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Related papers: Bayesian adaptive randomization in the I-SPY2 sequ…

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We propose a new sampling algorithm combining two quite powerful ideas in the Markov chain Monte Carlo literature -- adaptive Metropolis sampler and two-stage Metropolis-Hastings sampler. The proposed sampling method will be particularly…

Computation · Statistics 2021-01-05 Anirban Mondal , Kai Yin , Abhijit Mandal

Clinicians and researchers alike are increasingly interested in how best to personalize interventions. A dynamic treatment regimen (DTR) is a sequence of pre-specified decision rules which can be used to guide the delivery of a sequence of…

Randomized Controlled Trials (RCTs) are the gold standard for comparing the effectiveness of a new treatment to the current one (the control). Most RCTs allocate the patients to the treatment group and the control group by uniform…

Machine Learning · Statistics 2018-10-22 Onur Atan , William R. Zame , Mihaela van der Schaar

An important goal of precision medicine is to personalize medical treatment by identifying individuals who are most likely to benefit from a specific treatment. The Likely Responder (LR) framework, which identifies a subpopulation where…

Methodology · Statistics 2026-03-13 Annan Deng , Carole Siegel , Hyung G. Park

This paper considers sequential adaptive estimation of sparse signals under a constraint on the total sensing effort. The advantage of adaptivity in this context is the ability to focus more resources on regions of space where signal…

Methodology · Statistics 2013-04-03 Dennis Wei , Alfred O. Hero

Dynamic treatment regimes (DTRs) are sequences of decision rules to guide treatment assignments in response to a patient's evolving, time-varying disease status. Sequential multiple assignment randomized trials (SMARTs) are considered the…

Methodology · Statistics 2026-04-29 Xinru Wang , Meghna Bose , Bibhas Chakraborty , Robert Mahar

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

The majority of response-adaptive randomisation (RAR) designs in the literature rely on efficacy data to guide dynamic patient allocation. However, their applicability becomes limited in settings where efficacy outcomes, such as survival,…

Methodology · Statistics 2026-02-23 Maria Vittoria Chiaruttini , Lukas Pin , Sofia S. Villar

This paper presents the foundations of a computer oriented approach for preparing a list of random treatment assignments to be adopted in randomised controlled trials. Software is presented which can be applied in the earliest stage of…

Applications · Statistics 2015-02-12 N. S. Santos-Magalhaes , H. M. de Oliveira , A. J. Alves

A dynamic treatment regime is a sequence of medical decisions that adapts to the evolving clinical status of a patient over time. To facilitate personalized care, it is crucial to assess the probability of each available treatment option…

Methodology · Statistics 2024-11-05 Jiefeng Bi , Matteo Borrotti , Bernardo Nipoti

Adaptive interventions, aka dynamic treatment regimens, are sequences of pre-specified decision rules that guide the provision of treatment for an individual given information about their baseline and evolving needs, including in response…

Methodology · Statistics 2024-05-02 Wenchu Pan , Daniel Almirall , Amy M. Kilbourne , Andrew Quanbeck , Lu Wang

We examine three landmark clinical trials -- ECMO, CALGB~49907, and I-SPY~2 -- through a unified Bayesian framework connecting prior specification, sequential adaptation, and decision-theoretic optimisation. For ECMO, the posterior…

Methodology · Statistics 2026-02-12 Alexandra Sokolova , Vadim Sokolov , Nick Polson

Biomarker-guided designs are increasingly used to evaluate personalized treatments based on patients' biomarker status in Phase II and III clinical trials. With adaptive enrichment, these designs can improve the efficiency of evaluating the…

Methodology · Statistics 2024-06-11 Kaiyuan Hua , Hwanhee Hong , Xiaofei Wang

A clustered adaptive intervention (cAI) is a pre-specified sequence of decision rules that guides practitioners on how best - and based on which measures - to tailor cluster-level intervention to improve outcomes at the level of individuals…

Methodology · Statistics 2025-05-05 Yao Song , Kelly Speth , Amy Kilbourne , Andrew Quanbeck , Daniel Almirall , Lu Wang

Optimal designs minimize the number of experimental runs (samples) needed to accurately estimate model parameters, resulting in algorithms that, for instance, efficiently minimize parameter estimate variance. Governed by knowledge of past…

Methodology · Statistics 2023-02-03 Nicholas W. Barendregt , Emily G. Webb , Zachary P. Kilpatrick

Precision oncology aims to prescribe the optimal cancer treatment to the right patients, maximizing therapeutic benefits. However, identifying patient subgroups that may benefit more from experimental cancer treatments based on randomized…

Methodology · Statistics 2026-01-06 Xingyu Li , Qing Liu , Tony Jiang , Hong Amy Xia , Peng Wei , Brian P. Hobbs

In clinical trials, response-adaptive randomization (RAR) has the appealing ability to assign more subjects to better-performing treatments based on interim results. The traditional RAR strategy alters the randomization ratio on a…

Methodology · Statistics 2021-10-01 David Merrell , Thevaa Chandereng , Yeonhee Park

Traditionally, optimization of radiation therapy (RT) treatment plans has been done before the initiation of RT course, using population-wide estimates for patients' response to therapy. However, recent technological advancements have…

Medical Physics · Physics 2021-02-15 Stefan C. M. ten Eikelder , Ali Ajdari , Thomas Bortfeld , Dick den Hertog

In many phase II trials in solid tumours, patients are assessed using endpoints based on the Response Evaluation Criteria in Solid Tumours (RECIST) scale. Often, analyses are based on the response rate. This is the proportion of patients…

Methodology · Statistics 2017-03-02 Chien-Ju Lin , James Wason