Scenarios where special considerations
apply
Cluster trials
In patient randomised trials, all the data in the dummy tables relate
to individual patients or participants. In contrast, the
reporting of cluster randomized trials often requires the reporting of
both cluster level and patient level data. The dummy tables
should reflect this difference by reporting two baseline tables – one
that reports the cluster level characteristics by randomized group and
another that reports the patient level characteristics. In
addition, the flow diagram should represent the flow of clusters
through each stage of the trial. See further reading for more
details.
Illustrative examples - WHO pre-eclampsia
trial
|
|
---|---|
The protocol for the [WHO Multicentre Randomized Trial of Calcium Supplementation for the Prevention of Pre-eclamsia] contains dummy tables for the trial starting on page 29. (WHO Multicentre Randomized Trial of Calcium Supplementation for the Prevention of Pre-eclamsia - go to protocol) |
Illustrative examples - KAT trial
|
|
---|---|
The protocol for the [Knee Arthroplasty Trial] contains dummy tables for the trial in Appendix 8. (KAT trial - go to protocol) |
This checklist was developed by Dave Sackett, who prepared it for
the forthcoming
3rd edition of Clinical Epidemiology; A Basic Science for Answering
Questions
about Health Care, to be published by Lippincott, Williams &
Wilkins
in 2004.
The CONSORT statement is an important research tool that takes an
evidence-based approach to improve the quality of reports of randomized
trials. The statement is available in six languages and has been
endorsed by prominent medical journals such as The Lancet, Annals of
Internal Medicine, and the Journal of the American Medical Association.
Its critical value to researchers, health care providers, peer
reviewers, and journal editors, and health policy makers is the
guarantee of integrity in the reported results of research.
Elbourne DR. Campbell MK. Extending the CONSORT statement to cluster
randomized trials: for discussion. Statistics in Medicine 2001; 20:
489-96.