A Comparison of Active Pharmacovigilance Strategies Used to Monitor Adverse Events to Antiviral Agents: A Systematic Review.

INTRODUCTION: The safety of antiviral agents in real-world clinical settings is crucial, as pre-marketing studies often do not capture all adverse events (AE). Active pharmacovigilance strategies are essential for detecting and characterising these AE comprehensively. OBJECTIVE: The aim of this study was to identify and characterise active pharmacovigilance strategies used in real-world clinical settings for patients under systemic antiviral agents, focusing on the frequency of AE and the clinical data sources used. METHODS: We conducted a systematic review by searching three electronic bibliographic databases targeting observational prospective active pharmacovigilance studies, phase IV clinical trials for post-marketing safety surveillance, and interventional studies assessing active pharmacovigilance strategies, focusing on individuals exposed to systemic antiviral agents. RESULTS: We included 36 primary studies, predominantly using Drug Event Monitoring (DEM), with a minority employing sentinel sites and registries. Human immunodeficiency virus (HIV) was the most common condition, with the majority using DEM. Within the DEM, there was a wide range of incidences of patients experiencing at least one AE, and most of these studies used one or two data sources. Sentinel site studies were less common, with two on hepatitis C virus (HCV) and one on HIV, each relying on one or two data sources. The single study using a registry focusing on HIV therapy reported using just one data source. Patient interviews were the most common data source, followed by medical records and laboratory tests. The quality of the studies was considered 'good' in 18/36, 'fair' in 1/36, and 'poor' in 17/36 studies. CONCLUSION: DEM was the predominant pharmacovigilance strategy, employing multiple data sources, and appears to increase the likelihood of detecting higher AE incidence. Establishing such a framework would facilitate a more detailed and consistent approach across different studies and settings.

Renal effects of selective cyclooxygenase-2 inhibitor anti-inflammatory drugs: A systematic review and meta-analysis.

Background: Selective cyclooxygenase-2 inhibitor anti-inflammatory drugs (coxibs) are associated with the development of adverse events, mainly gastrointestinal and cardiovascular, but renal effects are less known. Objective: To assess the renal risks of coxibs compared to placebo by means of a systematic review and meta-analysis. Methods: Randomized controlled trials that assessed renal effects of coxibs (celecoxib, etoricoxib, lumiracoxib, parecoxib, and valdecoxib) were searched in PubMed, Embase, Scopus and other sources up to March 2024. Two independent reviewers performed study screening, data extraction, and risk of bias assessment. Random effect meta-analysis was employed to calculate the relative risks (RR) and 95% confidence intervals (CI) of renal effects of coxibs compared to placebo and inconsistency among studies (I 2 ). Certainty of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation approach. Results: Out of 5284 retrieved records, 49 studies (comprising 46 reports) were included. Coxibs increased the risk of edema (RR 1.46; 95% CI 1.15, 1.86; I 2  = 0%; 34 studies, 19,754 participants; moderate-certainty evidence), and celecoxib increased hypertensive or renal events (RR 1.24; 95% CI 1.08, 1.43; I 2  = 0%; 2 studies, 3589 participants; moderate-certainty evidence). Etoricoxib increased the risk of hypertension (RR 1.98; 95% CI 1.14, 3.46; I 2  = 34%; 13 studies, 6560 participants; moderate-certainty evidence); no difference was observed when pooling all coxibs (RR 1.26; 95% CI 0.91, 1.76; I 2  = 26%; 30 studies, 16,173 participants; moderate-certainty evidence). Conclusions: Coxibs likely increase the renal adverse effects, including hypertension and edema. Awareness about the renal risks of coxibs should be increased, mainly in high-risk patient.

Composite outcome measures in high-impact critical care randomised controlled trials: a systematic review.

BACKGROUND: The use of composite outcome measures (COM) in clinical trials is increasing. Whilst their use is associated with benefits, several limitations have been highlighted and there is limited literature exploring their use within critical care. The primary aim of this study was to evaluate the use of COM in high-impact critical care trials, and compare study parameters (including sample size, statistical significance, and consistency of effect estimates) in trials using composite versus non-composite outcomes. METHODS: A systematic review of 16 high-impact journals was conducted. Randomised controlled trials published between 2012 and 2022 reporting a patient important outcome and involving critical care patients, were included. RESULTS: 8271 trials were screened, and 194 included. 39.1% of all trials used a COM and this increased over time. Of those using a COM, only 52.6% explicitly described the outcome as composite. The median number of components was 2 (IQR 2-3). Trials using a COM recruited fewer participants (409 (198.8-851.5) vs 584 (300-1566, p = 0.004), and their use was not associated with increased rates of statistical significance (19.7% vs 17.8%, p = 0.380). Predicted effect sizes were overestimated in all but 6 trials. For studies using a COM the effect estimates were consistent across all components in 43.4% of trials. 93% of COM included components that were not patient important. CONCLUSIONS: COM are increasingly used in critical care trials; however effect estimates are frequently inconsistent across COM components confounding outcome interpretations. The use of COM was associated with smaller sample sizes, and no increased likelihood of statistically significant results. Many of the limitations inherent to the use of COM are relevant to critical care research.

