Repeated measures dose-finding design with time-trend detection in the presence of correlated toxicity data

Abstract

Background: Phase I trials are designed to determine the safety, tolerability, and recommended phase 2 dose of therapeutic agents for subsequent testing. The dose-finding paradigm has thus traditionally focused on identifying the maximum tolerable dose of an agent or combination therapy under the assumption that there is a non-decreasing relationship between dose-toxicity and dose-efficacy. The dose is typically determined based on the probability of severe toxicity observed during the first treatment cycle. A novel endpoint, the total toxicity profile, was previously developed to account for the multiple toxicity types and grades experienced in the first cycle. More recently, this was extended to a repeated measures design based on the total toxicity profile to account for longitudinal toxicities over multiple treatment cycles in the absence of within-patient correlation.

Methods: In this work, we propose to extend the design in the presence of within-patient correlation. Furthermore, we provide a framework to detect a toxicity time trend (toxicity increasing, decreasing, or stable) over multiple treatment cycles. We utilize a linear mixed model in the Bayesian framework, with the addition of Bayesian risk functions for decision-making in dose assignment.

Results: The performance of this design was evaluated using simulation studies and real data from a phase I trial. We demonstrated that using available toxicity data from all cycles of treatment improves the accuracy of maximum tolerated dose identification and allows for the detection of a time trend. The performance is consistent regardless of the strength of the within-patient correlation. In addition, the use of a quasi-continuous total toxicity profile score significantly increased the power to detect time trends compared to when binary data only were used.

Conclusion: The increased interest in molecularly targeted agents and immunotherapies in oncology necessitates innovative phase I study designs. Our proposed framework provides a tool to tackle some of the challenges presented by these novel agents, specifically through the ability to understand patterns of toxicity over time, which is important in the cases of cumulative or late toxicities.

Keywords: Dose-finding; adaptive; continual reassessment method; correlated toxicity; immunotherapy; maximum tolerated dose; molecularly targeted agents; phase I clinical trials; repeated measures; time trend.

Figure 1

Expected nTTP at each dose level at each cycle when the true MTD is d₂, d₃, d₄, and d₅. The top panel shows dose toxicity curves with increasing trends; the bottom panel shows dose-toxicity curves with decreasing trends. The dashed lines represent the target nTTP 0.28.

Figure 2

Observed nTTP (dashed line) vs. predicted nTTP from the repeated measures design model (solid line) per cycle. The observed nTTP per dose per cycle were marked with colors (red represents dose level 1, yellow dose level 2, green dose level 3, light blue dose level 4, dark blue dose level 5, and pink dose level six).