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Estimating dynamic treatment regimes (DTRs) from retrospective observational data is challenging as some degree of unmeasured confounding is often expected. In this work, we develop a framework of estimating properly defined "optimal" DTRs…

Methodology · Statistics 2021-04-19 Shuxiao Chen , Bo Zhang

Dynamic treatment regimes (DTRs) are critical to precision medicine, optimizing long-term outcomes through personalized, real-time decision-making in evolving clinical contexts, but require careful supervision for unsafe treatment risks.…

Machine Learning · Computer Science 2025-06-10 Yishan Shen , Yuyang Ye , Hui Xiong , Yong Chen

Studies often report estimates of the average treatment effect. While the ATE summarizes the effect of a treatment on average, it does not provide any information about the effect of treatment within any individual. A treatment strategy…

Methodology · Statistics 2025-06-13 Nicholas T. Williams , Katherine L. Hoffman Iván Díaz , Kara E. Rudolph

Dynamic Treatment Regimes (DTRs) provide a systematic framework for optimizing sequential decision-making in chronic disease management, where therapies must adapt to patients' evolving clinical profiles. Inverse probability weighting (IPW)…

Methodology · Statistics 2026-03-26 Chloe Si , David A. Stephens , Erica E. M. Moodie

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

Personalized intervention strategies, in particular those that modify treatment based on a participant's own response, are a core component of precision medicine approaches. Sequential Multiple Assignment Randomized Trials (SMARTs) are…

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

Mobile health is a rapidly developing field in which behavioral treatments are delivered to individuals via wearables or smartphones to facilitate health-related behavior change. Micro-randomized trials (MRT) are an experimental design for…

Methodology · Statistics 2019-05-13 Tianchen Qian , Predrag Klasnja , Susan A. Murphy

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

Precision medicine incorporates patient-level covariates to tailor treatment decisions, seeking to improve outcomes. In longitudinal studies with time-varying covariates and sequential treatment decisions, precision medicine can be…

Methodology · Statistics 2020-08-05 Dylan Spicker , Michael Wallace

Optimal dynamic treatment regimes (DTRs), as a key part of precision medicine, have progressively gained more attention recently. To inform clinical decision making, interpretable and parsimonious models for contrast functions are…

Methodology · Statistics 2025-12-08 Chunyu Wang , Brian Tom

A dynamic treatment regime (DTR) is an approach to delivering precision medicine that uses patient characteristics to guide treatment decisions for optimal health outcomes. Numerous methods have been proposed for DTR estimation, including…

Methodology · Statistics 2025-02-03 Adel Ahmadi Nadi , Michael Wallace

In the rapidly changing healthcare landscape, the implementation of offline reinforcement learning (RL) in dynamic treatment regimes (DTRs) presents a mix of unprecedented opportunities and challenges. This position paper offers a critical…

Machine Learning · Computer Science 2024-06-05 Zhiyao Luo , Yangchen Pan , Peter Watkinson , Tingting Zhu

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

Public policies and medical interventions often involve dynamic treatment assignments, in which individuals receive a sequence of interventions over multiple stages. We study the statistical learning of optimal dynamic treatment regimes…

Methodology · Statistics 2025-05-21 Shosei Sakaguchi

Sequential, multiple assignment randomized trials (SMARTs), which assist in the optimization of adaptive interventions, are growing in popularity in education and behavioral sciences. This is unsurprising, as adaptive interventions reflect…

Methodology · Statistics 2023-09-26 Timothy Lycurgus , Amy Kilbourne , Daniel Almirall

Dynamic treatment regimes (DTRs) are sequences of functions that formalize the process of precision medicine. DTRs take as input patient information and output treatment recommendations. A major focus of the DTR literature has been on the…

Methodology · Statistics 2024-02-21 Dylan Spicker , Michael P. Wallace , Grace Y. Yi

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

Adaptive interventions (AIs) are increasingly becoming popular in medical and behavioral sciences. An AI is a sequence of individualized intervention options that specify for whom and under what conditions different intervention options…

Applications · Statistics 2018-12-18 Palash Ghosh , Inbal Nahum-Shani , Bonnie Spring , Bibhas Chakraborty

Dynamic Treatment Regimes (DTRs) provide a systematic approach for making sequential treatment decisions that adapt to individual patient characteristics, particularly in clinical contexts where survival outcomes are of interest.…

Machine Learning · Computer Science 2025-03-11 Animesh Kumar Paul , Russell Greiner