Unveiling the future: precision pharmacovigilance in the era of personalized medicine.

In the era of personalized medicine, pharmacovigilance faces new challenges and opportunities, demanding a shift from traditional approaches. This article delves into the evolving landscape of drug safety monitoring in the context of personalized treatments. We aim to provide a succinct reflection on the intersection of tailored therapeutic strategies and vigilant pharmacovigilance practices. We discuss the integration of pharmacogenetics in enhancing drug safety, illustrating how genetic profiling aids in predicting drug responses and adverse reactions. Emphasizing the importance of phase IV-post-marketing surveillance, we explore the limitations of pre-marketing trials and the necessity for a comprehensive approach to drug safety. The article discusses the pivotal role of pharmacogenetics in pre-exposure risk management and the redefinition of pharmacoepidemiological methods for post-exposure surveillance. We highlight the significance of integrating patient-specific genetic profiles in creating personalized medication leaflets and the use of advanced computational methods in data analysis. Additionally, we examine the ethical, privacy, and data security challenges inherent in precision medicine, emphasizing their implications for patient consent and data management.

Assessing medication use patterns by clinical outcomes severity among inpatients with COVID-19: A retrospective drug utilization study.

PURPOSE: This study assessed medication patterns for inpatients at a central hospital in Portugal and explored their relationships with clinical outcomes in COVID-19 cases. METHODS: A retrospective study analyzed inpatient medication data, coded using the Anatomical Therapeutic Chemical classification system, from electronic patient records. It investigated the association between medications and clinical severity outcomes such as ICU admissions, respiratory/circulatory support needs, and hospital discharge status, including mortality (identified by ICD-10-CM/PCS codes). Multivariate analyses incorporating demographic data and comorbidities were used to adjust for potential confounders and understand the impact of medication patterns on disease progression and outcomes. RESULTS: The analysis of 2688 hospitalized COVID-19 patients (55.3% male, average age 62.8 years) revealed a significant correlation between medication types and intensity and disease severity. Cases requiring ICU admission or ECMO support often involved blood and blood-forming organ drugs. Increased use of nervous system and genitourinary hormones was observed in nonsurvivors. Corticosteroids, like dexamethasone, were common in critically ill patients, while tocilizumab was used in ECMO cases. Medications for the alimentary tract, metabolism, and cardiovascular system, although widely prescribed, were linked to more severe cases. Invasive mechanical ventilation correlated with higher usage of systemic anti-infectives and musculoskeletal medications. Trends in co-prescribing blood-forming drugs with those for acid-related disorders, analgesics, and antibacterials were associated with intensive interventions and worse outcomes. CONCLUSIONS: The study highlights complex medication regimens in managing severe COVID-19, underscoring specific drug patterns associated with critical health outcomes. Further research is needed to explore these patterns.

MedGAN: optimized generative adversarial network with graph convolutional networks for novel molecule design.

Generative Artificial Intelligence can be an important asset in the drug discovery process to meet the demand for novel medicines. This work outlines the optimization and fine-tuning steps of MedGAN, a deep learning model based on Wasserstein Generative Adversarial Networks and Graph Convolutional Networks, developed to generate new quinoline-scaffold molecules from complex molecular graphs, including hyperparameter adjustments and evaluations of drug-likeness attributes such as pharmacokinetics, toxicity, and synthetic accessibility. The best model was capable of generating 25% valid molecules, 62% fully connected, from which 92% were quinolines, 93% were novel, and 95% unique, preserving chirality, atom charge, and favorable drug-like properties while generating 4831 novel quinolines. These results provide valuable insights into how activation functions, optimizers, learning rates, neuron units, molecule size and constitution, and scaffold structure affect the performance of generative models and their potential to create new molecular structures, enhancing deep learning applications in computational drug design.

Public's perspective on COVID-19 adenovirus vector vaccines after thrombosis with thrombocytopenia syndrome (TTS) reports and associated regulatory actions - A cross-sectional study in six EU member states.

