In oncology dose-finding trials, due to staggered enrollment, it might be desirable to make dose-assignment decisions in real-time in the presence of pending toxicity outcomes, for example, when the dose-limiting toxicity is late-onset. Patients' time-to-event information may be utilized to facilitate such decisions. We review statistical frameworks for time-to-event modeling in dose-finding trials and summarize existing designs into two classes: TITE designs and POD designs. TITE designs are based on inference on toxicity probabilities, while POD designs are based on inference on dose-finding decisions. These two classes of designs contain existing individual designs as special cases and also give rise to new designs. We discuss and study the theoretical properties of these designs, including large-sample convergence properties, coherence principles, and the underlying decision rules. To facilitate the use of these designs in practice, we introduce efficient computational algorithms and review common practical considerations, such as safety rules and suspension rules. Finally, the operating characteristics of several designs are evaluated and compared through computer simulations.

翻译：在肿瘤剂量调查试验中,由于摄入时间错开,在毒性结果尚未确定的情况下,在实时作出剂量分配决定可能是可取的,例如,当剂量限制毒性晚期出现时。病人的时间对活动的信息可用于便利作出这种决定。我们审查剂量调查试验的时间对活动模型的统计框架,并将现有设计归纳为两类:TITE设计和POD设计。TITE设计基于毒性概率的推断,而POD设计则基于剂量调查决定的推断。这两类设计包括作为特殊案例的现有个别设计,并产生新的设计。我们讨论和研究这些设计的理论性质,包括大量聚合特性、一致性原则以及基本决定规则。为了便利在实践中使用这些设计,我们引入高效的计算算法,并审查共同的实际考虑,例如安全规则和暂停规则。最后,通过计算机模拟对若干设计的运作特点进行评价和比较。</s>