Cancer phase I trial design using drug combinations when a fraction of dose limiting toxicities is attributable to one or more agents

Abstract

Drug combination trials are increasingly common nowadays in clinical research. However, very few methods have been developed to consider toxicity attributions in the dose escalation process. We are motivated by a trial in which the clinician is able to identify certain toxicities that can be attributed to one of the agents. We present a Bayesian adaptive design in which toxicity attributions are modeled via copula regression and the maximum tolerated dose (MTD) curve is estimated as a function of model parameters. The dose escalation algorithm uses cohorts of two patients, following the continual reassessment method (CRM) scheme, where at each stage of the trial, we search for the dose of one agent given the current dose of the other agent. The performance of the design is studied by evaluating its operating characteristics when the underlying model is either correctly specified or misspecified. We show that this method can be extended to accommodate discrete dose combinations.

Keywords: attributable toxicity; cancer phase I trials; continual reassessment method; copula type models; drug combination.

Figure 1

A chance tree illustrating the 5 possible outcomes we can find in a trial.

Figure 2

Contour plots for the working model in scenarios 1, 2 and 3. The black dashed curve represents the true MTD curve and the gray dashed lines represent the contours at θ ± 0.05 and θ ± 0.10.

Figure 3

Estimated MTD curves for m=1000 simulated trials. The black dashed curve represents the true MTD curve, the gray dashed lines represent the contours at θ ± 0.05 and θ ± 0.10, and the solid curves represent the estimated MTD curves at each value of η.

Figure 4

Pointwise average bias in estimating the true MTD in m=1000 simulated trials.

Figure 5

Pointwise percent of MTD recommendation for m=1000 simulated trials. Solid lines represent the pointwise percent of MTD recommendation when p=0.2 and dashed lines represent the pointwise percent of MTD recommendation when p=0.1.

Figure 6

Probability of DLT surfaces of the 6 scenarios from Table 3.

Figure 7

Probability of DLT surfaces of the 6 scenarios from Table 5.