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Keyboard: A Novel Bayesian Toxicity Probability Interval Design for Phase I Clinical Trials.

ABSTRACT: The primary objective of phase I oncology trials is to find the MTD. The 3+3 design is easy to implement but performs poorly in finding the MTD. A newer design, such as the modified toxicity probability interval (mTPI) design, provides better accuracy to identify the MTD but tends to overdose patients. We propose the keyboard design, an intuitive Bayesian design that conducts dose escalation and de-escalation based on whether the strongest key, defined as the dosing interval that most likely contains the current dose, is below or above the target dosing interval. The keyboard design can be implemented in a simple way, similar to the traditional 3+3 design, but provides more flexibility for choosing the target toxicity rate and cohort size. Our simulation studies demonstrate that compared with the 3+3 design, the keyboard design has favorable operating characteristics in terms of identifying the MTD. Compared with the mTPI design, the keyboard design is safer, with a substantially lower risk of treating patients at overly toxic doses, and has the better precision to identify the MTD, thereby providing a useful upgrade to the mTPI design. Software freely available at http://www.trialdesign.org facilitates the application of the keyboard design. Clin Cancer Res; 23(15); 3994-4003. ©2017 AACRSee related commentary by Paoletti et al., p. 3977.

SUBMITTER: Yan F

PROVIDER: S-EPMC5554436 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Keyboard: A Novel Bayesian Toxicity Probability Interval Design for Phase I Clinical Trials.

Yan Fangrong F Mandrekar Sumithra J SJ Yuan Ying Y

Clinical cancer research : an official journal of the American Association for Cancer Research 20170525 15

The primary objective of phase I oncology trials is to find the MTD. The 3+3 design is easy to implement but performs poorly in finding the MTD. A newer design, such as the modified toxicity probability interval (mTPI) design, provides better accuracy to identify the MTD but tends to overdose patients. We propose the keyboard design, an intuitive Bayesian design that conducts dose escalation and de-escalation based on whether the strongest key, defined as the dosing interval that most likely con ...[more]

PMID: 28546227

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Project description:BackgroundRandomized controlled trials are considered the gold standard for evaluating experimental treatments but often require large sample sizes. Single-arm trials require smaller sample sizes but are subject to bias when using historical control data for comparative inferences. This article presents a Bayesian adaptive synthetic-control design that exploits historical control data to create a hybrid of a single-arm trial and a randomized controlled trial.MethodsThe Bayesian adaptive synthetic control design has two stages. In stage 1, a prespecified number of patients are enrolled in a single arm given the experimental treatment. Based on the stage 1 data, applying propensity score matching and Bayesian posterior prediction methods, the usefulness of the historical control data for identifying a pseudo sample of matched synthetic-control patients for making comparative inferences is evaluated. If a sufficient number of synthetic controls can be identified, the single-arm trial is continued. If not, the trial is switched to a randomized controlled trial. The performance of The Bayesian adaptive synthetic control design is evaluated by computer simulation.ResultsThe Bayesian adaptive synthetic control design achieves power and unbiasedness similar to a randomized controlled trial but on average requires a much smaller sample size, provided that the historical control data patients are sufficiently comparable to the trial patients so that a good number of matched controls can be identified in the historical control data. Compared to a single-arm trial, The Bayesian adaptive synthetic control design yields much higher power and much smaller bias.ConclusionThe Bayesian adaptive synthetic-control design provides a useful tool for exploiting historical control data to improve the efficiency of single-arm phase II clinical trials, while addressing the problem of bias when comparing trial results to historical control data. The proposed design achieves power similar to a randomized controlled trial but may require a substantially smaller sample size.

Dataset Information

Keyboard: A Novel Bayesian Toxicity Probability Interval Design for Phase I Clinical Trials.

Publications

Keyboard: A Novel Bayesian Toxicity Probability Interval Design for Phase I Clinical Trials.

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