Strategy for randomised clinical trials in rare cancersBMJ 2003; 327 doi: http://dx.doi.org/10.1136/bmj.327.7405.47 (Published 03 July 2003) Cite this as: BMJ 2003;327:47
- Say-Beng Tan (email@example.com), senior biostatistician1,
- Keith B G Dear, senior fellow2,
- Paolo Bruzzi, head3,
- David Machin, professor4
- 1Division of Clinical Trials and Epidemiological Sciences, National Cancer Centre, 11 Hospital Drive, Singapore 169610
- 2National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
- 3Unit of Clinical Epidemiology and Trials, National Cancer Research Institute, Genoa, Italy
- 4United Kingdom Children's Cancer Study Group, University of Leicester, Leicester
- Correspondence to: S-B Tan
- Accepted 30 May 2003
Proving that a new treatment is more effective than current treatment can be difficult for rare conditions. Data from small randomised trials could, however, be made more robust by taking other related research into account
The need for randomised trials to establish that treatments are effective is well established. However, because the effects of new treatments are usually modest compared with standard treatment, large numbers of patients are needed to detect any genuine benefits. This means that, even for common cancers, studies often have to be multicentred to ensure enough patients are recruited in a reasonable time. The strategy for testing new treatments in rare cancers, where it is impossible to accrue large number of patients, is unclear. We extend Lilford and others' proposal that a bayesian statistical approach, using related information from earlier studies, would be useful in designing and subsequently summarising small randomised controlled trials.1 We suggest a scoring system for pooling this evidence and detail how this may be combined with hypothetical scenarios to assist in the design of, and justification for, a small randomised controlled trial.
Problems of small trials
Randomised controlled trials are regarded as the standard when comparing a new treatment with the standard treatment for a particular cancer. However, to be considered clinically worth while in clinical trials, these (essentially) very toxic regimens typically need to show relative reductions in the risk of death of 20-30%. For studies to have sufficient statistical power (≥80%) to detect treatment effects of this magnitude, several hundreds of deaths (typically 200 to 500) need to be observed. This implies trial sizes that are unrealistically large for rare cancers. Furthermore, even if a much larger treatment effect could be expected, estimates derived from the resulting (small) randomised controlled trial would lack the precision needed for clinical decisions.
Thus, investigators who wish …
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