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An accurately identified maximum tolerated dose (MTD) serves as the cornerstone of successful subsequent phases in oncology drug development. Bayesian logistic regression model (BLRM) is a popular and versatile model-based dose-finding…

Methodology · Statistics 2021-05-17 Hongtao Zhang , Alan Y Chiang , Jixian Wang

Personalized cancer treatments based on the molecular profile of a patient's tumor are an emerging and exciting class of treatments in oncology. As genomic tumor profiling is becoming more common, targeted treatments to specific molecular…

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…

Methodology · Statistics 2024-08-13 Kai Chen , Heng Zhou , J. Jack Lee , Ying Yuan

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…

Applications · Statistics 2023-01-12 Rebecca B. Silva , Bin Cheng , Richard D. Carvajal , Shing M. Lee

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,…

Methodology · Statistics 2025-08-19 Ayon Mukherjee , Jonathan L. Moscovici , Zheng Liu

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…

Methodology · Statistics 2024-02-13 James Willard , Shirin Golchi , Erica E. M. Moodie , Bruno Boulanger , Bradley P. Carlin

Accurate models of clinical actions and their impacts on disease progression are critical for estimating personalized optimal dynamic treatment regimes (DTRs) in medical/health research, especially in managing chronic conditions.…

Methodology · Statistics 2021-02-19 William Hua , Hongyuan Mei , Sarah Zohar , Magali Giral , Yanxun Xu

It is increasingly common for therapies in oncology to be given in combination. In some cases, patients can benefit from the interaction between two drugs, although often at the risk of higher toxicity. A large number of designs to conduct…

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

The conventional more-is-better dose selection paradigm, which targets the maximum tolerated dose (MTD), is not suitable for the development of targeted therapies and immunotherapies as the efficacy of these novel therapies may not increase…

Methodology · Statistics 2023-08-31 Peng Yang , Daniel Li , Ruitao Lin , Bo Huang , Ying Yuan

The primary goal of dose allocation in phase I trials is to minimize patient exposure to subtherapeutic or excessively toxic doses, while accurately recommending a phase II dose that is as close as possible to the maximum tolerated dose…

Methodology · Statistics 2025-03-21 Jiapeng Xu , Dehua Bi , Shenghua Kelly Fan , Bee Leng Lee , Ying Lu

The main objective of dose finding trials is to find an optimal dose amongst a candidate set for further research. The trial design in oncology proceeds in stages with a decision as to how to treat the next group of patients made at every…

Methodology · Statistics 2025-10-21 Andrew Hall , Duncan Wilson , Stuart Barber , Sarah R Brown

The primary objective of phase I oncology studies is to establish the safety profile of a new treatment and determine the maximum tolerated dose (MTD). This is motivated by the development of cytotoxic agents based on the underlying…

Applications · Statistics 2023-02-10 Yiding Zhang , Zhixing Xu , Hui Quan , Ji Lin

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…

Methodology · Statistics 2021-10-07 Masahiro Kojima

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…

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

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…

Methodology · Statistics 2017-01-24 Assaf P. Oron , Peter D. Hoff

There is wide interest in studying how the distribution of a continuous response changes with a predictor. We are motivated by environmental applications in which the predictor is the dose of an exposure and the response is a health…

Methodology · Statistics 2018-05-10 Antonio Canale , Daniele Durante , David Dunson

Exploratory cancer drug studies test multiple tumor cell lines against multiple candidate drugs. The goal in each paired (cell line, drug) experiment is to map out the dose-response curve of the cell line as the dose level of the drug…

Machine Learning · Statistics 2021-03-23 Wesley Tansey , Christopher Tosh , David M. Blei

Imaging in clinical oncology trials provides a wealth of information that contributes to the drug development process, especially in early phase studies. This paper focuses on kinetic modeling in DCE-MRI, inspired by mixed-effects models…

Applications · Statistics 2020-04-22 Volker J. Schmid , Brandon Whitcher , Anwar R. Padhani , N. Jane Taylor , Guang-Zhong Yang