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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.


Papers
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Journal ArticleDOI
TL;DR: Simulations quantified the risks of misinterpreting subgroup analyses as evidence of differential subgroup effects and the limited power of the interaction test in trials designed to detect overall treatment effects.

610 citations

Journal ArticleDOI
TL;DR: In simulations, it is shown that even modest influences on selection into, or attrition from, a study can generate biased and potentially misleading estimates of both phenotypic and genotypic associations.
Abstract: Large-scale cross-sectional and cohort studies have transformed our understanding of the genetic and environmental determinants of health outcomes. However, the representativeness of these samples may be limited-either through selection into studies, or by attrition from studies over time. Here we explore the potential impact of this selection bias on results obtained from these studies, from the perspective that this amounts to conditioning on a collider (i.e. a form of collider bias). Whereas it is acknowledged that selection bias will have a strong effect on representativeness and prevalence estimates, it is often assumed that it should not have a strong impact on estimates of associations. We argue that because selection can induce collider bias (which occurs when two variables independently influence a third variable, and that third variable is conditioned upon), selection can lead to substantially biased estimates of associations. In particular, selection related to phenotypes can bias associations with genetic variants associated with those phenotypes. In simulations, we show that even modest influences on selection into, or attrition from, a study can generate biased and potentially misleading estimates of both phenotypic and genotypic associations. Our results highlight the value of knowing which population your study sample is representative of. If the factors influencing selection and attrition are known, they can be adjusted for. For example, having DNA available on most participants in a birth cohort study offers the possibility of investigating the extent to which polygenic scores predict subsequent participation, which in turn would enable sensitivity analyses of the extent to which bias might distort estimates.

608 citations

Journal ArticleDOI
TL;DR: Available evidence does not strongly support an important causal relation between cannabis use by young people and psychosocial harm, but cannot exclude the possibility that such a relation exists, and the lack of evidence of robust causal relations prevents the attribution of public health detriments to illicit drug use.

598 citations

Journal ArticleDOI
22 Feb 1997-BMJ
TL;DR: Assessment of the influence of socioeconomic position over a lifetime on risk factors for cardiovascular disease, on morbidity, and on mortality from various causes found participants' social class at the time of screening was more strongly associated than the other social class indicators with mortality from cancer and from non-cardiovascular, non-cancer causes.
Abstract: OBJECTIVES: To assess the influence of socioeconomic position over a lifetime on risk factors for cardiovascular disease, on morbidity, and on mortality from various causes. DESIGN: Prospective observational study with 21 years of follow up. Social class was determined as manual or non-manual at three stages of participants' lives: from the social class of their father's job, the social class of their first job, and the social class of their job at the time of screening. A cumulative social class indicator was constructed, ranging from non-manual social class at all three stages of life to manual social class at all three stages. SETTING: 27 workplaces in the west of Scotland. PARTICIPANTS: 5766 men aged 35-64 at the time of examination. MAIN OUTCOME MEASURES: Prevalence and level of risk factors for cardiovascular disease; morbidity; and mortality from broad causes of death. RESULTS: From non-manual social class locations at all three life stages to manual at all stages there were strong positive trends for blood pressure, body mass index, current cigarette smoking, angina, and bronchitis. Inverse trends were seen for height, cholesterol concentration, lung function, and being an ex-smoker. 1580 men died during follow up. Age adjusted relative death rates in comparison with the men of non-manual social class locations at all three stages of life were 1.29 (95% confidence interval 1.08 to 1.56) in men of two non-manual and one manual social class; 1.45 (1.21 to 1.73) in men of two manual and one non-manual social class; and 1.71 (1.46 to 2.01) in men of manual social class at all three stages. Mortality from cardiovascular disease showed a similar graded association with cumulative social class. Mortality from cancer was mainly raised among men of manual social class at all three stages. Adjustment for a wide range of risk factors caused little attenuation in the association of cumulative social class with mortality from all causes and from cardiovascular disease; greater attenuation was seen in the association with mortality from non-cardiovascular, non-cancer disease. Fathers having a manual [corrected] occupation was strongly associated with mortality from cardiovascular disease: relative rate 1.41 (1.15 to 1.72). Participants' social class at the time of screening was more strongly associated than the other social class indicators with mortality from cancer and from non-cardiovascular, non-cancer causes. CONCLUSIONS: Socioeconomic factors acting over the lifetime affect health and risk of premature death. The relative importance of influences at different stages varies for the cause of death. Studies with data on socioeconomic circumstances at only one stage of life are inadequate for fully elucidating the contribution of socioeconomic factors to health and mortality risk.

598 citations

Journal ArticleDOI
TL;DR: There were significant and similar increases in arterial pressure and circulating catecholamine concentrations following laryngoscopy with or without intubation, however, Intubation was associated with significant increases in heart rate which did not occur in the larygoscopy-only group.
Abstract: The catecholamine and cardiovascular responses to laryngoscopy alone have been compared with those following laryngoscopy and intubation in 24 patients allocated randomly to each group. Following induction with fentanyl and thio-pentone, atracurium was administered and artificial ventilation undertaken via a face mask for 2 min with 67% nitrous oxide in oxygen. Following laryngoscopy, the vocal cords were visualized for 10 s. In one group of patients, ventilation was then re-instituted via a face mask, while in the second group the trachea was intubated during the 10-s period and ventilation of the lungs maintained. Arterial pressure, heart rate and plasma noradrenaline and adrenaline concentrations were measured before and after induction and at 1, 3 and 5 min after laryngoscopy. There were significant and similar increases in arterial pressure and circulating catecholamine concentrations following laryngoscopy with or without intubation. Intubation, however, was associated with significant increases in heart rate which did not occur in the laryngoscopy-only group.

595 citations


Cited by
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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