The Application of Genetic Risk Scores in Rheumatic Diseases: A Perspective

\ua9 2023 by the authors.Modest effect sizes have limited the clinical applicability of genetic associations with rheumatic diseases. Genetic risk scores (GRSs) have emerged as a promising solution to translate genetics into useful tools. In this review, we provide an overview of the recent literature on GRSs in rheumatic diseases. We describe six categories for which GRSs are used: (a) disease (outcome) prediction, (b) genetic commonalities between diseases, (c) disease differentiation, (d) interplay between genetics and environmental factors, (e) heritability and transferability, and (f) detecting causal relationships between traits. In our review of the literature, we identified current lacunas and opportunities for future work. First, the shortage of non-European genetic data restricts the application of many GRSs to European populations. Next, many GRSs are tested in settings enriched for cases that limit the transferability to real life. If intended for clinical application, GRSs are ideally tested in the relevant setting. Finally, there is much to elucidate regarding the co-occurrence of clinical traits to identify shared causal paths and elucidate relationships between the diseases. GRSs are useful instruments for this. Overall, the ever-continuing research on GRSs gives a hopeful outlook into the future of GRSs and indicates significant progress in their potential applications

The application of genetic risk scores in rheumatic diseases: a perspective

Modest effect sizes have limited the clinical applicability of genetic associations with rheumatic diseases. Genetic risk scores (GRSs) have emerged as a promising solution to translate genetics into useful tools. In this review, we provide an overview of the recent literature on GRSs in rheumatic diseases. We describe six categories for which GRSs are used: (a) disease (outcome) prediction, (b) genetic commonalities between diseases, (c) disease differentiation, (d) interplay between genetics and environmental factors, (e) heritability and transferability, and (f) detecting causal relationships between traits. In our review of the literature, we identified current lacunas and opportunities for future work. First, the shortage of non-European genetic data restricts the application of many GRSs to European populations. Next, many GRSs are tested in settings enriched for cases that limit the transferability to real life. If intended for clinical application, GRSs are ideally tested in the relevant setting. Finally, there is much to elucidate regarding the co-occurrence of clinical traits to identify shared causal paths and elucidate relationships between the diseases. GRSs are useful instruments for this. Overall, the ever-continuing research on GRSs gives a hopeful outlook into the future of GRSs and indicates significant progress in their potential applications.Pathophysiology and treatment of rheumatic disease

Principles of clinical and economic analysis of antimicrobial drugs

In light of rising costs in the health care system and the introduction of innovative but expensive technologies, decision makers are looking for reliable methods to assess their cost-effectiveness. To this end, a comprehensive assessment of medical technology is carried out, including the analysis of information on its comparative clinical efficacy and safety, as well as an assessment of the economic consequences of its implementation. One of the most important features of clinical and economic studies of antimicrobials is the ability of infectious agents to acquire resistance to therapy, which fundamentally changes their effectiveness, and, consequently, the clinical and economic feasibility of use over time. Taking into account the risks of resistance as a criterion of effectiveness in pharmacoeconomical studies of antimicrobial drugs is an important factor affecting the feasibility of inclusion of drugs in the restrictive lists. At the same time, this criterion remains underutilized

Socio-economic burden of COVID-19 in the Russian Federation

Purpose. Assessment of the socio-economic burden of COVID-19 in the Russian Federation (RF). Materials and methods. Identification and assessment of direct medical, direct non-medical costs, as well as indirect costs associated with the development of the coronavirus infection epidemic. When calculating the socio-economic burden, the prevalence-based calculation approach was chosen. The sources of data on the epidemiology of the disease were data from the Ministry of Health and data from the Government of the Russian Federation. Results. The socio-economic burden of COVID-19 in the Russian Federation will amount to 4.6 trillion rubles ($71.1 billion) or 4 % from GDP. In the cost structure, more than half of the costs are direct non-medical expenses (58.62 %), indirect expenses due to GDP losses are 40.65 %, direct medical expenses are only less than 1 % (0.74 %). The results of the sensitivity analysis showed that the extension of the self-isolation period from 1 month to 1.5 and 2 months will lead to an increase in the share of indirect expenses from 40.65 % (1 month) to 56.08 (1.5 months) and 67.76 % (2 months) for all expenses in connection with the COVID-19 epidemic. At the same time, the socio-economic burden of COVID-19 will amount to 6.2 and 8.5 trillion rubles, respectively. Conclusions. The epidemic of a novel coronavirus infection will lead to great economic losses in the Russian society

Approaches to Assessing the Safety of Medicines during the COVID-19 Pandemic Using the Example of Azithromycin

