

There are significant differences in methodological quality and scientometric characteristics of clinical research published in medical journals of ex-Yugoslav countries that could be mitigated by more intensive training of clinical researchers in statistics and research design, as well as by more rigorous editorial practices.

A super-combo-drug test to detect adverse drug events and drug interactions from electronic health records in the era of polypharmacy

Pharmacoinformatics research has experienced a great deal of successes in detecting drug-induced adverse events (AEs) using large-scale health record databases. In the era of polypharmacy, pharmacoinformatics faces many new challenges, and two significant challenges are to detect high-order drug interactions and to handle strongly correlated drugs. In this article, we propose a super-combo-drug test (SupCD-T) to address the aforementioned two challenges. SupCD-T detects drug interactions by identifying optimal drug combinations with increased AE risks. In addition, SupCD-T increases the statistical powers to detect single-drug effects by combining strongly correlated drugs. Although SupCD-T does not distinguish single-drug effects from their combination effects, it is noticeably more powerful in selecting an individual drug effect in the multiple regression analysis, where confounding justification between two correlated drugs reduces the power in testing the individual drug effects on AEs. Our simulation studies demonstrate that SupCD-T has generally better power comparing with the multiple regression analysis. In addition, SupCD-T is able to select meaningful drug combinations (eg, highly coprescribed drugs). Using electronic health record database, we illustrate the utility of SupCD-T and discover a number of drug combinations that have increased risk in myopathy. Some novel drug combinations have not yet been investigated and reported in the pharmacology research.

The prevalence and severity of potential drug-drug interactions among adult polypharmacy patients at outpatient clinics in Jordan

Objective

To assess the prevalence of potential drug-drug interactions (pDDIs) among polypharmacy patients in Jordan using Lexicomp®. Additionally, this study aims to categorize and rate the identified pDDIs according to interaction risk, severity, and reliability.

Methods

A descriptive cross-sectional study was conducted at six different hospitals representing different public health sectors in Jordan (ministry of health, royal medical services, and university-affiliated hospitals). Polypharmacy patients from outpatient clinics (e.g., cardiology,& and internal medicine) were identified, recruited, and interviewed by clinical pharmacists. pDDIs were assessed using the Lexicomp® mobile application and classified according to interaction risk rating, severity, and reliability rating. Furthermore, the prevalence of pDDIs across chronic medical conditions was assessed. P-value <0.05 was considered as significant.

Results

A total of 801 patients with polypharmacy were identified. The average number of drugs per patient was 6.6 ± 1.96, with an average of 4.2 ± 3.0 pDDIs per patient. Potential drug-drug interactions were detected in 769 patients (96%), with a total of 3359 interactions. Blood pressure lowering agents were involved in 39.9% of the pDDIs. Cardiovascular system drugs contributed to the largest share of pDDIs (46.6%). While diuretics had the major share of interactions among cardiovascular system drugs (16.2%), drugs used in diabetes had the highest share across all groups (17.1%). The majority of pDDIs were of “C” risk rating with a moderate interaction severity, whilst 1.6% of pDDIs could have been avoided in the first place as the concurrent administration of these agents is contraindicated (i.e., risk rating X). Patients with cardiovascular diseases, diabetes, chronic obstructive pulmonary disease, gout, and chronic kidney disease were associated with the highest number of potential drug-drug interactions.

Conclusion

Our study showed that 96% of polypharmacy patients at outpatient clinics have at least one pDDI. Almost half of the detected interactions involved cardiovascular medications. The majority of these pDDIs had moderate severity, with no more than 10% of the interactions requiring therapy modification.

Detection of drug-drug interactions through data mining studies using clinical sources, scientific literature and social media

Drug-drug interactions (DDIs) constitute an important concern in drug development and postmarketing pharmacovigilance. They are considered the cause of many adverse drug effects exposing patients to higher risks and increasing public health system costs. Methods to follow-up and discover possible DDIs causing harm to the population are a primary aim of drug safety researchers. Here, we review different methodologies and recent advances using data mining to detect DDIs with impact on patients. We focus on data mining of different pharmacovigilance sources, such as the US Food and Drug Administration Adverse Event Reporting System and electronic health records from medical institutions, as well as on the diverse data mining studies that use narrative text available in the scientific biomedical literature and social media. We pay attention to the strengths but also further explain challenges related to these methods. Data mining has important applications in the analysis of DDIs showing the impact of the interactions as a cause of adverse effects, extracting interactions to create knowledge data sets and gold standards and in the discovery of novel and dangerous DDIs.

