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Cohort-based enrollment can slow down dose-finding trials since the outcomes of the previous cohort must be fully evaluated before the next cohort can be enrolled. This results in frequent suspension of patient enrollment. The issue is…

应用统计 · 统计学 2020-01-01 Tianjian Zhou , Wentian Guo , Yuan Ji

Interval designs are a class of phase I trial designs for which the decision of dose assignment is determined by comparing the observed toxicity rate at the current dose with a prespecified (toxicity tolerance) interval. If the observed…

统计方法学 · 统计学 2013-09-20 Suyu Liu , Ying Yuan

In phase I dose escalation studies for dual-agent combinations, at least one drug often has an established monotherapy dose. Consequently, substantial prior clinical safety data often exist for one or more monotherapies, allowing the study…

统计方法学 · 统计学 2026-05-07 Yuxuan Chen , Haiming Zhou , Keiko Nakajima , Philip He

In oncology dose-finding trials, due to staggered enrollment, it might be desirable to make dose-assignment decisions in real-time in the presence of pending toxicity outcomes, for example, when the dose-limiting toxicity is late-onset.…

统计方法学 · 统计学 2023-03-13 Tianjian Zhou , Yuan Ji

We propose an adaptive design for early phase drug combination cancer trials with the goal of estimating the maximum tolerated dose (MTD). A nonparametric Bayesian model, using beta priors truncated to the set of partially ordered dose…

应用统计 · 统计学 2019-10-22 Zahra S. Razaee , Galen Wien-Cook , Mourad Tighiouart

We propose a Bayesian optimal phase 2 design for jointly monitoring efficacy and toxicity, referred to as BOP2-TE, to improve the operating characteristics of the BOP2 design proposed by Zhou et al. (2017). BOP2-TE utilizes a…

统计方法学 · 统计学 2024-08-13 Kai Chen , Heng Zhou , J. Jack Lee , Ying Yuan

Dose-finding clinical trials in oncology aim to determine the maximum tolerated dose (MTD) of a new drug, generally defined by the proportion of patients with short-term dose-limiting toxicities (DLTs). Model-based approaches for such phase…

统计方法学 · 统计学 2020-12-08 Moreno Ursino , Lucie Biard , Sylvie Chevret

The US Food and Drug Administration (FDA) launched Project Optimus and issued guidance to reform dose-finding and selection trials, shifting the paradigm from identifying the maximum tolerable dose (MTD) to determining the optimal…

统计方法学 · 统计学 2025-09-16 Kai Chen , Yixuan Zhao , Kentaro Takeda , Ying Yuan

Immunotherapies and targeted therapies have gained popularity due to their promising therapeutic effects across multiple treatment areas. The focus of early phase dose-finding clinical trials has shifted from finding the maximum tolerated…

统计方法学 · 统计学 2023-12-27 Hao Sun , Jieqi Tu

Oncology dose-finding trials are shifting from identifying the maximum tolerated dose (MTD) to determining the optimal biological dose (OBD), driven by the need for efficient methods that consider both toxicity and efficacy. This is…

统计方法学 · 统计学 2025-04-01 Hao Sun , Jieqi Tu , Revathi Ananthakrishnan , Eunhee Kim

The purpose of a phase I dose-finding clinical trial is to investigate the toxicity profiles of various doses for a new drug and identify the maximum tolerated dose. Over the past three decades, various dose-finding designs have been…

统计方法学 · 统计学 2021-11-25 Yunshan Duan , Shijie Yuan , Yuan Ji , Peter Mueller

Early phase, personalized dose-finding trials for combination therapies seek to identify patient-specific optimal biological dose (OBD) combinations, which are defined as safe dose combinations which maximize therapeutic benefit for a…

统计方法学 · 统计学 2024-04-18 James Willard , Shirin Golchi , Erica EM Moodie

Model-assisted designs have garnered significant attention in recent years due to their high accuracy in identifying the maximum tolerated dose (MTD) and their operational simplicity. To identify the MTD, they employ estimated dose limiting…

应用统计 · 统计学 2025-08-19 Rentaro Wakayama , Tomotaka Momozaki , Shuji Ando

The primary goal of a two-stage Phase I/II trial is to identify the optimal dose for the following large-scale Phase III trial. Recently, Phase I dose-finding designs have shifted from identifying the maximum tolerated dose (MTD) to the…

统计方法学 · 统计学 2025-01-16 Hao Sun , Jerry Li

Phase I dose-finding trials in oncology seek to find the maximum tolerated dose (MTD) of a drug under a specific schedule. Evaluating drug-schedules aims at improving treatment safety while maintaining efficacy. However, while we can…

Purpose: The early identification of maximum tolerated dose (MTD) in phase I trial leads to faster progression to a phase II trial or an expansion cohort to confirm efficacy. Methods: We propose a novel adaptive design for identifying MTD…

统计方法学 · 统计学 2021-10-07 Masahiro Kojima

The landscape of dose-finding designs for phase I clinical trials is rapidly shifting in the recent years, noticeably marked by the emergence of interval-based designs. We categorize them as the iDesigns and the IB-Designs. The iDesigns are…

统计方法学 · 统计学 2017-06-15 Yuan Ji , Shengjie Yang

Phase I clinical trials are designed to test the safety (non-toxicity) of drugs and find the maximum tolerated dose (MTD). This task becomes significantly more challenging when multiple-drug dose-combinations (DC) are involved, due to the…

机器学习 · 计算机科学 2021-01-27 Hyun-Suk Lee , Cong Shen , William Zame , Jang-Won Lee , Mihaela van der Schaar

Phase I dose-escalation trials must be guided by a safety model in order to avoid exposing patients to unacceptably high risk of toxicities. Traditionally, these trials are based on one type of schedule. In more recent practice, however,…

统计方法学 · 统计学 2020-08-18 Burak Kürsad Günhan , Sebastian Weber , Tim Friede

In the development of new cancer treatment, an essential step is to determine the maximum tolerated dose (MTD) via phase I clinical trials. Generally speaking, phase I trial designs can be classified as either model-based or algorithm-based…

应用统计 · 统计学 2022-03-02 Huaqing Jin , Wenbin Du , Guosheng Yin
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