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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.


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Journal ArticleDOI
TL;DR: The use of modified weights within two-sample summary-data MR studies is proposed for accurately quantifying heterogeneity and detecting outliers in the presence of weak instruments.
Abstract: BACKGROUND Two-sample summary-data Mendelian randomization (MR) incorporating multiple genetic variants within a meta-analysis framework is a popular technique for assessing causality in epidemiology. If all genetic variants satisfy the instrumental variable (IV) and necessary modelling assumptions, then their individual ratio estimates of causal effect should be homogeneous. Observed heterogeneity signals that one or more of these assumptions could have been violated. METHODS Causal estimation and heterogeneity assessment in MR require an approximation for the variance, or equivalently the inverse-variance weight, of each ratio estimate. We show that the most popular 'first-order' weights can lead to an inflation in the chances of detecting heterogeneity when in fact it is not present. Conversely, ostensibly more accurate 'second-order' weights can dramatically increase the chances of failing to detect heterogeneity when it is truly present. We derive modified weights to mitigate both of these adverse effects. RESULTS Using Monte Carlo simulations, we show that the modified weights outperform first- and second-order weights in terms of heterogeneity quantification. Modified weights are also shown to remove the phenomenon of regression dilution bias in MR estimates obtained from weak instruments, unlike those obtained using first- and second-order weights. However, with small numbers of weak instruments, this comes at the cost of a reduction in estimate precision and power to detect a causal effect compared with first-order weighting. Moreover, first-order weights always furnish unbiased estimates and preserve the type I error rate under the causal null. We illustrate the utility of the new method using data from a recent two-sample summary-data MR analysis to assess the causal role of systolic blood pressure on coronary heart disease risk. CONCLUSIONS We propose the use of modified weights within two-sample summary-data MR studies for accurately quantifying heterogeneity and detecting outliers in the presence of weak instruments. Modified weights also have an important role to play in terms of causal estimation (in tandem with first-order weights) but further research is required to understand their strengths and weaknesses in specific settings.

225 citations

Journal ArticleDOI
TL;DR: The initial increased mortality for single men was no longer evident after adjustment for other risk factors, suggesting that single status in itself may not increase the risk, and future work should not assume that all unmarried men have similar mortality risks and must examine the life course of each subgroup to advance the understanding of the possible causal role of marital status in disease aetiology.
Abstract: STUDY OBJECTIVE--To determine the effect of marital status on mortality for men. In particular, to examine whether subgroups of unmarried men (widowed, single, and divorced/separated men) have a similar mortality to married men. DESIGN--Cohort study. SETTING--Whitehall civil service, London, between 1967 and 1969. PARTICIPANTS--A total of 18,403 men aged 40-64 years with 18 years' follow up. MEASUREMENTS AND MAIN RESULTS--Cause-specific mortality rates and risk factors at baseline were determined. Overall mortality was greater for all groups of unmarried men. Patterns of mortality were different in the subgroups of unmarried men. Widowed men had a significantly greater risk of dying from ischaemic heart disease (relative risk (RR) 1.46, 95% confidence interval (CI) 1.08, 1.97) which persisted after exclusion of deaths that occurred in the first two years. Divorced men had greater cancer mortality (RR 1.49; 95% CI 1.06, 2.10) that could not be explained simply by their greater consumption of cigarettes. The initial increased mortality for single men was no longer evident after adjustment for other risk factors, suggesting that single status in itself may not increase the risk. The risk for single men may have been underestimated, however, by over adjustment for possible intermediary factors. CONCLUSIONS--Previous studies, which have examined total mortality only or have grouped all unmarried men, have masked interesting differences in the cause of death between subgroups of unmarried men. The extent to which the findings are explicable by psychosocial factors or the role of other environmental factors, which may also differ in relation to marital status, is unclear. Future work should not assume that all unmarried men have similar mortality risks and must examine the life course of each subgroup to advance our understanding of the possible causal role of marital status in disease aetiology.

222 citations

Journal ArticleDOI
TL;DR: It is premature to consider adiponectin as a root for vascular disease in women despite its association with insulin resistance and diabetes, and additional prospective studies are required to determine whether there is a true sex difference in the effect of adip on CHD.
Abstract: Context: Low adiponectin levels predict type 2 diabetes, and one prospective study in men reported its independent prediction of vascular events. Many observers thus already consider adiponectin to be a major part of the “common soil” underpinning diabetes and vascular disease. Objective: The objective of this study was to assess the association between adiponectin and incident coronary heart disease (CHD) risk in the British Women’s Heart and Health Study. Design: This was a prospective (4 yr) case (n = 167) control (n = 334) study nested within the 4286 women in British Women’s Heart and Health Study. Setting: The study was performed in a primary care setting. Participants: The study consisted of women (n = 4286) randomly selected from 23 British towns between 1999 and 2001, who were 60–79 yr of age at baseline. Main Outcome Measures: Association of adiponectin with CHD risk factors and incident CHD events were the main outcome measures. Results: Among both cases and controls, adiponectin positively cor...

222 citations

Journal ArticleDOI
TL;DR: A meta-analysis of studies looking at the ALDH2 genotype and esophageal cancer found that risk was reduced among *2*2 homozygotes and increased among heterozygotes, providing strong evidence that alcohol intake increases the risk of esophagal cancer and individuals whose genotype results in markedly lower intake are thus protected.
Abstract: Mendelian randomization, the use of common polymorphisms as surrogates for measuring exposure levels in epidemiologic studies, provides one method of assessing the causal nature of some environmental exposures. This can be illustrated by looking at the association between the ALDH2 polymorphism and esophageal cancer. Alcohol drinking is considered a risk factor for esophageal cancer, and exposure to high levels of acetaldehyde, the principal metabolite of alcohol, may be responsible for the increased cancer risk. The ability to metabolize acetaldehyde is encoded by the ALDH2 gene, which is polymorphic in some populations. The ALDH2*2 allele produces an inactive protein subunit, which is unable to metabolize acetaldehyde. An individual's genotype at this locus may influence their esophageal cancer risk through two mechanisms, first through influencing alcohol intake and second through influencing acetaldehyde levels. We have carried out a meta-analysis of studies looking at the ALDH2 genotype and esophageal cancer and found that risk was reduced among *2*2 homozygotes [odds ratio (OR), 0.36; 95% confidence interval (95% CI), 0.16-0.80] and increased among heterozygotes (OR, 3.19; 95% CI, 1.86-5.47) relative to *1*1 homozygotes. This provides strong evidence that alcohol intake increases the risk of esophageal cancer and individuals whose genotype results in markedly lower intake, because they have an adverse reaction to alcohol are thus protected. This meta-analysis also provides evidence that acetaldehyde plays a carcinogenic role in esophageal cancer. The two different processes operating as a result of the ALDH2 genotype have implications for the interpretation of studies using the Mendelian randomization paradigm.

218 citations


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Journal ArticleDOI
04 Sep 2003-BMJ
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

Journal ArticleDOI
13 Sep 1997-BMJ
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

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
18 Oct 2011-BMJ
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