Meta-analysis of randomised controlled trials

Rothwell, Peter M.; Robertson, G. A.

doi:10.1016/s0140-6736(05)63832-9

Cited by 19 publications

(8 citation statements)

References 5 publications

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“…Heterogeneity among the studies was examined with v 2 -based Q statistic (Lau et al, 1997). If there was statistically significant heterogeneity among studies (v 2 = 3.84; p < 0.05) (Rothwell and Robertson, 1997;Chu et al, 2012), a random effect model based on Dersimonian-Laird method was used to pool the data from different studies. Otherwise, a fixed effect model (Mantel-Haenszel method) (DerSimonian and Laird, 1986) was employed to analyze data.…”

Section: Discussionmentioning

confidence: 99%

Association Between Apolipoprotein B XbaI Polymorphism and Coronary Heart Disease in Han Chinese Population: A Meta-Analysis

Chen

Lin

Liang³

et al. 2016

Genetic Testing and Molecular Biomarkers

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Objective: To examine the association between apolipoprotein B (ApoB) XbaI polymorphisms (rs693) and coronary heart disease (CHD) risk among the Han Chinese population by systematically analyzing multiple independent studies. Methods: The Hardy-Weinberg equilibrium test was applied to check genetic equilibrium among genotypes for the selected literatures. The quality of the studies was assessed by using the NewcastleOttawa Scale. Power analysis was performed with Power and Precision V4 software. A fixed or random effect model was used on the basis of heterogeneity. Publication bias was quantified and examined with Begg's funnel plot test and Egger's linear regression test. The meta-analysis was performed by Stata 12.0 software. Results: A total of 10 eligible association studies were included in this meta-analysis, and the pooled sample consisted of 1195 CHD patients and 1178 health controls. No consistent inference regarding publication bias for the included studies was obtained by using the two above-mentioned methods.

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Section: Discussionmentioning

confidence: 99%

Association Between Apolipoprotein B XbaI Polymorphism and Coronary Heart Disease in Han Chinese Population: A Meta-Analysis

Chen

Lin

Liang³

et al. 2016

Genetic Testing and Molecular Biomarkers

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“…It is also important to recognise how unreliable initial evidence can be [60]–[61]. An analysis of data from 85,000 meta-analyses with binary outcomes in Cochrane Reviews showed that early trials tend to overestimate treatment effects [62].…”

Section: Discussionmentioning

confidence: 99%

Accumulating Research: A Systematic Account of How Cumulative Meta-Analyses Would Have Provided Knowledge, Improved Health, Reduced Harm and Saved Resources

Clarke

Brice²,

Chalmers³

2014

PLoS ONE

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Background“Cumulative meta-analysis” describes a statistical procedure to calculate, retrospectively, summary estimates from the results of similar trials every time the results of a further trial in the series had become available. In the early 1990s, comparisons of cumulative meta-analyses of treatments for myocardial infarction with advice promulgated through medical textbooks showed that research had continued long after robust estimates of treatment effects had accumulated, and that medical textbooks had overlooked strong, existing evidence from trials. Cumulative meta-analyses have subsequently been used to assess what could have been known had new studies been informed by systematic reviews of relevant existing evidence and how waste might have been reduced.Methods and FindingsWe used a systematic approach to identify and summarise the findings of cumulative meta-analyses of studies of the effects of clinical interventions, published from 1992 to 2012. Searches were done of PubMed, MEDLINE, EMBASE, the Cochrane Methodology Register and Science Citation Index. A total of 50 eligible reports were identified, including more than 1,500 cumulative meta-analyses. A variety of themes are illustrated with specific examples. The studies showed that initially positive results became null or negative in meta-analyses as more trials were done; that early null or negative results were over-turned; that stable results (beneficial, harmful and neutral) would have been seen had a meta-analysis been done before the new trial; and that additional trials had been much too small to resolve the remaining uncertainties.ConclusionsThis large, unique collection of cumulative meta-analyses highlights how a review of the existing evidence might have helped researchers, practitioners, patients and funders make more informed decisions and choices about new trials over decades of research. This would have led to earlier uptake of effective interventions in practice, less exposure of trial participants to less effective treatments, and reduced waste resulting from unjustified research.

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“…Rothwell and Robertson 59 found that the treatment effect was overestimated by early trials compared with the subsequent trials in 20 of 26 meta-analyses of clinical trials. The average difference in relative odds was 35% (95% CI 15 to 55).…”

Section: Time Lag Biasmentioning

confidence: 99%

Publication and related biases.

Song¹,

Eastwood²,

Gilbody³

et al. 2000

Health Technology Assessment

416

275

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Health Technology Assessment is indexed in Index Medicus/MEDLINE and Excerpta Medica/ EMBASE. Copies of the Executive Summaries are available from the NCCHTA website (see overleaf). NHS R&D HTA Programme T he overall aim of the NHS R&D Health Technology Assessment (HTA) programme is to ensure that high-quality research information on the costs, effectiveness and broader impact of health technologies is produced in the most efficient way for those who use, manage and work in the NHS. Research is undertaken in those areas where the evidence will lead to the greatest benefits to patients, either through improved patient outcomes or the most efficient use of NHS resources. The Standing Group on Health Technology advises on national priorities for health technology assessment. Six advisory panels assist the Standing Group in identifying and prioritising projects. These priorities are then considered by the HTA Commissioning Board supported by the National Coordinating Centre for HTA (NCCHTA). This report is one of a series covering acute care, diagnostics and imaging, methodology, pharmaceuticals, population screening, and primary and community care. It was identified as a priority by the Methodology Group and funded as project number 95/12/01. The views expressed in this publication are those of the authors and not necessarily those of the Standing Group, the Commissioning Board, the Panel members or the Department of Health. The editors wish to emphasise that funding and publication of this research by the NHS should not be taken as implicit support for the recommendations for policy contained herein. In particular, policy options in the area of screening will be considered by the National Screening Committee. This Committee, chaired by the Chief Medical Officer, will take into account the views expressed here, further available evidence and other relevant considerations. Reviews in Health Technology Assessment are termed 'systematic' when the account of the search, appraisal and synthesis methods (to minimise biases and random errors) would, in theory, permit the replication of the review by others. Criteria for inclusion in the HTA monograph series Reports are published in the HTA monograph series if (1) they have resulted from work either prioritised by the Standing Group on Health Technology, or otherwise commissioned for the HTA programme, and (2) they are of a sufficiently high scientific quality as assessed by the referees and editors.

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Meta-analysis of randomised controlled trials

Cited by 19 publications

References 5 publications

Association Between Apolipoprotein B XbaI Polymorphism and Coronary Heart Disease in Han Chinese Population: A Meta-Analysis

Association Between Apolipoprotein B XbaI Polymorphism and Coronary Heart Disease in Han Chinese Population: A Meta-Analysis

Accumulating Research: A Systematic Account of How Cumulative Meta-Analyses Would Have Provided Knowledge, Improved Health, Reduced Harm and Saved Resources

Publication and related biases.

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