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相关论文: A Bayesian Precision Response-adaptive Phase II Cl…

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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…

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

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…

统计方法学 · 统计学 2025-05-15 Moka Komaki , Satoru Shinoda , Haiyan Zheng , Kouji Yamamoto

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…

应用统计 · 统计学 2011-08-09 Ying Yuan , Guosheng Yin

An important goal of precision medicine is to personalize medical treatment by identifying individuals who are most likely to benefit from a specific treatment. The Likely Responder (LR) framework, which identifies a subpopulation where…

统计方法学 · 统计学 2026-03-13 Annan Deng , Carole Siegel , Hyung G. Park

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…

统计方法学 · 统计学 2020-02-17 José L. Jiménez , Sungjin Kim , Mourad Tighiouart

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…

统计方法学 · 统计学 2021-08-31 Elja Arjas , Dario Gasbarra

An important task in drug development is to identify patients, which respond better or worse to an experimental treatment. Identifying predictive covariates, which influence the treatment effect and can be used to define subgroups of…

统计方法学 · 统计学 2018-11-27 Marius Thomas , Björn Bornkamp , Katja Ickstadt

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…

统计方法学 · 统计学 2023-05-09 José L. Jiménez , Haiyan Zheng

Precision medicine leverages patient heterogeneity to estimate individualized treatment regimens, formalized, data-driven approaches designed to match patients with optimal treatments. In the presence of competing events, where multiple…

统计方法学 · 统计学 2024-11-14 Christina W. Zhou , Nikki L. B. Freeman , Katharine L. McGinigle , Michael R. Kosorok

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

Determining the extent to which a patient is benefiting from cancer therapy is challenging. Criteria for quantifying the extent of "tumor response" observed within a few cycles of treatment have been established for various types of solid…

统计方法学 · 统计学 2020-09-18 Jie Zhou , Xun Jiang , H. Amy Xia , Peng Wei , Brian P. Hobbs

Identification of optimal dose combinations in early phase dose-finding trials is challenging, due to the trade-off between precisely estimating the many parameters required to flexibly model the possibly non-monotonic dose-response…

统计方法学 · 统计学 2024-02-13 James Willard , Shirin Golchi , Erica E. M. Moodie , Bruno Boulanger , Bradley P. Carlin

Adaptive approaches, allowing for more flexible trial design, have been proposed for individually randomized trials to save time or reduce sample size. However, adaptive designs for cluster-randomized trials in which groups of participants…

统计方法学 · 统计学 2022-01-10 Junwei Shen , Shirin Golchi , Erica E. M. Moodie , David Benrimoh

Targeted therapies on the basis of genomic aberrations analysis of the tumor have shown promising results in cancer prognosis and treatment. Regardless of tumor type, trials that match patients to targeted therapies for their particular…

应用统计 · 统计学 2018-04-18 Yanxun Xu , Peter Mueller , Apostolia M Tsimberidou , Donald Berry

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…

统计方法学 · 统计学 2025-07-17 James M. McGree , Antony M. Overstall , Mark Jones , Robert K. Mahar

In this article, we propose a phase I-II design in two stages for the combination of molecularly targeted therapies. The design is motivated by a published case study that combines a MEK and a PIK3CA inhibitors; a setting in which higher…

统计方法学 · 统计学 2025-05-21 José L. Jiménez , Mourad Tighiouart

In developing products for rare diseases, statistical challenges arise due to the limited number of patients available for participation in drug trials and other clinical research. Bayesian adaptive clinical trial designs offer the…

应用统计 · 统计学 2019-09-19 Xiao Wu , Yi Xu , Bradley P. Carlin

Immunotherapy has transformed cancer treatment, yet its delayed therapeutic effects often lead to non-proportional hazards, rendering many conventional phase II designs underpowered and prone to type I error inflation. To address this…

统计方法学 · 统计学 2025-09-03 Zhongheng Cai , Haitao Pan

Most conventional risk analysis methods rely on a single best estimate of exposure per person which does not allow for adjustment for exposure-related uncertainty. Here, we propose a Bayesian model averaging method to properly quantify the…

应用统计 · 统计学 2020-04-07 Deukwoo Kwon , F. Owen Hoffman , Brian E. Moroz , Steven L. Simon
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