Abstract
We identify three properties of the standard oncology Phase I trial design or 3 + 3 design. We show that the standard design implicitly uses isotonic regression to estimate a maximum tolerated dose. We next illustrate the relationship between the standard design and a Bayesian design proposed by Ji et al. (Citation2007). A slight modification to this Bayesian design, under a particular model specification, would assign treatments in a manner identical to the standard design. We finally present calculations revealing the behavior of the standard design in a worst case scenario and compare its behavior with other 3 + 3-like designs.
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ACKNOWLEDGMENTS
We are grateful to Mei Polley for referring us to the work of Ji, Li, and Bekele. We also thank Wei Yu, Ron Yu, David Hiller, and Grazyna Lieberman for their ideas and suggestions.
Notes
The design stops enrolling patients after a dose is found where at most 1 of 6 patients experiences a DLT and where at least 2 DLTs are observed at the next highest dose.
The columns correspond to the number of patients treated at the current dose level, and the rows correspond to the number of DLTs at the current dose level. The elements specify the action, where “E” means escalate, “S” means stay the same, and “DU” means declare the current dose to be unacceptably toxic and de-escalate. The design stops enrolling patients after a dose is found where at most 1 of 6 patients experiences a DLT and where at least 2 DLTs are observed at the next highest dose.