Measuring inconsistency in meta-analyses
Reads0
Chats0
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 …read more
Citations
More filters
Reference EntryDOI
Vitamin D and vitamin D analogues for preventing fractures associated with involutional and post-menopausal osteoporosis
TL;DR: Frail older people confined to institutions may sustain fewer hip and other non-vertebral fractures if given vitamin D with calcium supplements, and there is no evidence of advantage of analogues of vitamin D compared with vitamin D.
Journal ArticleDOI
Methodological issues and advances in biological meta-analysis
TL;DR: It is shown how the marriage between mixed-effects (hierarchical/multilevel) models and phylogenetic comparative methods has resolved most of the issues under discussion and how the use of within-study meta-analysis can improve many empirical studies typical of ecology and evolution.
Journal ArticleDOI
Effects of testosterone on body composition, bone metabolism and serum lipid profile in middle-aged men: a meta-analysis.
Andrea M. Isidori,Elisa Giannetta,Emanuela A. Greco,Daniele Gianfrilli,V. Bonifacio,Aldo Isidori,Andrea Lenzi,Andrea Fabbri +7 more
TL;DR: A systematic review of randomized controlled trials evaluating the effects of testosterone administration to middle‐aged and ageing men on body composition, muscle strength, bone density, markers of bone metabolism and serum lipid profile concludes that androgen treatment might be beneficial in these subjects.
Journal ArticleDOI
Preventing 30-day hospital readmissions: a systematic review and meta-analysis of randomized trials.
Aaron L. Leppin,Michael R. Gionfriddo,Maya E. Kessler,Juan P. Brito,Frances S. Mair,Katie Gallacher,Zhen Wang,Patricia J. Erwin,Tanya Sylvester,Kasey R. Boehmer,Kasey R. Boehmer,Henry H. Ting,M. Hassan Murad,Nathan D. Shippee,Victor M. Montori +14 more
TL;DR: Tested interventions are effective at reducing readmissions, but more effective interventions are complex and support patient capacity for self-care.
Journal ArticleDOI
Blood Pressure Lowering in Type 2 Diabetes: A Systematic Review and Meta-analysis
TL;DR: Among patients with type 2 diabetes, BP lowering was associated with improved mortality and other clinical outcomes with lower RRs observed among those with baseline BP of 140 mm Hg and greater, and these findings support the use of medications for BP lowering in these patients.
References
More filters
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
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).