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In their paper, Zhang et al 1 propose further extensions of the Bayesian Logistic Regression Model (BLRM) with overdose control for dose-escalation studies of a novel drug. These extensions aim… Click to show full abstract
In their paper, Zhang et al 1 propose further extensions of the Bayesian Logistic Regression Model (BLRM) with overdose control for dose-escalation studies of a novel drug. These extensions aim to reduce the risk of underdosing trial participants and improve accuracy of Maximum Tolerated Dose (MTD) estimation. While their results show that the designs proposed improve MTD estimation accuracy compared to the original BLRM approach, the authors also raise important points on the most appropriate strategy to estimate the MTD in a dose-escalation study for a particular clinical scenario.
Journal Title: Statistics in Medicine
Year Published: 2022
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