Choosing a method to reduce selection bias: A tool for researchers

Selection bias is well known to affect surveys and epidemiological studies. There have been numerous methods proposed to reduce its effects, so many that researchers may be unclear which method is most suitable for their study; the wide choice may even deter some researchers, for fear of choosing a sub-optimal approach. We propose a straightforward tool to inform researchers of the most promising methods available to reduce selection bias and to assist the search for an appropriate method given their study design and details. We demonstrate the tool using three exam- ples where selection bias may occur; the tool quickly eliminates inappropriate methods and guides the researcher towards those to consider implementing. If more studies con- sider selection bias and adopt methods to reduce it, valuable time and resources will be saved, and should lead to more focused research towards disease prevention or cure

The Authors Respond

Although the studies highlighted in Kinlen and Peto’s letter describe situations they take to be “national in scope”, none of these adopted the ‘region-wide’ analysis we recommend. Rather, these studies have focussed on rural areas with small populations experiencing extreme levels of inward-migration that had been selected from larger regions/nation states. To definitively avoid bias, our study points to the need for comparisons of areas with varying levels of inward migration, either by comparing all areas within an entire region/nation state or random subsets thereof

BβArg448Lys polymorphism is associated with altered fibrin clot structure and fibrinolysis in type 2 diabetes

Both type 2 diabetes (T2DM) and Bβ448Lys variant of fibrinogen are associated with dense fibrin clots, impaired fibrinolysis and increased cardiovascular risk. It was our objective to investigate whether BβArg448Lys adds to vascular risk by modulating fibrin network structure and/or fibrinolysis in diabetes. The primary aim was to study effects of BβArg448Lys on fibrin network characteristics in T2DM. Secondary aims investigated interactions between gender and BβArg448Lys substitution in relation to fibrin clot properties and vascular disease. Genotyping for BβArg448Lys and dynamic clot studies were carried out on 822 T2DM patients enrolled in the Edinburgh Type 2 Diabetes Study. Turbidimetric assays of individual plasma samples analysed fibrin clot characteristics with additional experiments conducted on clots made from purified fibrinogen, further examined by confocal and electron microscopy. Plasma clot lysis time in Bβ448Lys was longer than Bβ448Arg variant (mean ± SD; 763 ± 322 and 719 ± 351 seconds [s], respectively; p<0.05). Clots made from plasma-purified fibrinogen of individuals with Arg/Arg, Arg/Lys and Lys/Lys genotypes showed differences in fibre thickness (46.75 ± 8.07, 38.40 ± 6.04 and 25 ± 4.99 nm, respectively; p<0.001) and clot lysis time (419 ± 64, 442 ± 87 and 517 ± 65 s, respectively; p=0.02), directly implicating the polymorphism in the observed changes. Women with Bβ448Lys genotype had increased risk of cerebrovascular events and were younger compared with Bβ448Arg variant (67.2 ± 4.0 and 68.2 ± 4.4 years, respectively; p=0.035). In conclusion, fibrinogen Bβ448Lys variant is associated with thrombotic fibrin clots in diabetes independently of traditional risk factors. Prospective studies are warranted to fully understand the role of BβArg448Lys in predisposition to vascular ischaemia in T2DM with the potential to develop individualised antithrombotic management strategies

Adaptation of Chain Event Graphs for use with Case-Control Studies in Epidemiology

Case-control studies are used in epidemiology to try to uncover the causes of diseases, but are a retrospective study design known to suffer from non-participation and recall bias, which may explain their decreased popularity in recent years. Traditional analyses report usually only the odds ratio for given exposures and the binary disease status. Chain event graphs are a graphical representation of a statistical model derived from event trees which have been developed in artificial intelligence and statistics, and only recently introduced to the epidemiology literature. They are a modern Bayesian technique which enable prior knowledge to be incorporated into the data analysis using the agglomerative hierarchical clustering algorithm, used to form a suitable chain event graph. Additionally, they can account for missing data and be used to explore missingness mechanisms. Here we adapt the chain event graph framework to suit scenarios often encountered in case-control studies, to strengthen this study design which is time and financially efficient. We demonstrate eight adaptations to the graphs, which consist of two suitable for full case-control study analysis, four which can be used in interim analyses to explore biases, and two which aim to improve the ease and accuracy of analyses. The adaptations are illustrated with complete, reproducible, fully-interpreted examples, including the event tree and chain event graph. Chain event graphs are used here for the first time to summarise non-participation, data collection techniques, data reliability, and disease severity in case-control studies. We demonstrate how these features of a case-control study can be incorporated into the analysis to provide further insight, which can help to identify potential biases and lead to more accurate study results

