Practicalities in running early-phase trials using the time-to-event continual reassessment method (TiTE-CRM) for interventions with long toxicity periods using two radiotherapy oncology trials as examples

Abstract

Background: Awareness of model-based designs for dose-finding studies such as the Continual Reassessment Method (CRM) is now becoming more commonplace amongst clinicians, statisticians and trial management staff. In some settings toxicities can occur a long time after treatment has finished, resulting in extremely long, interrupted, CRM design trials. The Time-to-Event CRM (TiTE-CRM), a modification to the original CRM, accounts for the timing of late-onset toxicities and results in shorter trial duration. In this article, we discuss how to design and deliver a trial using this method, from the grant application stage through to dissemination, using two radiotherapy trials as examples.

Methods: The TiTE-CRM encapsulates the dose-toxicity relationship with a statistical model. The model incorporates observed toxicities and uses a weight to account for the proportion of completed follow-up of participants without toxicity. This model uses all available data to determine the next participant's dose and subsequently declare the maximum tolerated dose. We focus on two trials designed by the authors to illustrate practical issues when designing, setting up, and running such studies.

Results: In setting up a TiTE-CRM trial, model parameters need to be defined and the time element involved might cause complications, therefore looking at operating characteristics through simulations is essential. At the grant application stage, we suggest resources to fund statisticians' time before funding is awarded and make recommendations for the level of detail to include in funding applications. While running the trial, close contact of all involved staff is required as a dose decision is made each time a participant is recruited. We suggest ways of capturing data in a timely manner and give example code in R for design and delivery of the trial. Finally, we touch upon dissemination issues while the trial is running and upon completion.

Conclusion: Model-based designs can be complex. We hope this paper will help clinical trial teams to demystify the conduct of TiTE-CRM trials and be a starting point for using this methodology in practice.

Trial registration: ClinicalTrials.gov NCT03641547 NCT01562210.

Keywords: Adaptive trial design; Clinical trial design; Dose-finding; Late toxicity; Phase I; TiTE-CRM.

Conflict of interest statement

RdH declares research grant funding from AstraZeneca to support 3 trials, including the NCT01562210 example used in this paper. All other authors declare that they have no competing interests.

Figures

Fig. 1

Graphic illustration of the TiTECRM method. The first plot shows the recruited participants over time. We illustrate the observation window T for each recruit; y3 has experienced a toxicity hence omitting presenting the full observation window. The dose allocated for participant 5, at the current time point, is decided by accounting for all of the available data, which includes the toxicity status and weights of participants 1–4. These will be accounted for in the calculation of the updated dose-toxicity curve. The table shows the weight that each participant contributes in updating the dose-toxicity curve when participant 5 is recruited onto the trial. Although participant 3 has not completed the observation window, they have experienced a toxicity event, so their contributed weight to the model is 1. The second plot presents the dose allocation for each participant. In this scenario, once a toxicity is observed, the model recommends de-escalating to dose level 2. As participant 4 was not on the trial for long when participant 5 was recruited, the model recommends the same dose for participant 5. This figure reflects the example code and (fictitious) data presented in the Additional file 1