Generalization of the time-to-event continual reassessment method to bivariate outcomes

This article considers the problem of designing Phase I-II clinical trials with delayed toxicity and efficacy outcomes. The proposed design is motivated by a Phase I-II study evaluating all-trans retinoic acid (ATRA) in combination with a fixed dose of daratumumab in the treatment of relapsed or refractory multiple myeloma. The primary objective of the study is to identify a dose that maximizes efficacy and has an acceptable level of toxicity. The toxicity endpoint is observed in one cycle of therapy (i.e., 4 weeks) while the efficacy endpoint is assessed after 8 weeks of treatment. The difference in endpoint observation windows causes logistical challenges in conducting the trial, since it is not practical to wait until both outcomes for each patient have been fully observed before sequentially assigning the dose of a newly eligible patient. In order to avoid delays in treatment for newly enrolled patients and to accelerate trial progress, we generalize the time-to-event continual reassessment method (TITE-CRM) to bivariate outcomes. Simulation studies are conducted to evaluate the proposed method, and we found that the proposed design is able to accurately select doses that maximize efficacy and have acceptable toxicity, while using all available information in allocating patients at the time of dose assignment. We compare the proposed methodology to two existing methods in the area.

Single arm two-stage studies: Improved designs for molecularly targeted agents

Mechanistic understanding of cancers and their potential interactions with molecularly targeted agents is driving the need for stratified medicine to ensure each participant receives the best possible care. This understanding, backed by scientific research, should be used to guide the design of clinical trials for these agents. The mechanism of action of a molecularly targeted agent often suggests that a biomarker can be used as a predictor of activity of the agent on the targeted disease. A biomarker driven trial is needed to confirm that the molecularly targeted agent stratifies the participant population with disease into high and low responder groups. We assume that the biomarker of interest can be dichotomised and propose a balanced parallel two-stage single-arm phase II trial that builds on existing two-stage single-arm designs. A single-arm trial cannot distinguish between a marker being predictive in the population as a whole and the agent causing an increased response in the marker positive group, but it is a first step. We compare this approach to the existing single-arm approaches, sequential enrichment, tandem two-stage, and parallel two-stage designs, and discuss the advantages and disadvantages of each design. We show that our design compares favourably to existing designs in the Bayesian framework, making a more efficient use of collected data. We recommend using the parallel two-stage balanced or sequential enrichment designs when randomisation is not practical in a phase II trial.

Potential utility of a longitudinal relative dose intensity of molecularly targeted agents in phase 1 dose-finding trials

Phase 1 trials of molecularly targeted agents (MTA) often do not use toxicity data beyond the first cycle of treatment to determine a recommended phase 2 dose (RP2D). We investigated the potential utility of longitudinal relative dose intensity (RDI) that may be a better new way of determining a more accurate RP2D as a lower dose that is presumably more tolerable over the long term without compromising efficacy. All consecutive patients who were initially treated using a single MTA at the conventional RP2D or at one level lower dose (OLLD) of that RP2D in 9 phase 1 trials sponsored by the National Cancer Institute were included. The associations between longitudinal RDI, time to first progression, and response rate were analyzed. The RDI of the conventional RP2D group were maintained a rate of ≥70% throughout 10 cycles, and were higher than those of the OLLD group, although in both groups the RDI gradually decreased with additional treatment cycles. The RP2D group was similar to the OLLD group with respect to time to first progression and response rate. In both groups, however, the decreasing RDI over time was significantly associated with shorter time to first disease progression; therefore, the longitudinal RDI, which takes into account lower grade toxicity occurrences, may be useful in determining a more desirable dose to use in phase 2 and 3 studies.

A Bayesian dose-finding design incorporating toxicity data from multiple treatment cycles

Phase I oncology trials are designed to identify a safe dose with an acceptable toxicity profile. The dose is typically determined based on the probability of severe toxicity observed during the first treatment cycle, although patients continue to receive treatment for multiple cycles. In addition, the toxicity data from multiple types and grades are typically summarized into a single binary outcome of dose-limiting toxicity. A novel endpoint, the total toxicity profile, was previously developed to account for the multiple toxicity types and grades. In this work, we propose to account for longitudinal repeated measures of total toxicity profile over multiple treatment cycles, accounting for cumulative toxicity during dosing-finding. A linear mixed model was utilized in the Bayesian framework, with addition of Bayesian risk functions for decision-making in dose assignment. The performance of this design is evaluated using simulation studies and compared with the previously proposed quasi-likelihood continual reassessment method (QLCRM) design. Twelve clinical scenarios incorporating four different locations of maximum tolerated dose and three different time trends (decreasing, increasing, and no effect) were investigated. The proposed repeated measures design was comparable with the QLCRM when only cycle 1 data were utilized in dose-finding; however, it demonstrated an improvement over the QLCRM when data from multiple cycles were used across all scenarios. Copyright © 2016 John Wiley & Sons, Ltd.