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相关论文: Backfilling Cohorts in Phase I Dose-Escalation Stu…

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One common approach for dose optimization is a two-stage design, which initially conducts dose escalation to identify the maximum tolerated dose (MTD), followed by a randomization stage where patients are assigned to two or more doses to…

统计方法学 · 统计学 2024-11-11 Yixuan Zhao , Rachael Liu , Jianchang Lin , 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

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

Phase I dose escalation trials in oncology generally aim to find the maximum tolerated dose (MTD). However, with the advent of molecular targeted therapies and antibody drug conjugates, dose limiting toxicities are less frequently observed,…

统计方法学 · 统计学 2025-08-19 Ayon Mukherjee , Jonathan L. Moscovici , Zheng Liu

Phase I dose-escalation trials constitute the first step in investigating the safety of potentially promising drugs in humans. Conventional methods for phase I dose-escalation trials are based on a single treatment schedule only. More…

应用统计 · 统计学 2021-03-04 Burak Kürsad Günhan , Sebastian Weber , Abdelkader Seroutou , Tim Friede

Phase I oncology trials aim to identify a safe dose - often the maximum tolerated dose (MTD) - for subsequent studies. Conventional designs focus on population-level toxicity modeling, with recent attention on leveraging pharmacokinetic…

应用统计 · 统计学 2026-01-13 Kyong Ju Lee , Yuan Ji

Broadening eligibility criteria in cancer trials has been advocated to represent the true patient population more accurately. While the advantages are clear in terms of generalizability and recruitment, novel dose-finding designs are needed…

应用统计 · 统计学 2023-01-12 Rebecca B. Silva , Bin Cheng , Richard D. Carvajal , Shing M. Lee

Phase I dose-finding trials are increasingly challenging as the relationship between efficacy and toxicity of new compounds (or combination of them) becomes more complex. Despite this, most commonly used methods in practice focus on…

机器学习 · 计算机科学 2020-06-16 Cong Shen , Zhiyang Wang , Sofia S. Villar , Mihaela van der Schaar

An early phase clinical trial is the first step in evaluating the effects in humans of a potential new anti-disease agent or combination of agents. Usually called "phase I" or "phase I/II" trials, these experiments typically have the…

统计方法学 · 统计学 2010-12-01 Peter F. Thall

When a novel treatment has successfully passed phase I, different options to design subsequent phase II trials are available. One approach is a single-arm trial, comparing the response rate in the intervention group against a fixed…

统计方法学 · 统计学 2020-08-03 Johannes Krisam , Dorothea Weber , Richard F. Schlenk , Meinhard Kieser

Phase 1-2 designs provide a methodological advance over phase 1 designs for dose finding by using both clinical response and toxicity. A phase 1-2 trial still may fail to select a truly optimal dose. because early response is not a perfect…

应用统计 · 统计学 2024-04-03 Cheng-Han Yang , Peter F. Thall , Ruitao Lin

Oncology drug development starts with a dose escalation phase to find the maximal tolerable dose (MTD). Dose limiting toxicity (DLT) is the primary endpoint for dose escalation phase. Traditionally, model-based dose escalation trial designs…

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…

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 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

Novel dose-finding designs, using estimation to assign the best estimated maximum- tolerated-dose (MTD) at each point in the experiment, most commonly via Bayesian techniques, have recently entered large-scale implementation in Phase I…

统计方法学 · 统计学 2017-01-24 Assaf P. Oron , Peter D. Hoff

There is a growing interest in the implementation of platform trials, which provide the flexibility to incorporate new treatment arms during the trial and the ability to halt treatments early based on lack of benefit or observed…

统计方法学 · 统计学 2023-08-25 Peter Greenstreet , Thomas Jaki , Alun Bedding , Pavel Mozgunov

Treatment of cancer has rapidly evolved over time in quite dramatic ways, for example from chemotherapies, targeted therapies to immunotherapies and chimeric antigen receptor T-cells. Nonetheless, the basic design of early phase I trials in…

应用统计 · 统计学 2024-12-04 Lukas Andreas Widmer , Sebastian Weber , Yunnan Xu , Hans-Jochen Weber

High dimensional case control studies are ubiquitous in the biological sciences, particularly genomics. To maximise power while constraining cost and to minimise type-1 error rates, researchers typically seek to replicate findings in a…

统计方法学 · 统计学 2017-07-11 James Liley

Dual agent dose-finding trials study the effect of a combination of more than one agent, where the objective is to find the Maximum Tolerated Dose Combination (MTC), the combination of doses of the two agents that is associated with a…

应用统计 · 统计学 2025-02-10 Helen Barnett , Oliver Boix , Dimitris Kontos , Thomas Jaki