Volume 12 Supplement 1

Clinical Trials Methodology Conference 2011

Open Access

Clustering in surgical trials – database of intra-cluster correlations

  • Jonathan A Cook1,
  • Thomas Bruckner2,
  • Graeme S MacLennan1 and
  • Christoph M Seiler3
Trials201112(Suppl 1):A24

https://doi.org/10.1186/1745-6215-12-S1-A24

Published: 13 December 2011

Background

Randomised trials evaluating surgical interventions are often design and analysed as if the outcome of individual patients is independent of the surgeon providing the intervention. There is reason to expect outcomes for patients treated by the same surgeon to be more similar than those under the care of another surgeon due to previous experience, individual practice, training, and infrastructure. Such a phenomenon is referred to as the clustering effect and potentially impacts on the required sample size. This depends upon the design and analysis adopted. However, trialists have little data upon which to assess the impact and base trial design. The aim of this study was to quantify the clustering effect by producing a database of surgical trial ICCs.

Methods

Intra-cluster correlation coefficients (ICCs) were calculated for outcomes from a set of 10 multicentre surgical trials for a range of outcomes and different time points for clustering at both the centre and surgeon level.

Results

ICCs were calculated for 198 outcomes across the 10 trials at both centre and surgeon cluster levels. The number of cases varied from 138 to 1370 across the trials. The median (range) average cluster size was 32 (9 to 51) and 6 (3 to 30) for centre and surgeon levels respectively. ICC estimates varied substantially between outcomes though uncertainty around individual ICC estimates was substantial. Full details are available online [http://www.abdn.ac.uk/hsru/research/research-tools/study-design].

Conclusions

Our data for multicentre trials of surgical interventions suggests clustering of outcome is more of an issue than has been previously acknowledged. This database provides trialists with valuable information to aid the design of surgical trials. We anticipate that over time the addition of ICCs from further surgical trial datasets will enhance the usefulness of the database.

Declarations

Acknowledgements

The authors would like to thank the trial groups for access to the trial data and help preparing the data for analysis. The Health Services Research Unit is core funded by the Chief Scientist Office of the Scottish Government Health Directorates. Jonathan Cook holds a Medical Research Council UK fellowship (G0601938).Views expressed are those of the authors and do not necessarily reflect the view of Chief Scientist Office.

Authors’ Affiliations

(1)
Health Services Research Unit, University of Aberdeen
(2)
Institute of Medical Biometry and Informatics, University of Heidelberg
(3)
Department of General, Visceral and Trauma Surgery, University of Heidelberg

Copyright

© Cook et al; licensee BioMed Central Ltd. 2011

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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