Size of cancer clinical trials and stopping rules

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Abstract
A recent international survey on the size of clinical trials in cancer showed the frequent problem of slow patient accrual, which remains a major hindrance to progress. The survey also revealed that, although the design of most trials specified a fixed number of patients, subsequent experience revealed a much more flexible approach, with analysis of results, say, every 4--6 months. Conventional sequential methods are hardly ever used and unfortunately most trials proceed without any predetermined stopping rules. Some trial organizers use repeated significance tests on accumulating data as a guide to the detection of treatment differences, an approach that can be adapted to a more rigorous statistical framework as a "group sequential design". The major statistical principle involved is that the more often one analyses the data the greater is the probability of achieving a statistically significant result, even when the two treatments are equally effective. Group sequential designs require the adoption of a more stringent significance level to allow for repeated testing. If one intends up to 10 repeated analyses of the data, only a treatment difference significant at the 1% level would merit a decision to stop the trial. For any trial to implement a stopping rule successfully there must also be prompt feedback and processing of response and survival data ready for up-to-date analysis. Such efficiency is often lacking. The repeated presentation of interim results of a trial to participating investigators can seriously affect their future reaction, especially if there are interesting but non-significant differences. Thus, some secrecy about ongoing results is advisable if trials are to achieve an unbiased conclusion.

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