The treatment versus experimentation dilemma in dose finding studies

Abstract

Phase I clinical trials are conducted in order to find the maximum tolerated dose (MTD) of a given drug from a finite set of doses. For ethical reasons, these studies are usually sequential, treating patients or group of patients with the best available dose according to the current knowledge. However, it is proved here that such designs, and, more generally, designs that concentrate on one dose from some time on, cannot provide consistent estimators for the MTD unless very strong parametric assumptions hold. We describe a family of sequential designs that treat individuals with one of the two closest doses to the estimated MTD, and prove that such designs, under general conditions, concentrate eventually on the two closest doses to the MTD and estimate the MTD consistently. It is shown that this family contains randomized designs that assign the MTD with probability that approaches 1 as the size of the experiment goes to infinity. We compare several designs by simulations, studying their performances in terms of correct estimation of the MTD and the proportion of individuals treated with the MTD.

A Phase I/II trial design when response is unobserved in subjects with dose-limiting toxicity

“…the MSD, near the end of the study. However, recent work Azriel et al 20 shows for the traditional setting of dose-finding based solely on toxicity, any design that eventually focuses upon one dose being assigned to subjects cannot asymptotically find the correct MTD with probability 1.0. We would expect these results would hold true for our setting as well.…”

Adaptive Clinical Trials

“…However, doubts about the convergence and informativeness of best intention designs were raised long ago, and cases were found in which such designs led to allocations converging to the wrong point. Examples are provided by Azriel (29), Mandel and Rinott (25), Bozin and Zarr (30), Chang and Ying (31), Ghosh, Mukhopadhyay and Sen (32), Lai and Robbins (33), Oron, Azriel and Hoff (34), and Pronzato (18). The major remedy to ensure convergence and increase informativeness of best intention designs is to introduce the intentional variability of allocations around the dose that is currently viewed as being the best.…”

Optimizing Sedative Dose in Preterm Infants Undergoing Treatment for Respiratory Distress Syndrome

“…Robbins, 1952; Gittins, 1979; Sutton and Barto, 1998). This fact has been recognized only recently in the context of dose-finding clinical trials (Azriel, et al, 2011; Thall and Nguyen, 2012; Oron and Hoff, 2013). In the propofol trial, always choosing an “optimal” dose x by maximizing u ( x | data n ) is an example of a greedy algorithm, even if x is restricted to 𝒜 n .…”