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Measuring inconsistency in meta-analyses

TLDR
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 …

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Meta-analysis: anticoagulant prophylaxis to prevent symptomatic venous thromboembolism in hospitalized medical patients.

TL;DR: A meta-analysis of randomized, controlled trials of anticoagulant prophylaxis in medical patients, focusing on the effects of treatment on clinically important efficacy outcomes (any PE, fatal PE, symptomatic DVT, and all-cause mortality) and safety outcomes (major bleeding).
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Systematic Review and Meta-analysis: Renal Safety of Tenofovir Disoproxil Fumarate in HIV-Infected Patients

TL;DR: The findings do not support the need to restrict TDF use in jurisdictions where regular monitoring of renal function and serum phosphate levels is impractical and support the use of TDF-containing ART regimens for HIV-infected individuals.
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Screening for thrombophilia in high-risk situations: systematic review and cost-effectiveness analysis. The Thrombosis: Risk and Economic Assessment of Thrombophilia Screening (TREATS) study

TL;DR: A systematic review of the literature on VTE and thrombophilia in women using oral oestrogen preparations and patients undergoing major orthopaedic surgery and the effectiveness of prophylaxis found homozygous carriers of this mutation are 34 times more likely to develop VTE in pregnancy than non-carriers.
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Helicobacter pylori eradication therapy to prevent gastric cancer in healthy asymptomatic infected individuals: systematic review and meta-analysis of randomised controlled trials

TL;DR: Limited, moderate quality evidence is provided that searching for and eradicating H pylori reduces the incidence of gastric cancer in healthy asymptomatic infected Asian individuals, but these data cannot necessarily be extrapolated to other populations.
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Non-vigorous physical activity and all-cause mortality: systematic review and meta-analysis of cohort studies

TL;DR: The largest benefit was found from moving from no activity to low level of activity, but even at high levels of activity benefits accrue from additional activity, as well as in studies that looked at walking alone.
References
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Journal ArticleDOI

Quantifying heterogeneity in a meta‐analysis

TL;DR: It is concluded that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity, and one or both should be presented in publishedMeta-an analyses in preference to the test for heterogeneity.
Journal ArticleDOI

The combination of estimates from different experiments.

TL;DR: The problem of making a combined estimate has been discussed previously by Cochran and Yates and Cochran (1937) for agricultural experiments, and by Bliss (1952) for bioassays in different laboratories as discussed by the authors.
Journal ArticleDOI

Tamoxifen for early breast cancer: An overview of the randomised trials

TL;DR: The absolute improvement in recurrence was greater during the first 5 years, whereas the improvement in survival grew steadily larger throughout the first 10 years, and these benefits appeared to be largely irrespective of age, menopausal status, daily tamoxifen dose, and of whether chemotherapy had been given to both groups.
Journal Article

Tamoxifen for early breast cancer: an overview of the randomised trials. Early Breast Cancer Trialists' Collaborative Group

Anthony Howell
- 16 May 1998 - 
TL;DR: There have been many randomised trials of adjuvant tamoxifen among women with early breast cancer, and an updated overview of their results is presented in this paper, which approximately doubles the amount of evidence from trials of about 5 years of tamoxifier and, taking all trials together, on events occurring more than 5 years after randomisation.
Journal ArticleDOI

Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis.

TL;DR: In this paper, the authors evaluated standard error, precision (inverse of standard error), variance, inverse of variance, sample size and log sample size (vertical axis) and log odds ratio, log risk ratio and risk difference (horizontal axis).
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