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Use of Rolling-enrollment Designs to Accelerate Clinical Trials


Popular statistical designs, such as CRM (O’Quigley et al., 1990), mTPI-2 (Guo et al., 2017), and i3+3 (Liu et al., 2020) typically enroll patients in cohorts and follow the enrolled cohort for a certain period (e.g., 28 days), and then apply sequential decisions that determine the dose level for each cohort based on the observed toxicity data. Accrual is suspended after enrollment of each cohort of patients until all the patients in the current cohort have been fully followed with definitive dose-limiting toxicity (DLT) or non-DLT outcomes. Cohort-based enrollment can thus slow down dose-finding trials since the outcomes of the previous cohort must be fully evaluated before the next cohort can be enrolled. This type of cohort-based designs can also be inefficient, especially if the trial needs to be frequently suspended. 1

To shorten the study duration of phase I trials and reduce the number of accrual suspensions, use of rolling-enrollment designs is recommended, which allows concurrent patient enrollment that is faster than cohort-base enrollment.

The Rolling 6 design (Skolnik et al., 2008) is a rule-based design that extends the 3+3 design with the aim to reduce the occurrence of accrual suspension after enrolling each set of three patients, thereby accelerating the trial. It allows for accrual of two to six patients concurrently onto a dose level based on the number of patients concurrently enrolled and evaluable, the number experiencing DLT, and the number still at risk of developing a DLT.

Rolling-enrollment designs

Rolling Toxicity Probability Interval (R-TPI) Design

R-TPI Design is a rolling enrollment design that combines the features in model-based designs such as mTPI-2 (Guo et al., 2017) and rule-based designs such as rolling six (Skolnik et al., 2008).

Benchmarking against rolling six, it is found that the R-TPI design is as fast in completing clinical trials but with fewer toxicity events and higher chance of finding the MTD in the single scenario laid out in Skolnik et al. (2008). In a broad setting involving multiple scenarios, R-TPI is generally faster and more reliable than standard designs. It leads to safer trials with fewer toxicity events and maintains relatively a high chance of identifying the MTD. This design can be applied to adult and pediatric phase I trials.

Probability-of-Decision Toxicity Probability Interval Design

The PoD-TPI design (Zhou et al., 2019) is motivated by the need to reduce the frequency of enrollment suspension but while maintaining safety. PoD-TPI enables dose assignment in real time in the presence of pending toxicity outcomes. With uncertain outcomes, the dose assignment decisions are treated as a random variable, and the posterior distribution of the decisions can be calculated. The posterior distribution reflects the variability in the pending outcomes and allows a direct and intuitive evaluation of the confidence of all possible decisions. A new and useful feature of PoD-TPI is that it allows investigators and regulators to balance the trade-off between enrollment speed and making risky decisions by tuning a pair of intuitive design parameters.

Better Decision Making with East Bayes

Cytel is continuing to invest in and improve their flagship East software. Developed by accomplished study design experts, East creates clinical trials that best address key questions confronted by clinical trial sponsors. East Bayes is an enhanced web-based extension of East, that contains the most extensive range of Bayesian and Frequentist dose escalation and dose-finding designs available, including innovative designs such as PoD-TPI. It enables thorough examination and comparison of operating characteristics of different dose finding designs effected by convenient simulations.

By leveraging its powerful range of designs and reporting tools, East Bayes helps clinicians save time, gain confidence in their dose-escalation decisions, increase development productivity, and provides greater opportunity for trial success and patient safety. All the rolling enrollment designs I speak about in this blog are currently available in East Bayes.

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  1. Skolnik, J. M., Barrett, J. S., Jayaraman, B., Patel, D., and Adamson, P. C. (2008). Shortening the timeline of pediatric phase I trials: the rolling six design. Journal of Clinical Oncology, 26(2):190–195.

About Pantelis Vlachos

Pantelis Vlachos photo on black 2018Pantelis is Vice President, Customer Success for Cytel, Inc. based in Geneva. He joined the company in January 2013. Before that, he was a Principal Biostatistician at Merck Serono as well as a Professor of Statistics at Carnegie Mellon University for 12 years. His research interests lie in the area of adaptive designs, mainly from a Bayesian perspective, as well as hierarchical model testing and checking although his secret passion is Text Mining. He has served as Managing Editor of the journal “Bayesian Analysis” as well as editorial boards of several other journals and online statistical data and software archives.


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