Adequacy and reporting of allocation concealment: review of recent trials published in four general medical journals.
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Periodicals as Topic↗
Biomedical subjects
Judith Watson
Publications and source records attributed to Judith Watson.
Methodological bias in cluster randomised trials.
BACKGROUND: Cluster randomised trials can be susceptible to a range of methodological problems. These problems are not commonly recognised by many researchers. In this paper we discuss the issues that can lead to bias in cluster trials. METHODS: We used a sample of cluster randomised trials from a recent review and from a systematic review of hip protectors. We compared the mean age of participants between intervention groups in a sample of 'good' cluster trials with a sample of potentially biased trials. We also compared the effect sizes, in a funnel plot, between hip protector trials that used individual randomisation compared with those that used cluster randomisation. RESULTS: There is a tendency for cluster trials, with evidence methodological biases, to also show an age imbalance between treatment groups. In a funnel plot we show that all cluster trials show a large positive effect of hip protectors whilst individually randomised trials show a range of positive and negative effects, suggesting that cluster trials may be producing a biased estimate of effect. CONCLUSION: Methodological biases in the design and execution of cluster randomised trials is frequent. Some of these biases associated with the use of cluster designs can be avoided through careful attention to the design of cluster trials. Firstly, if possible, individual allocation should be used. Secondly, if cluster allocation is required, then ideally participants should be identified before random allocation of the clusters. Third, if prior identification is not possible, then an independent recruiter should be used to recruit participants.
Age Factors↗
Cluster randomized controlled trials.
Cluster randomized controlled trial (RCT), in which groups or clusters of individuals rather than individuals themselves are randomized, are increasingly common. Indeed, for the evaluation of certain types of intervention (such as those used in health promotion and educational interventions) a cluster randomized trial is virtually the only valid approach. However, cluster trials are generally more difficult to design and execute than individually randomized studies, and some design features of a cluster trial may make it particularly vulnerable to a range of threats that can introduce bias. In this paper we discuss the issues that can lead to bias in cluster randomized trials and conclude with some suggestions for avoiding these problems.
Cluster Analysis↗
Evidence for risk of bias in cluster randomised trials: review of recent trials published in three general medical journals.
OBJECTIVE: To examine the prevalence of a risk of bias associated with the design and conduct of cluster randomised controlled trials among a sample of recently published studies. DESIGN: Retrospective review of cluster randomised trials published in the BMJ, Lancet, and New England Journal of Medicine from January 1997 to October 2002. MAIN OUTCOME MEASURES: Prevalence of secure randomisation of clusters, identification of participants before randomisation (to avoid foreknowledge of allocation), differential recruitment between treatment arms, differential application of inclusion and exclusion criteria, and differential attrition. RESULTS: Of the 36 trials identified, 24 were published in the BMJ,11 in the Lancet, and a single trial in the New England Journal of Medicine. At the cluster level, 15 (42%) trials provided evidence for secure allocation and 25 (69%) used stratified allocation. Few trials showed evidence of imbalance at the cluster level. However, some evidence of susceptibility to risk of bias at the individual level existed in 14 (39%) studies. CONCLUSIONS: Some recently published cluster randomised trials may not have taken adequate precautions to guard against threats to the internal validity of their design.
Bias↗