Design and Analysis of Phase I Clinical Trials

TLDR

Phase I trials aim to estimate the maximum tolerable dose (MTD) of a new drug, yet existing designs are largely ad hoc and lack intrinsic properties for satisfactory MTD estimation. The study compares the standard Phase I design and several simple alternatives in terms of conservativeness and MTD estimation with small sample sizes. Using a Markov chain representation and Monte Carlo simulations, the authors evaluated conservativeness, bias, and confidence interval methods for these designs. They found that several designs are nearly as conservative as the standard design, two two‑stage designs reduce bias in MTD estimation under non‑ideal dose‑response settings, and none of the three confidence interval methods achieved both narrow intervals and nominal coverage.

Abstract

The Phase I clinical trial is a study intended to estimate the so-called maximum tolerable dose (MTD) of a new drug. Although there exists more or less a standard type of design for such trials, its development has been largely ad hoc. As usually implemented, the trial design has no intrinsic property that provides a generally satisfactory basis for estimation of the MTD. In this paper, the standard design and several simple alternatives are compared with regard to the conservativeness of the design and with regard to point and interval estimation of an MTD (33rd percentile) with small sample sizes. Using a Markov chain representation, we found several designs to be nearly as conservative as the standard design in terms of the proportion of patients entered at higher dose levels. In Monte Carlo simulations, two two-stage designs are found to provide reduced bias in maximum likelihood estimation of the MTD in less than ideal dose-response settings. Of the three methods considered for determining confidence intervals--the delta method, a method based on Fieller's theorem, and a likelihood ratio method--none was able to provide both usefully narrow intervals and coverage probabilities close to nominal.