Background
toxicity, cancer, toxicities
ADVERSE EVENTS, CANCER
Phase I cancer clinical trials are a critical first step in the study of novel cancer therapeutic approaches. One of the primary goals of the phase I studies is to determine the dose of a new drug or therapeutic agent for use in subsequent phase II trials [The use of model-based adaptive clinical trial designs in phase I clinical trials has received much attention because it allows adaptations of trials and statistical designs of ongoing clinical trials [The other motivation is that various continuous measures of toxicity arise during phase I studies, which can be beneficial for examining dose-response relationships more precisely. For example, if one aims to consider all grades of toxicities from multiple adverse events when allocating doses, it may be necessary to derive a continuous toxicity score, such as the normalized equivalent toxicity score [Additionally, in pursuit of efficiency and speed in drug development, trialists are increasingly relying on the use of real-world data to assess the potential risks and benefits of new drugs, and much of this data may be originally measured on a continuous scale [Over the past few decades, there has been a remarkable development in adaptive dose-finding designs for phase I studies using binary toxicity outcomes, such as the continual reassessment method [However, the utilization of continuous toxicity outcomes for optimal dose finding has garnered relatively little attention compared to its counterpart based on binary toxicity outcomes. Since the earliest research work by Eichhorn in the 1970s [In this paper, our objective is to bridge the existing gap by introducing a novel, fully Bayesian dose-finding algorithm that provides flexibility in describing the dose-toxicity curve and wider applicability, based on continuous outcomes. The incorporation of a continuous response within our framework accommodates various scenarios, such as using a continuous toxicity score [