An MCEM Framework for Drug Safety Signal Detection and Combination from Heterogeneous Real World Evidence

Delayed drug safety insights can impact patients, pharmaceutical companies, and the whole society. Post-market drug safety surveillance plays a critical role in providing drug safety insights, where real world evidence such as spontaneous reporting systems (SRS) and a series of disproportional analysis serve as a cornerstone of proactive and predictive drug safety surveillance. However, they still face several challenges including concomitant drugs confounders, rare adverse drug reaction (ADR) detection, data bias, and the under-reporting issue. In this paper, we are developing a new framework that detects improved drug safety signals from multiple data sources via Monte Carlo Expectation-Maximization (MCEM) and signal combination. In MCEM procedure, we propose a new sampling approach to generate more accurate SRS signals for each ADR through iteratively down-weighting their associations with irrelevant drugs in case reports. While in signal combination step, we adopt Bayesian hierarchical model and propose a new summary statistic such that SRS signals can be combined with signals derived from other observational health data allowing for related signals to borrow statistical support with adjustment of data reliability. They combined effectively alleviate the concomitant confounders, data bias, rare ADR and under-reporting issues. Experimental results demonstrated the effectiveness and usefulness of the proposed framework.

Clinically relevant potential drug-drug interactions among outpatients: A nationwide database study

BACKGROUND

Adverse drug events due to drug-drug interactions (DDIs) represent a considerable public health burden, also in Slovenia. A better understanding of the most frequently occurring potential DDIs may enable safer pharmacotherapy and minimize drug-related problems.

OBJECTIVES

The aim of this study was to evaluate the prevalence and predictors of potential DDIs among outpatients in Slovenia.

METHODS

An analysis of potential DDIs was performed using health claims data on prescription drugs from a nationwide database. The Lexi-Interact Module was used as the reference source of interactions. The influence of patient-specific predictors on the risk of potential clinically relevant DDIs was evaluated using logistic regression model.

RESULTS

The study population included 1,179,803 outpatients who received 15,811,979 prescriptions. The total number of potential DDI cases identified was 3,974,994, of which 15.6% were potentially clinically relevant. Altogether, 9.3% (N = 191,213) of the total population in Slovenia is exposed to clinically relevant potential DDIs, and the proportion is higher among women and the elderly. After adjustment for cofactors, higher number of medications and older age are associated with higher odds of clinically relevant potential DDIs. The burden of DDIs is highest with drug combinations that increase risk of bleeding, enhance CNS depression or anticholinergic effects or cause cardiovascular complications.

CONCLUSION

The current study revealed that 1 in 10 individuals in the total Slovenian population is exposed to clinically relevant potential DDIs yearly. Taking into account the literature based conservative estimate that approximately 1% of potential DDIs result in negative health outcomes, roughly 1800 individuals in Slovenia experience an adverse health outcome each year as a result of clinically relevant potential interactions alone.

Actual drug-drug interactions in elderly patients discharged from internal medicine clinic: a prospective observational study

PURPOSE

The aim of the study was to evaluate the incidence and type of actual drug-drug interactions (DDIs) that result in adverse drug reactions (ADRs) or diminished therapeutic effect in elderly patients within 30 days of discharge from an internal medicine clinic.

METHODS

A prospective observational study was conducted at the Internal Medicine Clinic of University Hospital Dubrava, Zagreb, Croatia, between October and December 2011. Patients aged ≥ 65 years discharged from the Internal Medicine Clinic during the study period with a prescription for two or more medications were eligible for inclusion in the study. A total of 222 patients were ultimately enrolled in the study. For each patient, potential DDIs were identified using Lexi-Interact software. The follow-up visit was scheduled approximately 30 days after discharge. Causality between DDIs and ADRs or diminished therapeutic effect of drugs was assessed by two independent clinicians.

RESULTS

Potential DDIs were identified in 190 (85.6 %) patients. Actual DDIs were detected in 21 (9.5 %) patients. In 19 patients, DDIs resulted in an ADR. Diminished therapeutic effect resulting from DDIs was detected in two patients. Angiotensin-converting enzyme inhibitors were the drug class most frequently associated with DDI-related ADRs.

CONCLUSIONS

A significant incidence of actual DDIs suggests that DDIs play an important role in patient safety. Drug therapy should be initiated if absolutely necessary, and the number of drugs used to treat elderly patients should be minimized to reduce the incidence of DDI-related adverse patient outcomes.

Health promotion or pharmacological treatment for chronic diseases?

Over the last years medicine has progressed very rapidly. Communicable diseases, which were the leading causes of mortalities, are not anymore, especially in developed countries. Currently, non-communicable diseases are more prevalent, and most of them are related to changes in our daily habits and degenerative processes. Most of these diseases are chronic, need continuous care and treatment with limited improvement and high costs. The General Assembly of the United Nations in its resolution 65/238 recognized the primary role and responsibility of Governments in responding to the challenge of non-communicable diseases and the essential need for the efforts and engagement of all sectors of society to generate an effective response. Special emphasis has been concentrated on pharmacological treatments for most of chronic non-communicable diseases with the challenge to discover new drugs for treating, in most cases, chronic irreversible degenerative diseases associated with aging. Little care was given to non-pharmacological lines of treatment.