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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

When the early stopping parameter n.earlystop is relatively small or the cohortsize value is not optimized via simulation, it may be better to use p.tox < 1.4 * target.DLT.rate, or try out different cohort sizes, or increase n.earlystop,…

医学物理 · 物理学 2024-03-18 Rong Lu

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

Purpose: The 3+3 design has been shown to be less likely to achieve the objectives of phase I dose-finding trials when compared with more advanced model-based designs. One major criticism of the 3+3 design is that it is based on simple…

统计方法学 · 统计学 2019-04-30 Meizi Liu , Sue-Jane Wang , Yuan Ji

We consider a formal statistical design that allows simultaneous enrollment of a main cohort and a backfill cohort of patients in a dose-finding trial. The goal is to accumulate more information at various doses to facilitate dose…

应用统计 · 统计学 2024-04-03 Jiaxin Liu , Shijie Yuan , B. Nebiyou Bekele , Yuan Ji

We propose a rule-based statistical design for combination dose-finding trials with two agents. The Ci3+3 design is an extension of the i3+3 design with simple decision rules comparing the observed toxicity rates and equivalence intervals…

应用统计 · 统计学 2023-03-29 Shijie Yuan , Tianjian Zhou , Yawen Lin , Yuan Ji

Traditional phase I dose finding cancer clinical trial designs aim to determine the maximum tolerated dose (MTD) of the investigational cytotoxic agent based on a single toxicity outcome, assuming a monotone dose-response relationship.…

统计方法学 · 统计学 2024-11-14 Hao Sun , Hsin-Yu Lin , Jieqi Tu , Revathi Ananthakrishnan , Eunhee Kim

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

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

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

In oncology phase I trials, model-assisted designs have been increasingly adopted because they enable adaptive yet operationally simple dose adjustment based on accumulating safety data, leading to a paradigm shift in dose-escalation…

统计方法学 · 统计学 2026-02-23 Kana Yamada , Hisato Sunami , Kentaro Takeda , Keisuke Hanada , Masahiro Kojima

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

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

We consider a modified Ci3+3 (MCi3+3) design for dual-agent dose-finding trials in which both agents are tested on multiple doses. This usually happens when the agents are novel therapies. The MCi3+3 design offers a two-stage or three-stage…

应用统计 · 统计学 2024-09-05 Jiaxin Liu , Shijie Yuan , Qiqi Deng , Yuan Ji

We consider a Bayesian framework based on "probability of decision" for dose-finding trial designs. The proposed PoD-BIN design evaluates the posterior predictive probabilities of up-and-down decisions. In PoD-BIN, multiple grades of…

统计方法学 · 统计学 2021-03-12 Meizi Liu , Yuan Ji , Ji Lin

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

The traditional more-is-better dose selection paradigm, developed based on cytotoxic chemotherapeutics, is often problematic When applied to the development of novel molecularly targeted agents (e.g., kinase inhibitors, monoclonal…

统计方法学 · 统计学 2022-11-04 Liyun Jiang , Ying Yuan

Two useful strategies to speed up drug development are to increase the patient accrual rate and use novel adaptive designs. Unfortunately, these two strategies often conflict when the evaluation of the outcome cannot keep pace with the…

统计方法学 · 统计学 2018-07-24 Ruitao Lin , Ying Yuan

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

We propose to use Bayesian optimization (BO) to improve the efficiency of the design selection process in clinical trials. BO is a method to optimize expensive black-box functions, by using a regression as a surrogate to guide the search.…

统计方法学 · 统计学 2021-05-20 Jakob Richter , Tim Friede , Jörg Rahnenführer
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