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相关论文: PoD-TPI: Probability-of-Decision Toxicity Probabil…

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We consider a Bayesian framework based on "probability of decision" for dose-finding trial designs. The proposed PoD-BIN design evaluates the posterior predictive probabilities of up-and-down decisions. In PoD-BIN, multiple grades of…

统计方法学 · 统计学 2021-03-12 Meizi Liu , Yuan Ji , Ji Lin

In oncology dose-finding trials, due to staggered enrollment, it might be desirable to make dose-assignment decisions in real-time in the presence of pending toxicity outcomes, for example, when the dose-limiting toxicity is late-onset.…

统计方法学 · 统计学 2023-03-13 Tianjian Zhou , Yuan Ji

The landscape of dose-finding designs for phase I clinical trials is rapidly shifting in the recent years, noticeably marked by the emergence of interval-based designs. We categorize them as the iDesigns and the IB-Designs. The iDesigns are…

统计方法学 · 统计学 2017-06-15 Yuan Ji , Shengjie Yang

Oncology dose-finding trials are shifting from identifying the maximum tolerated dose (MTD) to determining the optimal biological dose (OBD), driven by the need for efficient methods that consider both toxicity and efficacy. This is…

统计方法学 · 统计学 2025-04-01 Hao Sun , Jieqi Tu , Revathi Ananthakrishnan , Eunhee Kim

We consider a formal statistical design that allows simultaneous enrollment of a main cohort and a backfill cohort of patients in a dose-finding trial. The goal is to accumulate more information at various doses to facilitate dose…

应用统计 · 统计学 2024-04-03 Jiaxin Liu , Shijie Yuan , B. Nebiyou Bekele , Yuan Ji

We study the problem of learning individualized dose intervals using observational data. There are very few previous works for policy learning with continuous treatment, and all of them focused on recommending an optimal dose rather than an…

统计方法学 · 统计学 2022-02-25 Guanhua Chen , Xiaomao Li , Menggang Yu

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

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…

统计方法学 · 统计学 2013-09-20 Suyu Liu , Ying Yuan

Clinical trials with time-to-event endpoints, such as overall survival (OS) or progression-free survival (PFS), are fundamental for evaluating new treatments, particularly in immuno-oncology. However, modern therapies, such as…

统计方法学 · 统计学 2025-09-10 James Salsbury , Jeremy Oakley , Steven Julious , Lisa Hampson

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…

统计方法学 · 统计学 2018-07-24 Ruitao Lin , Ying Yuan

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

Traditional phase I dose finding cancer clinical trial designs aim to determine the maximum tolerated dose (MTD) of the investigational cytotoxic agent based on a single toxicity outcome, assuming a monotone dose-response relationship.…

统计方法学 · 统计学 2024-11-14 Hao Sun , Hsin-Yu Lin , Jieqi Tu , Revathi Ananthakrishnan , Eunhee Kim

We consider a dose-optimization design for first-in-human oncology trial that aims to identify a suitable dose for late-phase drug development. The proposed approach, called the Pharmacometrics-Enabled DOse OPtimization (PEDOOP) design,…

应用统计 · 统计学 2024-06-19 Shijie Yuan , Zhanbo Huang , Jiaxin Liu , Yuan Ji

Recently, the strategy for dose optimization in oncology has shifted to conduct Phase 2 randomized controlled trials with multiple doses. Optimal biologic dose selection from Phase 1 trial data to determine candidate doses for Phase 2…

统计方法学 · 统计学 2023-02-14 Masahiro Kojima

Immunotherapies and targeted therapies have gained popularity due to their promising therapeutic effects across multiple treatment areas. The focus of early phase dose-finding clinical trials has shifted from finding the maximum tolerated…

统计方法学 · 统计学 2023-12-27 Hao Sun , Jieqi Tu

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

There has been an increasing interest in using interval-based Bayesian designs for dose finding, one of which is the modified toxicity probability interval (mTPI) method. We show that the decision rules in mTPI correspond to an optimal rule…

统计方法学 · 统计学 2016-09-29 Wentian Guo , Sue-Jane Wang , Shengjie Yang , Suiheng Lin , Yuan Ji

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

The use of `backfilling', assigning additional patients to doses deemed safe, in phase I dose-escalation studies has been used in practice to collect additional information on the safety profile, pharmacokinetics and activity of a drug.…

应用统计 · 统计学 2022-04-22 Helen Barnett , Oliver Boix , Dimitris Kontos , Thomas Jaki

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
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