7 research outputs found
A systematic review of randomisation method use in RCTs and association of trial design characteristics with method selection
Background: When conducting a randomised controlled trial, there exist many different methods to allocate participants, and a vast array of evidence-based opinions on which methods are the most effective at doing this, leading to differing use of these methods. There is also evidence that study characteristics affect the performance of these methods, but it is unknown whether the study design affects researchers’ decision when choosing a method. Methods: We conducted a review of papers published in five journals in 2019 to assess which randomisation methods are most commonly being used, as well as identifying which aspects of study design, if any, are associated with the choice of randomisation method. Randomisation methodology use was compared with a similar review conducted in 2014. Results: The most used randomisation method in this review is block stratification used in 162/330 trials. A combination of simple, randomisation, block randomisation, stratification and minimisation make up 318/330 trials, with only a small number of more novel methods being used, although this number has increased marginally since 2014. More complex methods such as stratification and minimisation seem to be used in larger multicentre studies. Conclusions: Within this review, most methods used can be classified using a combination of simple, block stratification and minimisation, suggesting that there is not much if any increase in the uptake of newer more novel methods. There seems to be a noticeable polarisation of method use, with an increase in the use of simple methods, but an increase in the complexity of more complex methods, with greater numbers of variables included in the analysis, and a greater number of strata
Choosing and evaluating randomisation methods in clinical trials: a qualitative study
Background: There exist many different methods of allocating participants to treatment groups during a randomised controlled trial. Although there is research that explores trial characteristics that are associated with the choice of method, there is still a lot of variety in practice not explained. This study used qualitative methods to explore more deeply the motivations behind researchers’ choice of randomisation, and which features of the method they use to evaluate the performance of these methods. Methods: Data was collected from online focus groups with various stakeholders involved in the randomisation process. Focus groups were recorded and then transcribed verbatim. A thematic analysis was used to analyse the transcripts. Results: Twenty-five participants from twenty clinical trials units across the UK were recruited to take part in one of four focus groups. Four main themes were identified: how randomisation methods are selected; researchers’ opinions of the different methods; which features of the method are desirable and ways to measure method features. Most researchers agree that the randomisation method should be selected based on key trial characteristics; however, for many, a unit standard is in place. Opinions of methods were varied with some participants favouring stratified blocks and others favouring minimisation. This was generally due to researchers’ perception of the effect these methods had on balance and predictability. Generally, predictability was considered more important than balance as adjustments cannot be made for it; however, most researchers felt that the importance of these two methods was dependent on the design of the study. Balance is usually evaluated by tabulating variables by treatment arm and looking for perceived imbalances, predictability was generally considered much harder to measure, partly due to differing definitions. Conclusion: There is a wide variety in practice on how randomisation methods are selected and researcher’s opinions on methods. The difference in practice observed when looking at randomisation method selection can be explained by a difference in unit practice, and also by a difference in researchers prioritisation of balance and predictability. The findings of this study show a need for more guidance on randomisation method selection
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COVID-19-related Genes in Sputum Cells in Asthma. Relationship to Demographic Features and Corticosteroids.
Rationale: Coronavirus disease (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). ACE2 (angiotensin-converting enzyme 2), and TMPRSS2 (transmembrane protease serine 2) mediate viral infection of host cells. We reasoned that differences in ACE2 or TMPRSS2 gene expression in sputum cells among patients with asthma may identify subgroups at risk for COVID-19 morbidity.Objectives: To determine the relationship between demographic features and sputum ACE2 and TMPRSS2 gene expression in asthma.Methods: We analyzed gene expression for ACE2 and TMPRSS2, and for ICAM-1 (intercellular adhesion molecule 1) (rhinovirus receptor as a comparator) in sputum cells from 330 participants in SARP-3 (Severe Asthma Research Program-3) and 79 healthy control subjects.Measurements and Main Results: Gene expression of ACE2 was lower than TMPRSS2, and expression levels of both genes were similar in asthma and health. Among patients with asthma, male sex, African American race, and history of diabetes mellitus were associated with higher expression of ACE2 and TMPRSS2. Use of inhaled corticosteroids (ICS) was associated with lower expression of ACE2 and TMPRSS2, but treatment with triamcinolone acetonide did not decrease expression of either gene. These findings differed from those for ICAM-1, where gene expression was increased in asthma and less consistent differences were observed related to sex, race, and use of ICS.Conclusions: Higher expression of ACE2 and TMPRSS2 in males, African Americans, and patients with diabetes mellitus provides rationale for monitoring these asthma subgroups for poor COVID-19 outcomes. The lower expression of ACE2 and TMPRSS2 with ICS use warrants prospective study of ICS use as a predictor of decreased susceptibility to SARS-CoV-2 infection and decreased COVID-19 morbidity
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A common polymorphism in the Intelectin-1 gene influences mucus plugging in severe asthma
By incompletely understood mechanisms, type 2 (T2) inflammation present in the airways of severe asthmatics drives the formation of pathologic mucus which leads to airway mucus plugging. Here we investigate the molecular role and clinical significance of intelectin-1 (ITLN-1) in the development of pathologic airway mucus in asthma. Through analyses of human airway epithelial cells we find that ITLN1 gene expression is highly induced by interleukin-13 (IL-13) in a subset of metaplastic MUC5AC+ mucus secretory cells, and that ITLN-1 protein is a secreted component of IL-13-induced mucus. Additionally, we find ITLN-1 protein binds the C-terminus of the MUC5AC mucin and that its deletion in airway epithelial cells partially reverses IL-13-induced mucostasis. Through analysis of nasal airway epithelial brushings, we find that ITLN1 is highly expressed in T2-high asthmatics, when compared to T2-low children. Furthermore, we demonstrate that both ITLN-1 gene expression and protein levels are significantly reduced by a common genetic variant that is associated with protection from the formation of mucus plugs in T2-high asthma. This work identifies an important biomarker and targetable pathways for the treatment of mucus obstruction in asthma
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A common polymorphism in the Intelectin-1 gene influences mucus plugging in severe asthma.
Funder: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)By incompletely understood mechanisms, type 2 (T2) inflammation present in the airways of severe asthmatics drives the formation of pathologic mucus which leads to airway mucus plugging. Here we investigate the molecular role and clinical significance of intelectin-1 (ITLN-1) in the development of pathologic airway mucus in asthma. Through analyses of human airway epithelial cells we find that ITLN1 gene expression is highly induced by interleukin-13 (IL-13) in a subset of metaplastic MUC5AC+ mucus secretory cells, and that ITLN-1 protein is a secreted component of IL-13-induced mucus. Additionally, we find ITLN-1 protein binds the C-terminus of the MUC5AC mucin and that its deletion in airway epithelial cells partially reverses IL-13-induced mucostasis. Through analysis of nasal airway epithelial brushings, we find that ITLN1 is highly expressed in T2-high asthmatics, when compared to T2-low children. Furthermore, we demonstrate that both ITLN-1 gene expression and protein levels are significantly reduced by a common genetic variant that is associated with protection from the formation of mucus plugs in T2-high asthma. This work identifies an important biomarker and targetable pathways for the treatment of mucus obstruction in asthma
The genome sequence of the filamentous fungus Neurospora crassa
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