bfboinet - Backfill Bayesian Optimal Interval Design Using Efficacy and Toxicity

The backfill Bayesian optimal interval design using efficacy and toxicity outcomes for dose optimization (BF-BOIN-ET) design is a novel clinical trial design to allow patients to be backfilled at lower doses during a dose-finding trial while prioritizing the dose-escalation cohort to explore a higher dose. The advantages compared to the other designs in terms of the percentage of correct optimal dose (OD) selection, reducing the sample size, and shortening the duration of the trial, in various realistic setting.

Last updated 1 months ago

1.30 score 374 downloads

TITEgBOIN - Time-to-Event Dose-Finding Design for Multiple Toxicity Grades

In some phase I trials, the design goal is to find the dose associated with a certain target toxicity rate or the dose with a certain weighted sum of rates of various toxicity grades. 'TITEgBOIN' provides the set up and calculations needed to run a dose-finding trial using bayesian optimal interval (BOIN) (Yuan et al. (2016) <doi:10.1158/1078-0432.CCR-16-0592>), generalized bayesian optimal interval (gBOIN) (Mu et al. (2019) <doi:10.1111/rssc.12263>), time-to-event bayesian optimal interval (TITEBOIN) (Lin et al. (2020) <doi:10.1093/biostatistics/kxz007>) and time-to-event generalized bayesian optimal interval (TITEgBOIN) (Takeda et al. (2022) <doi:10.1002/pst.2182>) designs. 'TITEgBOIN' can conduct tasks: run simulations and get operating characteristics; determine the dose for the next cohort; select maximum tolerated dose (MTD). These functions allow customization of design characteristics to vary sample size, cohort sizes, target dose limiting toxicity (DLT) rates or target normalized equivalent toxicity score (ETS) rates to account for discrete toxicity score, and incorporate safety and/or stopping rules.

Last updated 15 days ago

1.00 score 229 downloads