Phase I Designs That Allow for Uncertainty in the Attribution of Adverse Events
针对I期临床试验中不良事件归因的主观性偏差，提出基于模型的方法来减少偏差对最大耐受剂量估计的影响，提高估计准确性。
In determining dose limiting toxicities in Phase I studies, it is necessary to attribute adverse events (AE) to being drug related or not. Such determination is subjective and may introduce bias. In this paper, we develop methods for removing or at least diminishing the impact of this bias on the estimation of the maximum tolerated dose (MTD). The approach we suggest takes into account the subjectivity in the attribution of AE by using model-based dose escalation designs. The results show that gains can be achieved in terms of accuracy by recovering information lost to biases. These biases are a result of ignoring the errors in toxicity attribution.