Most of the medicines used to treat the novel coronavirus infection (COVID-19) are either approved under an accelerated procedure or not approved for the indication. Consequently, their safety requires special attention.The aim of the study was to review methodological approaches to collecting data on the safety of medicines, using COVID-19 treatment regimens involving azithromycin as a case study.Materials and methods: PubMed® (MEDLINE), Scopus, eLIBRARY, and Cyberleninka databases were searched for publications on azithromycin as part of combination therapy for COVID-19 in 2020–2021. Search queries included names of the medicinal product or its pharmacotherapeutic group and words describing adverse drug reactions (ADRs) during treatment.Results: the analysis included 7 publications presenting the results of studies covering the use of azithromycin as part of COVID-19 combination therapy in more than 4000 patients. Most commonly, the patients receiving COVID-19 therapy including azithromycin developed cardiovascular ADRs (up to 30% of azithromycin prescription cases). In 3 of the analysed publications, safety information was collected through spontaneous reporting and active identification based on the findings of laboratory and instrumental investigations performed during the clinical studies; in other 3, only spontaneous reports were used; and in the last one, ADR database information was studied.Conclusion: currently, information on ADRs associated with the use of medicines is mainly gathered via spontaneous reporting. Direct sourcing of information on personal experiences with a certain product from patients, among other means through social media analysis, opens a promising direction towards the improvement of existing approaches to collecting safety data

Socioeconomic and global burden of COVID-19

Relevance. Assessment of the burden of disease provides information on the economic consequences of the disease, allows you to assess the social significance, identify areas that require additional clinical and economic research, changes in methodological approaches to the organization of measures for the prevention, early detection and treatment of diseases.The aim. Assessment of the socioeconomic and global burden of COVID-19 in the Russian Federation (RF).Materials and methods. Identification and assessment of direct medical, direct non-medical, and indirect costs associated with the development of the coronavirus epidemic. When calculating the socioeconomic burden, the variant of calculations was chosen taking into account the prevalence of the disease. The sources of data on the epidemiology of the disease were data from the Ministry of Health and data from the Government of the RF.Results. The socioeconomic burden of COVID-19 in 2020 in the RF amounted to about 5.4 trillion rubles (5 % of nominal GDP in 2020) and was largely due to indirect costs due to GDP losses due to a 1.5-month period of self-isolation. The estimated global burden of disease is more than 4 million YLLs globally, of which in the RF 2,486.30 among men and 1,378.22 YLL among women.Conclusion. The epidemic of the new coronavirus infection has led to colossal economic losses in Russian society. The data presented underscore not only the clinical, but also the economic importance of investing in the development of strategies for the treatment and prevention of new coronavirus infection

Pharmacoeconomics modes of antibiotic therapy of uncomplicated community-acquired acute pyelonephritis in a multidisciplinary hospital

Introduction. Despite the high level of resistance of E.coli as the main causative agent of urinary tract infections, fluoroquinolones are among the most frequently used antimicrobial agents in empirical therapy of uroinfections.Aim. Clinical and economic evaluation of the effectiveness of different antibacterial strategies of community-acquired uncomplicated acute pyelonephritis with the predicted dynamics of resistance of E.coli as the main causative agent of uroinfections.Materials and methods. Te calculations take into account the literature data on the effectiveness and safety of the starting regime of antibacterial therapy of uncomplicated pyelonephritis with cephalosporins of the 3rd generation, fluoroquinolones, aminoglycosides and carbapenems in terms of hospital specialized medical care. Te model of «decision tree» is constructed. A list of direct and indirect costs was compiled, on the basis of which the cost of 1 case of acute uncomplicated pyelonephritis therapy for each strategy of antibacterial therapy was calculated. Te «cost-effectiveness analysis» and budget impact analysis were performed.Results. Te cost of 1 case of therapy with acute uncomplicated pyelonephritis gentamicin was the lowest in comparison with alternative strategies (33 679,89 rubles). Cost-effectiveness analysis showed that the strategy of antibacterial therapy of acute uncomplicated pyelonephritis with gentamicin dominated alternative strategies: at lower costs, it was also more effective.Summary. For a more accurate calculation of clinical and economic efciency of antimicrobial agents it is necessary to monitor the dynamics of the resistance level in the territory of the Russian Federation

Систематический обзор данных реальной клинической практики при COVID-19: неинтервенционные исследования

