New Methodology in Clinical Trials

Abstract

The review of adaptive assignment methods by Simon (1977) follows a similar review by Bailar (1976). Both authors point out that recent theoretical developments in clinical trial methodology have been almost totally ignored by practitioners. They reach similar conclusions, to the effect that the practitioners are on the whole correct in their implied judgment; the new methods, they hold, are not really well suited to the clinical trial field. There is no doubt that there are difficult problems, both practical and theoretical, with which adaptive methods have yet to come to terms. One of these relates to trials in which the response takes a long time to declare itself, so that it is unrealistic to suppose that the response on the ith subject is known at the time at which the treatment for the (i + l)th subject is to be determined. This situation is routine in the cancer field (it is to be noted that both Bailar and Simon wrote from cancer research centres) and is common in trials relating to a variety of chronic conditions. Another problem especially concerns methods which make it difficult to conceal the nature of the treatment from those concerned with administering it and assessing its consequences. A third points to difficulties arising from non-stationarity; if conditions change unpredictably in the course of a trial, adaptive methods may give rise to substantial biases. I do not wish to comment on this set of problems, except to say that they seem to me not to be logically insuperable and so to represent a challenge to clinical trial theorists. As things stand, they do present a set of good reasons for not embarking upon an adaptive trial at this time. Rather, I want to comment briefly on some other reasons given by Simon and Bailar which seem to me to be less well founded. These in fact relate to clinical trials in general and are not at all specific to those using adaptive methods. Simon in particular is critical of 'selection theory' methods in which the trial culminates in an explicit decision to recommend one or another of the treatments in the trial. 'Clinical trials', he states, 'are complicated experiments in which the evaluation of the treatments requires a careful summarization of all evidence concerning relative eSects. If there is little evidence that the treatments differ substantially in efficacy, then such a conclusion must be stated. Significance tests of the null hypothesis play an important role in the analysis and have evidential content that is meaningful to a wide variety of clinical investigators. Statisticians . . . have not dented the importance to clinicians of null 'p values' in interpreting and reporting complicated clinical results . . . Any design which does not provide for a convincing test of the null hypothesis has little chance of being adopted for general use.' With a decisionbased approach, 'there is no provision for concluding that . . . results for the treatments do not diSer more than might be expected by chance.' One reaction to Simon's emphasis on the importance of significance levels is to ask just what the clinician is expected to do with them. Presumably if treatment A gives significantly better results than treatment B (always having regard to undesirable side eSects), treatment A should be adopted for future patients since the evidence is that it is truly the better