Bond percolation on isoradial graphs: criticality and universality

In an investigation of percolation on isoradial graphs, we prove the criticality of canonical bond percolation on isoradial embeddings of planar graphs, thus extending celebrated earlier results for homogeneous and inhomogeneous square, triangular, and other lattices. This is achieved via the star-triangle transformation, by transporting the box-crossing property across the family of isoradial graphs. As a consequence, we obtain the universality of these models at the critical point, in the sense that the one-arm and 2j-alternating-arm critical exponents (and therefore also the connectivity and volume exponents) are constant across the family of such percolation processes. The isoradial graphs in question are those that satisfy certain weak conditions on their embedding and on their track system. This class of graphs includes, for example, isoradial embeddings of periodic graphs, and graphs derived from rhombic Penrose tilings.Comment: In v2: extended title, and small changes in the tex

Dose dependency of iatrogenic glucocorticoid excess and adrenal insufficiency and mortality: a cohort study in England

Context: Adrenal insufficiency and Cushing’s syndrome are known adverse events of glucocorticoids. However, no population estimates of dose-related risks are available. Objective: To investigate dose-related risks of adrenal dysfunction and death in adults with six chronic inflammatory diseases treated with oral glucocorticoids. Design and setting: Retrospective record-linkage open-cohort study spanning primary and hospital care in England. Patients: 70,638 people oral glucocorticoid-users and 41,166 non-users aged ≥18 years registered in 389 practices in 1998-2017. Main outcome measures: Incidence rates and hazard ratios (HRs) of diagnosed adrenal dysfunction and death. Results: During a median follow-up of 5.5 years, 183 patients had glucocorticoid-induced adrenal insufficiency and 248 glucocorticoid-induced Cushing’s syndrome. A total of 22,317 (31.6%) and 7,544 (18.3%) deaths occurred amongst glucocorticoid users and non-users, respectively. Incidence of all outcomes increased with higher current daily and cumulative doses. For adrenal insufficiency, the increases in HRs were of 1.07 (95% CI 1.04-1.09) for every increase of 5mg per day and of 2.25 (95% CI 2.15-2.35) per 1000mg of cumulative prednisolone-equivalent dose over the past year. The respective increases in HRs for Cushing’s syndrome were of 1.09 (95% CI 1.08-1.11) and 2.31 (95% CI 2.23-2.40) and for mortality of 1.26 (95% CI 2.24-1.28) and 2.05 (95% CI 2.04-2.06). Conclusion: We report a high glucocorticoid dose-dependent increased risk of adrenal adverse events and death. The low observed absolute risk of adrenal insufficiency highlights a potential lack of awareness, and a need for increased physician and patient education about the risks of adrenal dysfunction induced by glucocorticoids

Sinter formation during directed energy deposition of titanium alloy powders

During directed energy deposition (DED) additive manufacturing, powder agglomeration and sintering can occur outside of the melt pool when using titanium alloy powders. Using in situ synchrotron radiography we investigate the mechanisms by which sintering of Ti6242 powder occurs around the pool, performing a parametric study to determine the influence of laser power and stage traverse speed on sinter build-up. The results reveal that detrimental sinter can be reduced using a high laser power or increased stage traverse speed, although the latter also reduces deposition layer thickness. The mechanism of sinter formation during DED was determined to be in-flight heating of the powder particles in the laser beam. Calculations of particle heating under the processing conditions explored in this study confirm that powder particles can reasonably exceed 700 °C, the threshold for Ti surface oxide dissolution, and thus the powder is prone to sintering if not incorporated into the melt pool. The build-up of sinter powder layer on deposit surfaces led to lack of fusion pores. To mitigate sinter formation and its detrimental effects on DED component quality, it is essential that the powder delivery spot area is smaller than the melt pool, ensuring most powder lands in the melt pool

Network inference analysis identifies an APRR2-like gene linked to pigment accumulation in tomato and pepper fruits

Carotenoids represent some of the most important secondary metabolites in the human diet, and tomato (Solanum lycopersicum) is a rich source of these health-promoting compounds. In this work, a novel and fruit-related regulator of pigment accumulation in tomato has been identified by artificial neural network inference analysis and its function validated in transgenic plants. A tomato fruit gene regulatory network was generated using artificial neural network inference analysis and transcription factor gene expression profiles derived from fruits sampled at various points during development and ripening. One of the transcription factor gene expression profiles with a sequence related to an Arabidopsis (Arabidopsis thaliana) ARABIDOPSIS PSEUDO RESPONSE REGULATOR2-LIKE gene (APRR2-Like) was up-regulated at the breaker stage in wild-type tomato fruits and, when overexpressed in transgenic lines, increased plastid number, area, and pigment content, enhancing the levels of chlorophyll in immature unripe fruits and carotenoids in red ripe fruits. Analysis of the transcriptome of transgenic lines overexpressing the tomato APPR2-Like gene revealed up-regulation of several ripening-related genes in the overexpression lines, providing a link between the expression of this tomato gene and the ripening process. A putative ortholog of the tomato APPR2-Like gene in sweet pepper (Capsicum annuum) was associated with pigment accumulation in fruit tissues. We conclude that the function of this gene is conserved across taxa and that it encodes a protein that has an important role in ripening