Trial Design


For most Phase II trials, drug activity is defined in terms of reduction in tumor burden. The most recent criteria for measuring activity, known as the Response Evaluation Criteria in Solid Tumors or RECIST,22 are based on unidimensional measurements. The criteria require the identification of target lesions and nontarget lesions at baseline. A complete response (CR) is the disappearance of all target and nontarget lesions, provided no new lesions have developed. A partial response (PR) is a 30% or greater decrease in the sum of the longest diameter (LD) of all target lesions, provided no nontarget lesions have progressed and no new lesions have developed. Progressive disease (PD) is defined as a 20% or greater increase in the sum of the LD of target lesions, progression of nontarget lesions, or the occurrence of new lesions. If there has been neither sufficient shrinkage to qualify for PR nor sufficient increase to qualify for PD, the patient is classified as having stable disease (SD). A patient who achieves either a CR or PR is defined as an objective responder, and the proportion of patients responding, that is, the response rate, has become the primary endpoint of interest in the design and analysis of phase II cancer clinical trials. While it is conceptually straightforward and can be assessed within a shorter time frame, there has been concern that the response rate is an inadequate substitute for more clinically relevant endpoints such as extension of survival. Some studies have shown that less than 25% of agents that show positive tumor response are eventually found to extend survival in comparative trials,23 whereas other studies suggest that tumor response is a reasonable surrogate for survival extension.24 Moertel25 and others have raised additional problems with the use of response rates in Phase II trials, such as subjectivity and lack of reproducibility in assessment. Other possible choices for endpoints are discussed later in this section.

Sample Size

In a typical Phase II study, the objective is to compare the observed response rate for the new agent to some level, p0 which is usually set equal to or slightly below the response rate achievable with standard therapy in the target patient population. The value for p0 must be chosen carefully, using information from previously reported trials and investigator knowledge, because the main objective will be to determine whether there is sufficient evidence to conclude that the response rate for the new regimen is greater than p0. In formal terms, if we let p denote the probability of response, the problem can be formulated as a test of the null hypothesis H0: p = p0, against the alternative hypothesis HA: p = pA where pA is a response rate that, if true, would be clinically material. The value of pA, along with the sample size, will determine the power of the study and therefore, two points should be noted. First, to detect a small improvement (say, 10% or less) requires a large sample size. For example, to detect an improvement from 20% to 30% with 85% power, more than

100 subjects are required, which may be undesirable for a Phase II trial, where there are limited efficacy data thus far. Second, the value for pA must be realistic; it is of little value to design and carry out a study to detect an effect size pA - p0 that is unlikely to be realized, simply because it is compatible with the number of patients that can be recruited in a reasonable time period. Most Phase II clinical trials aim for a response rate improvement of 15% to 20%.

For a specified significance level and power, it is straightforward to determine the number of patients needed for the trial (see Fleming,26 for example) and to test H0. It should be noted that, in the context of Phase II trials, hypothesis tests are one-sided in the sense that we are only interested if the new treatment improves the response rate and not in establishing whether it could be worse. Statistical power should be high (85% or 90%), because if the drug is rejected as inactive it may never undergo further study. It is not uncommon to relax the a level from the usual 5% to 10%, because if the drug is falsely declared active, its lack of efficacy would likely be uncovered in subsequent trials.

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