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The use of drug combinations in clinical trials is increasingly common during the last years since a more favorable therapeutic response may be obtained by combining drugs. In phase I clinical trials, most of the existing methodology…

Methodology · Statistics 2020-02-17 José L. Jiménez , Sungjin Kim , Mourad Tighiouart

We propose a new integrated phase I/II trial design to identify the most efficacious dose combination that also satisfies certain safety requirements for drug-combination trials. We first take a Bayesian copula-type model for dose finding…

Applications · Statistics 2011-08-09 Ying Yuan , Guosheng Yin

Optimal design of a Phase I cancer trial can be formulated as a stochastic optimization problem. By making use of recent advances in approximate dynamic programming to tackle the problem, we develop an approximation of the Bayesian optimal…

Methodology · Statistics 2010-12-01 Jay Bartroff , Tze Leung Lai

Combination of several anti-cancer treatments has typically been presumed to have enhanced drug activity. Motivated by a real clinical trial, this paper considers phase I-II dose finding designs for dual-agent combinations, where one main…

Methodology · Statistics 2023-05-09 José L. Jiménez , Haiyan Zheng

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…

Methodology · Statistics 2013-09-20 Suyu Liu , Ying Yuan

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…

Applications · Statistics 2024-04-03 Cheng-Han Yang , Peter F. Thall , Ruitao Lin

Clinical trials are an integral component of medical research. Trials require careful design to, for example, maintain the safety of participants, use resources efficiently and allow clinically meaningful conclusions to be drawn. Adaptive…

Methodology · Statistics 2025-07-17 James M. McGree , Antony M. Overstall , Mark Jones , Robert K. Mahar

Clinical trials are an instrument for making informed decisions based on evidence from well-designed experiments. Here we consider adaptive designs mainly from the perspective of multi-arm Phase II clinical trials, in which one or more…

Methodology · Statistics 2021-08-31 Elja Arjas , Dario Gasbarra

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…

Applications · Statistics 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…

Methodology · Statistics 2021-11-25 Yunshan Duan , Shijie Yuan , Yuan Ji , Peter Mueller

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,…

Methodology · Statistics 2020-08-18 Burak Kürsad Günhan , Sebastian Weber , Tim Friede

Conventionally, a first-in-human phase I trial in healthy volunteers aims to confirm the safety of a drug in humans. In such situations, volunteers should not suffer from any safety issues and simple algorithm-based dose-escalation schemes…

Phase I-II cancer clinical trial designs are intended to accelerate drug development. In cases where efficacy cannot be ascertained in a short period of time, it is common to divide the study in two stages: i) a first stage in which dose is…

Methodology · Statistics 2022-12-13 José L. Jiménez , Mourad Tighiouart

We propose a two-stage design for a clinical trial with an early stopping rule for safety. We use different criteria to assess early stopping and efficacy. The early stopping rule is based on a criteria that can be determined more quickly…

Methodology · Statistics 2013-07-25 Daniel Zelterman

A general framework is proposed for Bayesian model-based designs of Phase I cancer trials, in which a general criterion for coherence (Cheung, 2005) of a design is also developed. This framework can incorporate both "individual" and…

Methodology · Statistics 2011-08-08 Jay Bartroff , Tze Leung Lai

It is crucial to design Phase II cancer clinical trials that balance the efficiency of treatment selection with clinical practicality. Sargent and Goldberg proposed a frequentist design that allow decision-making even when the primary…

Methodology · Statistics 2025-05-15 Moka Komaki , Satoru Shinoda , Haiyan Zheng , Kouji Yamamoto

Aims: Combinations of treatments can offer additional benefit over the treatments individually. However, trials of these combinations are lower priority than the development of novel therapies, which can restrict funding, timelines and…

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…

Methodology · Statistics 2018-07-24 Ruitao Lin , Ying Yuan

Many phase II clinical trials have used survival outcomes as the primary endpoints in recent decades. Suppose the radiotherapy is evaluated in a phase II trial using survival outcomes. In that case, the competing risk issue often arises…

Applications · Statistics 2022-03-15 Jina Park , Wenjing Hu , Ick Hoon Jin , Hao Liu , Yong Zang

Most statistical tests for treatment effects used in randomized clinical trials with survival outcomes are based on the proportional hazards assumption, which often fails in practice. Data from early exploratory studies may provide evidence…

Statistics Theory · Mathematics 2020-05-28 Andrea Arfé , Brian Alexander , Lorenzo Trippa
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