Methodological bias in cluster randomised trials

Medical Research Collaborating Center, Seoul National University College of Medicine, 2nd Floor Cancer Research Institute Building, 28 Yongon Dong, Chongno Gu, Seoul 110-744, Korea. <>
BMC Medical Research Methodology (Impact Factor: 2.27). 02/2005; 5(1):10. DOI: 10.1186/1471-2288-5-10
Source: PubMed


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.
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.
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.
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.

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Available from: David Torgerson
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    • "In CRTs, achieving balance on individual characteristics between treatment groups can sometimes be difficult. Indeed, clusters are sometimes randomized before patient inclusion, which increases the risk of selection bias because recruiters are no longer blinded to the treatment allocation which compromises allocation concealment [2] [3] [4] [5] [6] [7]. "
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    ABSTRACT: Despite randomization, selection bias may occur in cluster randomized trials. Classical multivariable regression usually allows for adjusting treatment effect estimates with unbalanced covariates. However, for binary outcomes with low incidence, such a method may fail because of separation problems. This simulation study focused on the performance of propensity score (PS)-based methods to estimate relative risks from cluster randomized trials with binary outcomes with low incidence. The results suggested that among the different approaches used (multivariable regression, direct adjustment on PS, inverse weighting on PS, and stratification on PS), only direct adjustment on the PS fully corrected the bias and moreover had the best statistical properties. Copyright © 2014 John Wiley & Sons, Ltd.
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    • "In the effort of minimizing the risk of bias caused by confounding parameters, randomized trials are needed. In a randomized trial, it may be methodologically preferable randomizing patients individually [40]. However, in an attempt to assess the impact of the implementation of recommendations made at a departmental level, it may be difficult to conduct organizational interventions at an individual level. "
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    • "Randomization of PHCCs will be done once the caregivers eligible for the study have been chosen, so that recruitment by health professionals is not influenced by their allocation to a study group [28,29]. "
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