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相关论文: Continual Reassessment and Related Dose-Finding De…

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Phase I clinical trials are essential to bringing novel therapies from chemical development to widespread use. Traditional approaches to dose-finding in Phase I trials, such as the '3+3' method and the Continual Reassessment Method (CRM),…

统计方法学 · 统计学 2024-03-04 Luka Kovacevic , Thomas Jaki , Helen Barnett , Pavel Mozgunov

An important tool to evaluate the performance of any design is an optimal benchmark proposed by O'Quigley and others (2002, Biostatistics 3(1), 51-56) that provides an upper bound on the performance of a design under a given scenario. The…

统计理论 · 数学 2018-03-06 Pavel Mozgunov , Thomas Jaki , Xavier Paoletti

The primary object of a phase I clinical trial is to determine the maximum tolerated dose (MTD). Typically, the MTD is identified using a dose-escalation study, where initial subjects are treated at the lowest dose level and subsequent…

统计方法学 · 统计学 2014-05-07 Joseph S. Koopmeiners , Andrew Wey

The study of combinations of drugs/drug-schedules gained increasing attention in various therapeutic areas recently. In oncology, the aim of phase I combination clinical trial is to find the maximum tolerated combination (MTC). Many…

统计方法学 · 统计学 2025-05-09 Weishi Chen , Pavel Mozgunov

Dose-finding trials for oncology studies are traditionally designed to assess safety in the early stages of drug development. With the rise of molecularly targeted therapies and immuno-oncology compounds, biomarker-driven approaches have…

统计方法学 · 统计学 2025-09-15 Xijin Chen , Pavel Mozgunov , Richard D. Baird , Thomas Jaki

This paper proposes a novel criterion for the allocation of patients in Phase~I dose-escalation clinical trials aiming to find the maximum tolerated dose (MTD). Conventionally, using a model-based approach the next patient is allocated to…

统计方法学 · 统计学 2018-07-17 Pavel Mozgunov , Thomas Jaki

Recommendation systems (RecSys) are designed to connect users with relevant items from a vast pool of candidates while aligning with the business goals of the platform. A typical industrial RecSys is composed of two main stages, retrieval…

信息检索 · 计算机科学 2024-12-19 Chi Liu , Jiangxia Cao , Rui Huang , Kuo Cai , Weifeng Ding , Qiang Luo , Kun Gai , Guorui Zhou

Design Research Methodology (DRM) supports systematic design research through representations such as Reference Models and Impact Models. However, the practical construction and maintenance of these models often remains manual, requiring…

软件工程 · 计算机科学 2026-05-12 Apala Chakrabarti

Up-and-Down (U&D) is a popular sequential design for estimating threshold percentiles in binary experiments. However, U&D application practices have stagnated, and significant gaps in understanding its properties persist. The first part of…

统计方法学 · 统计学 2008-08-25 Assaf P. Oron

Phase II dose finding studies in clinical drug development are typically conducted to adequately characterize the dose response relationship of a new drug. An important decision is then on the choice of a suitable dose response function to…

应用统计 · 统计学 2015-08-04 Kirsten Schorning , Björn Bornkamp , Frank Bretz , Holger Dette

An objective of phase I dose-finding trials is to find the maximum tolerated dose; the dose with a particular risk of toxicity. Frequently, this risk is assessed across the first cycle of therapy. However, in oncology, a course of treatment…

应用统计 · 统计学 2021-05-03 Helen Barnett , Oliver Boix , Dimintris Kontos , Thomas Jaki

In traditional dose-finding studies, dose-limiting toxicity (DLT) is determined within a fixed time observation window where DLT is often defined as a binary outcome. In the setting of oncology dose-finding trials, often patients in…

应用统计 · 统计学 2019-09-09 Lucie Biard , Bin Cheng , Gulam A. Manji , Shing M. Lee

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

Large language models (LLMs) have rapidly evolved from text generators into powerful problem solvers. Yet, many open tasks demand critical thinking, multi-source, and verifiable outputs, which are beyond single-shot prompting or standard…

In this paper, we provide a detailed overview of the models used for information retrieval in the first and second stages of the typical processing chain. We discuss the current state-of-the-art models, including methods based on terms,…

信息检索 · 计算机科学 2024-02-16 Kailash A. Hambarde , Hugo Proenca

Dose-finding trials are a key component of the drug development process and rely on a statistical design to help inform dosing decisions. Triallists wishing to choose a design require knowledge of operating characteristics of competing…

统计计算 · 统计学 2025-03-11 Michael Sweeting , Daniel Slade , Dan Jackson , Kristian Brock

In Phase I/II dose-finding trials, the objective is to find the Optimal Biological Dose (OBD), a dose that is both safe and efficacious that maximises some optimality criterion based on safety and efficacy. This is further complicated when…

应用统计 · 统计学 2022-03-31 Helen Barnett , Oliver Boix , Dimitris Kontos , Thomas Jaki

This paper introduces a new Phase I design aimed at enhancing the performance of existing methods, including algorithm-based, model-based, and model-assisted designs. The design, developed by integrating the concept of Fisher information,…

应用统计 · 统计学 2024-12-11 Xiaojun Zhu

Statistical methodology for the design and analysis of clinical Phase II dose response studies, with related software implementation, are well developed for the case of a normally distributed, homoscedastic response considered for a single…

统计方法学 · 统计学 2014-05-09 José Pinheiro , Björn Bornkamp , Ekkehard Glimm , Frank Bretz

Response Surface Methodology (RSM) introduced in the paper (Box & Wilson, 1951) explores the relationships between explanatory and response variables in complex settings and provides a framework to identify correct settings for the…

统计方法学 · 统计学 2020-11-02 Karthik Srinivasan , Amit Kumar , Parameshwaran Iyer , Abhinav Joshi
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