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 groups of patients with the optimal dose according to the current knowledge, with the hope that this will lead to using the true MTD from some time on. However, the first result proved here is that this goal is infeasible, and 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. Allowing some non-MTD treatment, we construct a randomized design that assigns the MTD with probability that approaches one as the size of the experiment goes to infinity and estimates the MTD consistently. We compare the suggested design with several methods by simulations, studying their performances in terms of correct estimation of the MTD and the proportion of individuals treated with the MTD.
Original language | English |
---|---|
Pages (from-to) | 2759-2768 |
Number of pages | 10 |
Journal | Journal of Statistical Planning and Inference |
Volume | 141 |
Issue number | 8 |
DOIs | |
State | Published - Aug 2011 |
Keywords
- Isotonic regression
- Maximum tolerated dose
- Phase I trial
- Stochastic approximation
- Up-and-down design
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics