Author
George Davey Smith
Other affiliations: Keele University, Western Infirmary, Health Science University ...read more
Bio: George Davey Smith is an academic researcher from University of Bristol. The author has contributed to research in topics: Population & Mendelian randomization. The author has an hindex of 224, co-authored 2540 publications receiving 248373 citations. Previous affiliations of George Davey Smith include Keele University & Western Infirmary.
Papers published on a yearly basis
Papers
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TL;DR: In this article, a nested case-control study of 176 initially nondiabetic men who developed diabetes during 5 years of follow-up, two controls were selected, one matched only for randomization date, treatment group, and clinic (loose controls) and the other matched additionally for fasting glucose and body mass index (tight controls).
Abstract: Few prospective data are available regarding the association of sex hormone-binding globulin (SHBG), testosterone, and the risk of developing diabetes. Stored fasting serum samples from participants enrolled in the Multiple Risk Factor Intervention Trial (MRFIT) at 22 different centers throughout the United States from December 1973 through February 1976 were used to perform a nested case-control study. For 176 initially nondiabetic men who developed diabetes during 5 years of follow-up, two controls were selected, one matched only for randomization date, treatment group, and clinic (loose controls) and the other matched additionally for fasting glucose and body mass index (tight controls). When cases were compared with loose controls, higher levels of fasting insulin and lower levels of total and free testosterone and SHBG were significantly associated with increased development of diabetes. However, when cases were compared with tightly matched controls, these associations weakened considerably. Low SHBG and testosterone may constitute part of the prediabetic state in men along with previously reported variables, such as higher glucose and insulin levels and obesity.
295 citations
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University of Bristol1, Hannover Medical School2, University of Copenhagen3, Erasmus University Rotterdam4, QIMR Berghofer Medical Research Institute5, Imperial College London6, University of Kiel7, Technische Universität München8, University of Pennsylvania9, University of Western Australia10, University of Basel11, University of Manchester12, VU University Amsterdam13, Karolinska Institutet14, Wellcome Trust Sanger Institute15, University of Geneva16, University of Oulu17, University of the East18, University of Washington19, University of Melbourne20, Ludwig Maximilian University of Munich21, University of Bonn22, Aarhus University23, Tartu University Hospital24, Statens Serum Institut25, University of Iowa26, Children's Hospital of Philadelphia27, King's College London28, Telethon Institute for Child Health Research29, Children's Medical Research Institute30, Swiss Tropical and Public Health Institute31, Norwegian Institute of Public Health32, Manchester Academic Health Science Centre33, Utrecht University34, Copenhagen University Hospital35, Karolinska University Hospital36, Sahlgrenska University Hospital37, Ontario Institute for Cancer Research38, St George's, University of London39, Medical Research Council40
TL;DR: A genome-wide association meta-analysis of affected individuals and controls and the ten most strongly associated new susceptibility loci examined underline the importance of both epidermal barrier function and immune dysregulation in atopic dermatitis pathogenesis.
Abstract: Atopic dermatitis (AD) is a commonly occurring chronic skin disease with high heritability. Apart from filaggrin (FLG), the genes influencing atopic dermatitis are largely unknown. We conducted a genome-wide association meta-analysis of 5,606 affected individuals and 20,565 controls from 16 population-based cohorts and then examined the ten most strongly associated new susceptibility loci in an additional 5,419 affected individuals and 19,833 controls from 14 studies. Three SNPs reached genome-wide significance in the discovery and replication cohorts combined, including rs479844 upstream of OVOL1 (odds ratio (OR) = 0.88, P = 1.1 × 10(-13)) and rs2164983 near ACTL9 (OR = 1.16, P = 7.1 × 10(-9)), both of which are near genes that have been implicated in epidermal proliferation and differentiation, as well as rs2897442 in KIF3A within the cytokine cluster at 5q31.1 (OR = 1.11, P = 3.8 × 10(-8)). We also replicated association with the FLG locus and with two recently identified association signals at 11q13.5 (rs7927894; P = 0.008) and 20q13.33 (rs6010620; P = 0.002). Our results underline the importance of both epidermal barrier function and immune dysregulation in atopic dermatitis pathogenesis.
294 citations
01 Jan 2012
293 citations
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TL;DR: In this paper, the structure of small copper precipitates in the α-Fe matrix has been investigated and it is shown that the precipitates have a twinned 9R close-packed structure, rather than the expected f.c.c structure.
Abstract: Conventional transmission electron microscopy (TEM) and high-resolution electron microscopy (HREM) experiments have been carried out on thermally-aged binary Fe 1·30 wt% Cu and ternary Fe 1·28 wt% Cu 1·43 wt.% Ni alloys to study the structure of small (7–15 nm) copper precipitates in the α-Fe matrix. The experiments show that the precipitates have a twinned 9R close-packed structure, rather than the expected f.c.c. structure. It is believed that this structure is generated initially by a martensitic transformation from the metastable b.c.c. phase.
292 citations
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TL;DR: Genetic epidemiology shows that the apparently protective effects of moderate alcohol intake against stroke are largely non-causal, and appears in this one study to have little net effect on the risk of myocardial infarction.
287 citations
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TL;DR: A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.
Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice?
Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis.
Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4
Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted?
A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …
45,105 citations
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TL;DR: Funnel plots, plots of the trials' effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials.
Abstract: Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews . Main outcome measure: Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. Results: In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution. Key messages Systematic reviews of randomised trials are the best strategy for appraising evidence; however, the findings of some meta-analyses were later contradicted by large trials Funnel plots, plots of the trials9 effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials Funnel plot asymmetry was found in 38% of meta-analyses published in leading general medicine journals and in 13% of reviews from the Cochrane Database of Systematic Reviews Critical examination of systematic reviews for publication and related biases should be considered a routine procedure
37,989 citations
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TL;DR: In this review the usual methods applied in systematic reviews and meta-analyses are outlined, and the most common procedures for combining studies with binary outcomes are described, illustrating how they can be done using Stata commands.
31,656 citations
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TL;DR: An Explanation and Elaboration of the PRISMA Statement is presented and updated guidelines for the reporting of systematic reviews and meta-analyses are presented.
Abstract: Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users.
Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions.
The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.
25,711 citations
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TL;DR: The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate.
Abstract: Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate
22,227 citations