Dataset Information

TEAMS: Toxicity- and Efficacy-based Dose Insertion Design with Adaptive Model Selection for Phase I/II Dose-Escalation Trials in Oncology.

ABSTRACT: In many oncology clinical trials it is necessary to insert new candidate doses when the prespecified doses are poorly elicited. Formal statistical designs with dose insertion are lacking. We propose a dose insertion design for phase I/II clinical trials in oncology based on both efficacy and toxicity outcomes. We also implement Bayesian model selection during the course of the trial so that better models can be adaptively chosen to achieve more accurate inference. The new design, TEAMS, achieves great operating characteristics in extensive simulation studies due to its ability to adaptively insert new doses as well as perform model selection. As a result, appropriate doses are inserted when necessary and desirable doses are selected with higher probabilities at the end of the trial.

SUBMITTER: Guo W

PROVIDER: S-EPMC4627719 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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TEAMS: Toxicity- and Efficacy-based Dose Insertion Design with Adaptive Model Selection for Phase I/II Dose-Escalation Trials in Oncology.

Guo Wentian W Ni Yang Y Ji Yuan Y

Statistics in biosciences 20150630 2

In many oncology clinical trials it is necessary to insert new candidate doses when the prespecified doses are poorly elicited. Formal statistical designs with dose insertion are lacking. We propose a dose insertion design for phase I/II clinical trials in oncology based on both efficacy and toxicity outcomes. We also implement Bayesian model selection during the course of the trial so that better models can be adaptively chosen to achieve more accurate inference. The new design, TEAMS, achieves ...[more]

PMID: 26528377

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Project description:BackgroundA key challenge in phase I trials is maintaining rapid escalation in order to avoid exposing too many patients to sub-therapeutic doses, while preserving safety by limiting the frequency of toxic events. Traditional rule-based designs require temporarily stopping recruitment whilst waiting to see whether enrolled patients develop toxicity. This can be both inefficient and introduces logistic challenges to recruitment in the clinic. We describe a novel two-stage dose assignment procedure designed for a phase I clinical trial (STARPAC), where a good estimation of prior was possible.MethodsThe STARPAC design uses rule-based design until the first patient has a dose limiting toxicity (DLT) and then switches to a modified CRM, with rules to handle patient recruitment during follow-up of earlier patients. STARPAC design is compared via simulations with the TITE-CRM and 3 + 3 methods in various toxicity estimate (T1-5), rate of recruitment (R1-2), and DLT events timing (DT1-4), scenarios using several metrics: accuracy of maximum tolerated dose (MTD), numbers of DLTs, number of patients enrolled and those missed; duration of trial; and proportion of patients treated at the therapeutic dose or MTD.ResultsThe simulations suggest that STARPAC design performed well in MTD estimation and in treating patients at the highest possible therapeutic levels. STARPAC and TITE-CRM were comparable in the number of patients required and DLTs incurred. The 3 + 3 design often had fewer patients and DLTs although this is due to its low escalation rate leading to poor MTD estimation. For the numbers of declined patients and MTD estimation 3 + 3 is uniformly worse, with STARPAC being better in those metrics for high toxicity scenarios and TITE-CRM better with low toxicity. In situations including doses with toxicities both above and below 30%, the STARPAC design outperformed TITE-CRM with respect to every metric.ConclusionWhen considering doses with toxicities both above and below the target of 30% toxicities, the two-stage STARPAC dose escalation design provides a more efficient phase I trial design than either the traditional 3 + 3 or the TITE-CRM design. Trialists should model various designs via simulation to adopt the most efficient design for their clinical scenario.Trial registrationClinical Trials NCT03307148 (11 October 2017).

Dataset Information

TEAMS: Toxicity- and Efficacy-based Dose Insertion Design with Adaptive Model Selection for Phase I/II Dose-Escalation Trials in Oncology.

Publications

TEAMS: Toxicity- and Efficacy-based Dose Insertion Design with Adaptive Model Selection for Phase I/II Dose-Escalation Trials in Oncology.

Similar Datasets

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