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相关论文: Statistical Frameworks for Oncology Dose-Finding D…

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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

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

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

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 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

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

Cohort-based enrollment can slow down dose-finding trials since the outcomes of the previous cohort must be fully evaluated before the next cohort can be enrolled. This results in frequent suspension of patient enrollment. The issue is…

应用统计 · 统计学 2020-01-01 Tianjian Zhou , Wentian Guo , Yuan Ji

Dual agent dose-finding trials study the effect of a combination of more than one agent, where the objective is to find the Maximum Tolerated Dose Combination (MTC), the combination of doses of the two agents that is associated with a…

应用统计 · 统计学 2025-02-10 Helen Barnett , Oliver Boix , Dimitris Kontos , Thomas Jaki

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

Safety evaluation is an essential component of clinical trials. To protect study participants, these studies often implement safety stopping rules that will halt the trial if an excessive number of toxicity events occur. Existing safety…

统计方法学 · 统计学 2025-10-06 Michael J. Martens , Qinghua Lian , Brent R. Logan

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

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…

统计方法学 · 统计学 2024-08-13 Kai Chen , Heng Zhou , J. Jack Lee , Ying Yuan

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 construct optimal designs for estimating fetal malformation rate, prenatal death rate and an overall toxicity index in a toxicology study under a broad range of model assumptions. We use Weibull distributions to model these rates and…

统计方法学 · 统计学 2009-02-10 Holger Dette , Andrey Pepelyshev , Weng Kee Wong

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

Dose-finding clinical trials in oncology aim to determine the maximum tolerated dose (MTD) of a new drug, generally defined by the proportion of patients with short-term dose-limiting toxicities (DLTs). Model-based approaches for such phase…

统计方法学 · 统计学 2020-12-08 Moreno Ursino , Lucie Biard , Sylvie Chevret

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

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,…

统计方法学 · 统计学 2020-08-18 Burak Kürsad Günhan , Sebastian Weber , Tim Friede

Treatment of cancer has rapidly evolved over time in quite dramatic ways, for example from chemotherapies, targeted therapies to immunotherapies and chimeric antigen receptor T-cells. Nonetheless, the basic design of early phase I trials in…

应用统计 · 统计学 2024-12-04 Lukas Andreas Widmer , Sebastian Weber , Yunnan Xu , Hans-Jochen Weber

Designing modern oncology trials requires synthesizing evidence from prior studies to inform hypothesis generation and sample size determination. Trial designs based on incomplete or imprecise summaries can lead to misspecified hypotheses…

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