Abstract
A desirable property of any dose-escalation strategy for phase I oncology trials is coherence: if the previous patient experienced a toxicity, a higher dose is not recommended for the next patient; similarly, if the previous patient did not experience a toxicity, a lower dose is not recommended for the next patient. The escalation with overdose control (EWOC) approach is a model-based design that has been applied in practice, under which the dose assigned to the next patient is the one that, given all available data, has a posterior probability of exceeding the maximum tolerated dose equal to a pre-specified value known as the feasibility bound. Several methodological and applied publications have considered the EWOC approach with both feasibility bounds fixed and increasing throughout the trial. Whilst the EWOC approach with fixed feasibility bound has been proven to be coherent, some proposed methods of increasing the feasibility bound regardless of toxicity outcomes of patients can lead to incoherent dose-escalation. This paper formalises a proof that incoherent dose-escalation can occur if the feasibility bound is increased without consideration of preceding toxicity outcomes, and shows via simulation studies that only small increases in the feasibility bound are required for incoherent dose-escalations to occur.
Highlights
Phase I clinical trials mark the first experimentation of a new drug in a human population
The escalation with overdose control (EWOC) approach is a model-based design that has been applied in practice, under which the dose assigned to the patient is the one that, given all available data, has a posterior probability of exceeding the maximum tolerated dose equal to a pre-specified value known as the feasibility bound
The escalation with overdose control (EWOC) approach (Babb et al 1998) is a Bayesian adaptive design that reduces the risk of overdosing patients by choosing doses with a posterior probability of being above the true Maximum Tolerated Dose (MTD) equal to some value known as a feasibility bound
Summary
Phase I clinical trials mark the first experimentation of a new drug in a human population. Sample sizes in phase I oncology trials are often very small, which means that multiple testing procedures that incorporate dose-toxicity orders are not useful (Pigeot 2000) To avoid these issues, several Bayesian adaptive methods, which sequentially recommend dose adaptations and borrow information from lower dose levels and prior beliefs, have been proposed for conducting dose-escalation studies and estimating the MTD (O’Quigley et al 1990; Babb et al 1998; Cheung and Chappell 2000).
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have