Effect of a misspecification of response rates on type I and type II errors, in a phase II Simon design.

Phase-II trials are a key stage in the clinical development of a new treatment. Their main objective is to provide the required information for a go/no-go decision regarding a subsequent phase-III trial. In single arm phase-II trials, widely used in oncology, this decision relies on the comparison of efficacy outcomes observed in the trial to historical controls. The false positive rate generally accepted in phase-II trials, around 10%, contrasts with the very high attrition rate of new compounds tested in phase-III trials, estimated at about 60%. We assumed that this gap could partly be explained by the misspecification of the response rate expected with standard treatment, leading to erroneous hypotheses tested in the phase-II trial. We computed the false positive probability of a defined design under various hypotheses of expected efficacy probability. Similarly we calculated the power of the trial to detect the efficacy of a new compound for different expected efficacy rates. Calculations were done considering a binary outcome, such as the response rate, with a decision rule based on a Simon two-stage design. When analysing a single-arm phase-II trial, based on a design with a pre-specified null hypothesis, a 5% absolute error in the expected response rate leads to a false positive rate of about 30% when it is supposed to be 10%. This inflation of type-I error varies only slightly according to the hypotheses of the initial design. Single-arm phase-II trials poorly control for the false positive rate. Randomised phase-II trials should, therefore, be more often considered.