The Cochrane Collaboration's tool for assessing risk of bias in randomised trials

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

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

Related collections

Most cited references 11

Record: found
Abstract: not found
Article: not found

Systematic reviews in health care: Assessing the quality of controlled clinical trials.

P Jüni, D Altman, M. Egger (2001)

0 comments Cited 455 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

The hazards of scoring the quality of clinical trials for meta-analysis.

Peter Jüni (1999)

Although it is widely recommended that clinical trials undergo some type of quality review, the number and variety of quality assessment scales that exist make it unclear how to achieve the best assessment. To determine whether the type of quality assessment scale used affects the conclusions of meta-analytic studies. Meta-analysis of 17 trials comparing low-molecular-weight heparin (LMWH) with standard heparin for prevention of postoperative thrombosis using 25 different scales to identify high-quality trials. The association between treatment effect and summary scores and the association with 3 key domains (concealment of treatment allocation, blinding of outcome assessment, and handling of withdrawals) were examined in regression models. Pooled relative risks of deep vein thrombosis with LMWH vs standard heparin in high-quality vs low-quality trials as determined by 25 quality scales. Pooled relative risks from high-quality trials ranged from 0.63 (95% confidence interval [CI], 0.44-0.90) to 0.90 (95% CI, 0.67-1.21) vs 0.52 (95% CI, 0.24-1.09) to 1.13 (95% CI, 0.70-1.82) for low-quality trials. For 6 scales, relative risks of high-quality trials were close to unity, indicating that LMWH was not significantly superior to standard heparin, whereas low-quality trials showed better protection with LMWH (P<.05). Seven scales showed the opposite: high quality trials showed an effect whereas low quality trials did not. For the remaining 12 scales, effect estimates were similar in the 2 quality strata. In regression analysis, summary quality scores were not significantly associated with treatment effects. There was no significant association of treatment effects with allocation concealment and handling of withdrawals. Open outcome assessment, however, influenced effect size with the effect of LMWH, on average, being exaggerated by 35% (95% CI, 1%-57%; P= .046). Our data indicate that the use of summary scores to identify trials of high quality is problematic. Relevant methodological aspects should be assessed individually and their influence on effect sizes explored.

0 comments Cited 383 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Bias in clinical intervention research.

Lise Lotte Gluud (2006)

Research on bias in clinical trials may help identify some of the reasons why investigators sometimes reach the wrong conclusions about intervention effects. Several quality components for the assessment of bias control have been suggested, but although they seem intrinsically valid, empirical evidence is needed to evaluate their effects on the extent and direction of bias. This narrative review summarizes the findings of methodological studies on the influence of bias in clinical trials. A number of methodological studies suggest that lack of adequate randomization in published trial reports may be associated with more positive estimates of intervention effects. The influence of double-blinding and follow-up is less clear. Several studies have found a significant association between funding sources and pro-industry conclusions. However, the methodological studies also show that bias is difficult to detect and appraise. The extent of bias in individual trials is unpredictable. A-priori exclusion of trials with certain characteristics is not recommended. Appraising bias control in individual trials is necessary to avoid making incorrect conclusions about intervention effects.

0 comments Cited 184 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Title: BMJ

Abbreviated Title: BMJ

Publisher: BMJ

ISSN (Print): 0959-8138

ISSN (Electronic): 1468-5833

Publication date Created: October 18 2011

Publication date (Electronic): October 18 2011

Publication date (Print): October 18 2011

Volume: 343

Issue: oct18 2

Page: d5928

Article

DOI: 10.1136/bmj.d5928

SO-VID: 2f4dc86a-ca60-4c3f-9f4b-582955dcdcc7

History

Data availability:

Comments

Comment on this article

scite_

Cited by 11,224

See all cited by

- Version 1

The Cochrane Collaboration's tool for assessing risk of bias in randomised trials

Read this article at

Abstract

Related collections

Primate Tool Use

Most cited references 11

Systematic reviews in health care: Assessing the quality of controlled clinical trials.

The hazards of scoring the quality of clinical trials for meta-analysis.

Bias in clinical intervention research.

Author and article information

Journal

Article

History

Comments

Comment on this article

Similar content 1,995

Cited by 11,224