OBJECTIVE: In 2021, thrombosis with thrombocytopenia syndrome (TTS) was confirmed by the European Medicines Agency (EMA) as a rare side effect of the COVID-19 adenovirus vector vaccines Vaxzevria® and Jcovden®. This study aimed to describe the public's knowledge of TTS and how it affected the willingness to be vaccinated with COVID-19 vaccines and other vaccines in six European countries. METHODS: From June to October of 2022, a multi-country cross-sectional online survey was conducted in Denmark, Greece, Latvia, Netherlands, Portugal, and Slovenia. The minimum target of participants to be recruited was based on the size of the country's population. The results were analysed descriptively. RESULTS: In total, 3794 respondents were included in the analysis; across the six countries, 33.3 %-68.3 % reported being familiar with signs and symptoms of TTS, although 3.1-61.4 % of those were able to identify the symptoms correctly. The reported changes in willingness to be vaccinated against COVID-19 and with other vaccines varied per country. The largest reported change in the willingness to be vaccinated with Vaxzevria® and Jcovden® was observed in Denmark (61.2 %), while the willingness to be vaccinated with other COVID-19 vaccines changed most in Slovenia (30.4 %). The smallest decrease in willingness towards future vaccination against COVID-19 was reported in the Netherlands (20.9 %) contrasting with the largest decrease observed in Latvia (69.1 %). CONCLUSION: Knowledge about TTS seemed to have influenced the public's opinion in Europe resulting in less willingness to be vaccinated with Vaxzevria® and Jcovden®. Willingness for vaccination against COVID-19 with other vaccines and widespread use of vaccines to prevent other diseases also differed and seemed to be determined by the approaches taken by national health authorities when reacting to and communicating about COVID-19 vaccination risks. Further investigation of optimal risk communication strategies is warranted.

Prevalence of antidepressant use in Brazil: a systematic review with meta-analysis

Objectives: To estimate the prevalence of antidepressant use in Brazil. Methods: We conducted a systematic review with searches in MEDLINE, Embase, Scopus, LILACS, and SciELO up to May 2023. Two researchers independently selected studies, extracted data, and assessed the methodological quality. We pooled the prevalence of antidepressant use using meta-analyses of proportions (Freeman-Tukey transformation) and estimated heterogeneity by the I2 statistic. OR meta-analyses of antidepressant use by sex were calculated (men as reference) and between-study variation was explored by meta-regressions. Results: Out of 3,299 records retrieved, 23 studies published in 28 reports were included, with a total of 75,061 participants. The overall prevalence of antidepressant use was 4.0% (95%CI 2.7-5.6%; I2 = 98.5%). Use of antidepressants in the previous 3 days was higher in women (12.0%; 95%CI 9.5-15.1%; I2 = 0%) than men (4.6%; 95%CI 3.1-6.8%; I2 = 0%) (p < 0.001; OR = 2.82; 95%CI 1.72-4.62). Gender differences were particularly higher for antidepressant use in the previous year (women: 2.3%; 95%CI 1.6-3.1; I2 = 37.6% vs. men: 0.5%; 95%CI 0.2-1.0%; I2 = 0%, p < 0.001; OR = 4.18; 95%CI 2.10-8.30). Between-study variation in the overall prevalence of antidepressant use significantly increased with mean participant age (p = 0.035; residual I2 = 0%; regression coefficient = 0.003). Conclusion: Four out of every 100 Brazilians used antidepressants in this 3-decade assessment. Use increased with age and was more prevalent in women compared to men. Registration number: PROSPERO CRD42022345332.

Prevalence of antidepressant use in Brazil: a systematic review with meta-analysis.

OBJECTIVE: To estimate the prevalence of antidepressant use in Brazil. METHODS: We conducted a systematic review with searches in MEDLINE, Embase, Scopus, LILACS, and SciELO up to May 2023. Two researchers independently selected studies, extracted data and assessed the methodological quality. We combined the prevalence of antidepressant use using meta-analyses of proportions by Freeman-Tukey and estimated heterogeneity by I². Odds ratio (OR) meta-analyses of antidepressant use by sex were calculated (men as reference) and between-study variation was explored by meta-regressions. RESULTS: Out of 3,299 records, 23 studies published in 28 reports were included. The overall prevalence of antidepressant use was 4.0% (95%CI 2.7-5.6%; I2=98.5%). Use of antidepressants in the previous 3 days was higher in women (12.0%; 95%CI 9.5-15.1%; I2=0.0%) than men (4.6%; 95%CI 3.1-6.8%; I2=0.0%), p<0.001; OR=2.82; 95%CI 1.72-4.62. Gender differences were particularly higher for antidepressant use in the previous year (women: 2.3%; 95%CI 1.6-3.1; I2=37.6% versus men: 0.5%; 95%CI 0.2-1.0%; I2=0.0%, p<0.001; OR=4.18; 95%CI 2.10-8.30). Between-study variation in the overall prevalence of antidepressant use significantly increased with participants' mean age (p=0.035; residual I²=0.0%; regression coefficient=0.003). CONCLUSIONS: Four in every 100 Brazilians use antidepressants; use increased with age and was higher in women compared to men.