The statistics of phase 0 trials

Abstract

The PD-driven phase 0 trial is a new form, designed to be a first-in-man study, often of a new agent, conducted to assess drug effect on a molecular target, by means of a pharmacodynamic (PD) assay, in a very small number (10-15) of patients. Such a study is meant to be a proof of principle trial to determine whether the agent yields the PD effect predicted by pre-clinical studies. The dosage is meant to be pharmacologically active, but is neither toxic nor likely to yield clinical benefit. Such a trial may be used to serve as a very early test of an agent's biologic effect, allowing for early weeding out of ineffective agents, or as an early means of determining the most promising of competing analogue agents. This manuscript will present designs for such PD-driven studies that are statistically efficient and rigorous, focusing on non-comparative trials. The phase 0 trial promises to become an increasingly important tool for facilitating and speeding the development of new therapeutic agents, particularly in oncology.

Figures

Figure 1

This figure illustrates the defining of PD “response” for an individual patient. Multipliers of the baseline SD are derived from asymptotic normal distribution theory. Significance levels are 1-sided.

Figure 2

This figure illustrates the defining of what constitutes a promising observed response rate for a dose level. The target (true) PD response rate, across patients, is 80%. Power and false positive rate are derived from the binomial distribution.

Figure 3

This figure illustrates the defining of what constitutes a promising observed response rate for a dose level with a 2-stage design. The target (true) PD response rate, across patients, is 60%. Power and false positive rate are derived from the binomial distribution.

Figure 4

This figure illustrates the defining of what constitutes a promising observed response rate for a dose level with a 2-stage design. The target (true) PD response rate, across patients, is 40%. Power and false positive rate are derived from the binomial distribution.