Introduction. As defined by the Food and Drug Administration, real-world data (RWD) is data related to a patient's health and/or health care delivery, usually collected from various sources as part of real-world clinical practice research.Objective: to describe the feasible and the most sought-after designs of non-interventional real-world clinical practice trials that provide evidence for the efficacy and safety of drug administration in the therapy of novel coronavirus infection.Material and methods. A search strategy for the terms “COVID-19 AND real-life”, “COVID-19 AND real-data”, “COVID-19 AND real-world” was developed to extract articles published between December 1, 2020 and March 12, 2021 from the databases: PubMed/MEDLINE, the Cochrane Database of Systematic Reviews, and the ClinicalTrials.gov database.Results. The search yielded 137 non-repetitive articles, 32 of them were included in the review. All randomized clinical trials (pragmatic and simplified large ones), studies of the effectiveness of laboratory diagnostic methods, medical triage, social distancing and other sanitary and epidemiological measures to cope with the epidemic were excluded.Conclusion. High-quality, non-randomized RWD studies can enhance the external validity of registration randomized clinical trials by complementing them with a broader range of indicators, which is essential in supporting medical and public health decision-making in the COVID-19 pandemic. Введение. По определению, данному Food and Drug Administration, данные реального мира (англ. real-world data, RWD) – это данные, относящиеся к состоянию здоровья пациента и/или оказанию медицинской помощи, обычно собираемые из различных источников в рамках исследований реальной клинической практики.Цель: описание возможных и наиболее востребованных дизайнов неинтервенционных исследований реальной клинической практики, которые позволяют получить сведения об эффективности и безопасности применения лекарственных средств в терапии новой коронавирусной инфекции.Материал и методы. Для извлечения статей, опубликованных с 1 декабря 2020 г., по 12 марта 2021 г., в рамках литературного обзора разработана стратегия поиска по терминам “COVID-19 AND real-life”, “COVID-19 AND real-data”, “COVID-19 AND real-world” в базе данных медицинских публикаций PubMed/MEDLINE, Кокрейновской базе данных систематических обзоров, а также базе данных клинических исследований СlinicalТrials.gov.Результаты. Было найдено 137 публикаций, из них 32 статьи вошли в обзор. Исключены все рандомизированные клинические испытания (прагматические и упрощенные большие), исследования эффективности методов лабораторной диагностики, медицинской сортировки, социального дистанцирования и других санитарно-эпидемиологических мер по сдерживанию эпидемии.Заключение. Высококачественные нерандомизированные исследования в рамках RWD способны усилить внешнюю валидность регистрационных рандомизированных клинических испытаний, дополнив их более широким спектром показателей, что имеет существенное значение при поддержке принятия решений в области медицины и общественного здравоохранения в условиях пандемии COVID-19.

High Levels of Sediment Contamination Have Little Influence on Estuarine Beach Fish Communities

While contaminants are predicted to have measurable impacts on fish assemblages, studies have rarely assessed this potential in the context of natural variability in physico-chemical conditions within and between estuaries. We investigated links between the distribution of sediment contamination (metals and PAHs), physico-chemical variables (pH, salinity, temperature, turbidity) and beach fish assemblages in estuarine environments. Fish communities were sampled using a beach seine within the inner and outer zones of six estuaries that were either heavily modified or relatively unmodified by urbanization and industrial activity. All sampling was replicated over two years with two periods sampled each year. Shannon diversity, biomass and abundance were all significantly higher in the inner zone of estuaries while fish were larger on average in the outer zone. Strong differences in community composition were also detected between the inner and outer zones. Few differences were detected between fish assemblages in heavily modified versus relatively unmodified estuaries despite high concentrations of sediment contaminants in the inner zones of modified estuaries that exceeded recognized sediment quality guidelines. Trends in species distributions, community composition, abundance, Shannon diversity, and average fish weight were strongly correlated to physico-chemical variables and showed a weaker relationship to sediment metal contamination. Sediment PAH concentrations were not significantly related to the fish assemblage. These findings suggest that variation in some physico-chemical factors (salinity, temperature, pH) or variables that co-vary with these factors (e.g., wave activity or grain size) have a much greater influence on this fish assemblage than anthropogenic stressors such as contamination

Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes?

Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change – particularly changes in climate and resource exploitation. In the absence of direct biological and ecological information for many marine species, scientists are increasingly using spatially-explicit, predictive-modeling approaches. Through the improved access to multibeam sonar and underwater video technology these models provide spatial predictions of the most suitable regions for an organism at resolutions previously not possible. However, sensible-looking, well-performing models can provide very different predictions of distribution depending on which occurrence dataset is used. To examine this, we construct species distribution models for nine temperate marine sedentary fishes for a 25.7 km2 study region off the coast of southeastern Australia. We use generalized linear model (GLM), generalized additive model (GAM) and maximum entropy (MAXENT) to build models based on co-located occurrence datasets derived from two underwater video methods (i.e. baited and towed video) and fine-scale multibeam sonar based seafloor habitat variables. Overall, this study found that the choice of modeling approach did not considerably influence the prediction of distributions based on the same occurrence dataset. However, greater dissimilarity between model predictions was observed across the nine fish taxa when the two occurrence datasets were compared (relative to models based on the same dataset). Based on these results it is difficult to draw any general trends in regards to which video method provides more reliable occurrence datasets. Nonetheless, we suggest predictions reflecting the species apparent distribution (i.e. a combination of species distribution and the probability of detecting it). Consequently, we also encourage researchers and marine managers to carefully interpret model predictions