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A dynamic treatment regime is a sequence of decision rules in which each decision rule recommends treatment based on features of patient medical history such as past treatments and outcomes. Existing methods for estimating optimal dynamic…

Methodology · Statistics 2015-05-22 Kristin A. Linn , Eric B. Laber , Leonard A. Stefanski

Health policy decisions regarding patient treatment strategies require consideration of both treatment effectiveness and cost. Optimizing treatment rules with respect to effectiveness may result in prohibitively expensive strategies; on the…

Methodology · Statistics 2021-10-20 Nicholas Illenberger , Andrew J. Spieker , Nandita Mitra

A dynamic treatment regime effectively incorporates both accrued information and long-term effects of treatment from specially designed clinical trials. As these become more and more popular in conjunction with longitudinal data from…

Methodology · Statistics 2011-08-29 Rui Song , Weiwei Wang , Donglin Zeng , Michael R. Kosorok

A dynamic treatment regime is a sequence of treatment decision rules tailored to an individual's evolving status over time. In precision medicine, much focus has been placed on finding an optimal dynamic treatment regime which, if followed…

Other Statistics · Statistics 2025-10-13 Chunyu Wang , Brian DM Tom

Dynamic treatment regimes (DTRs) have received an increasing interest in recent years. DTRs are sequences of treatment decision rules tailored to patient-level information. The main goal of the DTR study is to identify an optimal DTR, a…

Methodology · Statistics 2024-04-09 Dan Liu , Wenqing He

Precision medicine aims to tailor therapeutic decisions to individual patient characteristics. This objective is commonly formalized through dynamic treatment regimes, which use statistical and machine learning methods to derive sequential…

Machine Learning · Statistics 2026-03-23 Sophia Yazzourh , Erica E. M. Moodie

Dynamic treatment regimes operationalize the clinical decision process as a sequence of functions, one for each clinical decision, where each function takes as input up-to-date patient information and gives as output a single recommended…

Methodology · Statistics 2012-08-08 Eric B. Laber , Daniel J. Lizotte , Bradley Ferguson

The sequential treatment decisions made by physicians to treat chronic diseases are formalized in the statistical literature as dynamic treatment regimes. To date, methods for dynamic treatment regimes have been developed under the…

Methodology · Statistics 2022-02-22 Janie Coulombe , Erica E. M. Moodie , Susan M. Shortreed , Christel Renoux

Stabilized dynamic treatment regimes are sequential decision rules for individual patients that not only adaptive throughout the disease progression but also remain consistent over time in format. The estimation of stabilized dynamic…

Methodology · Statistics 2019-03-05 Ying-Qi Zhao , Ruoqing Zhu , Guanhua Chen , Yingye Zheng

The study of precision medicine involves dynamic treatment regimes (DTRs), which are sequences of treatment decision rules recommended by taking patient-level information as input. The primary goal of the DTR study is to identify an optimal…

Methodology · Statistics 2024-12-11 Dan Liu , Wenqing He

Dynamic treatment regimes are sequential decision rules that adapt treatment according to individual time-varying characteristics and outcomes to achieve optimal effects, with applications in precision medicine, personalized…

Methodology · Statistics 2025-10-24 Yuanshan Gao , Yang Bai , Yifan Cui

There has been significant attention given to developing data-driven methods for tailoring patient care based on individual patient characteristics. Dynamic treatment regimes formalize this through a sequence of decision rules that map…

Methodology · Statistics 2022-02-22 Eric J. Rose , Erica E. M. Moodie , Susan Shortreed

The vision for precision medicine is to use individual patient characteristics to inform a personalized treatment plan that leads to the best healthcare possible for each patient. Mobile technologies have an important role to play in this…

Q-learning is a regression-based approach that is widely used to formalize the development of an optimal dynamic treatment strategy. Finite dimensional working models are typically used to estimate certain nuisance parameters, and…

Methodology · Statistics 2020-03-30 Ashkan Ertefaie , James R. McKay , David Oslin , Robert L. Strawderman

Dynamic treatment regimes are of growing interest across the clinical sciences as these regimes provide one way to operationalize and thus inform sequential personalized clinical decision making. A dynamic treatment regime is a sequence of…

Methodology · Statistics 2013-11-27 Eric B. Laber , Min Qian , Dan J. Lizotte , William E. Pelham , Susan A. Murphy

Many policies involve dynamics in their treatment assignments, where individuals receive sequential interventions over multiple stages. We study estimation of an optimal dynamic treatment regime that guides the optimal treatment assignment…

Econometrics · Economics 2024-09-04 Shosei Sakaguchi

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

Dynamic treatment regimes are treatment allocations tailored to heterogeneous individuals. The optimal dynamic treatment regime is a regime that maximizes counterfactual welfare. We introduce a framework in which we can partially learn the…

Econometrics · Economics 2021-07-14 Sukjin Han

Dynamic treatment regimes (DTRs) are personalized, adaptive strategies designed to guide the sequential allocation of treatments based on individual characteristics over time. Before each treatment assignment, covariate information is…

Methodology · Statistics 2025-07-24 Kai Chen , Yuqian Zhang

Dynamic treatment regimes (DTRs) are used in medicine to tailor sequential treatment decisions to patients by considering patient heterogeneity. Common methods for learning optimal DTRs, however, have shortcomings: they are typically based…

Machine Learning · Statistics 2023-06-21 Theresa Blümlein , Joel Persson , Stefan Feuerriegel
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