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Related papers: The DURATIONS randomised trial design: estimation …

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Background: trials to identify the minimal effective treatment duration are needed in different therapeutic areas, including bacterial infections, TB and Hepatitis--C. However, standard non-inferiority designs have several limitations,…

Background. The DURATIONS design has been recently proposed as a practical alternative to a standard two-arm non-inferiority design when the goal is to optimise some continuous aspect of treatment administration, e.g. duration or frequency,…

Applications · Statistics 2023-04-20 Matteo Quartagno , Ehsan Ghorani , Tim P Morris , Michael J Seckl , Mahesh KB Parmar

Bayesian response adaptive clinical trials are currently evaluating experimental therapies for several diseases. Adaptive decisions, such as pre-planned variations of the randomization probabilities, attempt to accelerate the development of…

Methodology · Statistics 2021-05-25 Marta Bonsaglio , Sandra Fortini , Steffen Ventz , Lorenzo Trippa

Randomized clinical trials are considered the gold standard for estimating causal effects. Nevertheless, in studies that are aimed at examining adverse effects of interventions, such trials are often impractical because of ethical and…

Methodology · Statistics 2020-01-20 Anthony D. Scotina , Andrew R. Zullo , Robert J. Smith , Roee Gutman

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

Platform trials evaluate multiple experimental treatments against a common control group (and/or against each other), which often reduces the trial duration and sample size. Bayesian platform designs offer several practical advantages,…

Methodology · Statistics 2025-07-18 Luke Hagar , Lara Maleyeff , Shirin Golchi , Dick Menzies

The clinical trial process, a critical phase in drug development, is essential for developing new treatments. The primary goal of interventional clinical trials is to evaluate the safety and efficacy of drug-based treatments for specific…

Machine Learning · Computer Science 2024-07-19 Ling Yue , Jonathan Li , Sixue Xing , Md Zabirul Islam , Bolun Xia , Tianfan Fu , Jintai Chen

We develop and evaluate tolerance interval methods for dynamic treatment regimes (DTRs) that can provide more detailed prognostic information to patients who will follow an estimated optimal regime. Although the problem of constructing…

Methodology · Statistics 2017-04-26 Daniel J. Lizotte , Arezoo Tahmasebi

Bootstrap is a widely used technique that allows estimating the properties of a given estimator, such as its bias and standard error. In this paper, we evaluate and compare five bootstrap-based methods for making confidence intervals: two…

Numerous publications have now addressed the principles of designing, analyzing, and reporting the results of, stepped-wedge cluster randomized trials. In contrast, there is little research available pertaining to the design and analysis of…

Methodology · Statistics 2018-06-29 Michael Grayling , Adrian Mander , James Wason

Scheduling surgeries is a challenging task due to the fundamental uncertainty of the clinical environment, as well as the risks and costs associated with under- and over-booking. We investigate neural regression algorithms to estimate the…

Machine Learning · Statistics 2017-07-14 Nathan Ng , Rodney A Gabriel , Julian McAuley , Charles Elkan , Zachary C Lipton

Efficient optimization of operating room (OR) activity poses a significant challenge for hospital managers due to the complex and risky nature of the environment. The traditional "one size fits all" approach to OR scheduling is no longer…

Applications · Statistics 2024-03-21 David Azriel , Yosef Rinott , Orna Tal , Benyamine Abbou , Nadav Rappoport

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…

Methodology · Statistics 2022-01-10 Junwei Shen , Shirin Golchi , Erica E. M. Moodie , David Benrimoh

There are multiple cluster randomised trial designs that vary in when the clusters cross between control and intervention states, when observations are made within clusters, and how many observations are made at that time point. Identifying…

Methodology · Statistics 2023-07-20 Samuel I. Watson , Alan Girling , Karla Hemming

Most Bayesian response-adaptive designs unbalance randomization rates towards the most promising arms with the goal of increasing the number of positive treatment outcomes during the study, even though the primary aim of the trial is…

Applications · Statistics 2018-07-02 Steffen Ventz , Matteo Cellamare , Sergio Bacallado , Lorenzo Trippa

In precision medicine, Dynamic Treatment Regimes (DTRs) are treatment protocols that adapt over time in response to a patient's observed characteristics. A DTR is a set of decision functions that takes an individual patient's information as…

Methodology · Statistics 2022-03-17 Cong Jiang , Michael Wallace , Mary Thompson

In this paper, we study pooling downstream beds across specialties in a stochastic operating room planning problem. The main sources of uncertainty are stochastic surgical durations and patients' lengths of stay. We developed a two-stage…

Optimization and Control · Mathematics 2026-02-18 Arian Andam , Hossein Hashemi Doulabi

Practical employment of Bayesian trial designs is still rare. Even if accepted in principle, the regulators have commonly required that such designs be calibrated according to an upper bound for the frequentist type I error rate. This…

Methodology · Statistics 2026-03-25 Elja Arjas , Dario Gasbarra

This paper proposes a new non-parametric bootstrap method to quantify the uncertainty of average treatment effect estimate for the treated from matching estimators. More specifically, it seeks to quantify the uncertainty associated with the…

Methodology · Statistics 2024-08-21 Jing Li

Significant evidence has become available that emphasizes the importance of personalization in medicine. In fact, it has become a common belief that personalized medicine is the future of medicine. The core of personalized medicine is the…

Methodology · Statistics 2020-04-30 Qiong Zhang , Amin Khademi , Yongjia Song
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