Dose Finding for Drug Combination in Early Cancer Phase I Trials Using Conditional Continual Reassessment Method

Abstract

We describe a dose escalation algorithm for drug combinations in cancer phase I clinical trials. Parametric models for describing the association between the doses and the probability of dose limiting toxicity are used assuming univariate monotonicity of the dose-toxicity relationship. Trial design proceeds using the continual reassessment method, where at each stage of the trial, we seek the dose of one agent with estimated probability of toxicity closest to a target probability of toxicity given the current dose of the other agent. A Bayes estimate of the maximum tolerated dose (MTD) curve is proposed at the conclusion of the trial for continuous doses or a set of MTDs is determined in the case of discrete dose levels. We evaluate design operating characteristics in terms of safety of the trial and percent of dose recommendation at dose combination neighborhoods around the true MTD under various model generated scenarios and misspecification. The method is further assessed for varying algorithms enrolling cohorts of two and three patients receiving different doses and compared to previous approaches such as escalation with overdose control and two-dimensional design.

A Bayesian Adaptive Design in Cancer Phase I Trials Using Dose Combinations with Ordinal Toxicity Grades

“…The dose allocation algorithm proceeds by treating cohorts of two patients simultaneously. The dose combinations assigned to newly enrolled patients are based on EWOC scheme and the CRM principle proposed by the authors of [ 34 , 35 ], respectively.…”

“…The performance of the method is evaluated by calculating the percent of MTDs selection introduced by Tighiouart et al [ 34 ] estimating the percentage that a prospective trial will recommend a set of dose combinations that are all MTDs, where is the set of true MTDs such that the threshold parameter δ is fixed by a clinician. Following the same rationale, we also consider the percentage of selection of at least K dose combinations that are MTDs discussed in [ 35 ] is and the weighted average proportion of the recommended set of dose combinations which are MTDs is given by …”

“…Even though dose-finding designs for two agents have been the focus of statistical research in the last two decades [ 22 – 34 ], the proposed approaches have ignored lower grades and different types of toxicities. Noteworthy, Tighiouart et al [ 34 ] presented an early phase I EWOC design that estimates an MTD curve lying anywhere within the Cartesian plane defined by the range of the continuous doses of two synergistic agents, and Diniz et al [ 35 ] investigated properties of this approach using the CRM criterion. In this paper, we extend the work of Tighiouart et al [ 8 ] by accounting for lower grades of toxicities in the designs described in [ 34 , 35 ].…”

“…Noteworthy, Tighiouart et al [ 34 ] presented an early phase I EWOC design that estimates an MTD curve lying anywhere within the Cartesian plane defined by the range of the continuous doses of two synergistic agents, and Diniz et al [ 35 ] investigated properties of this approach using the CRM criterion. In this paper, we extend the work of Tighiouart et al [ 8 ] by accounting for lower grades of toxicities in the designs described in [ 34 , 35 ]. We assess the benefits of this added level of model complexity by comparing safety of the trial and efficiency of the estimate of the MTD to the ones obtained using binary DLT.…”

Modeling synergism in early phase cancer trials with drug combination with continuous dose levels: is there an added value?

“… Tighiouart et al, 2014 introduced a dose-finding method for continuous dose levels based on conditional EWOC and recommended an MTD curve at the conclusion of the trial. The method was extended to three drugs ( Tighiouart et al, 2016 ), case where the MTD curve lies anywhere in the Cartesian plane ( Tighiouart et al, 2017 ), using the CRM ( Diniz et al, 2017 ), adjusting for a baseline covariate ( Diniz et al, 2018 ), settings where an unknown fraction of DLTs is attributable to one or more agents ( Jiménez et al, 2019 ), using an ordinal toxicity grade ( Diniz et al, 2020 ), and to phase I/II designs ( Jiménez et al, 2020 ; Tighiouart, 2019 ).…”