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A dynamic treatment regimen (DTR) is a pre-specified sequence of decision rules which maps baseline or time-varying measurements on an individual to a recommended intervention or set of interventions. Sequential multiple assignment…

Methodology · Statistics 2019-10-23 Brook Luers , Min Qian , Inbal Nahum-Shani , Connie Kasari , Daniel Almirall

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…

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

Cluster-level dynamic treatment regimens can be used to guide sequential, intervention or treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level DTR, the…

Methodology · Statistics 2016-07-15 Timothy NeCamp , Amy Kilbourne , Daniel Almirall

Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients' time-varying clinical conditions. The sequential multiple assignment randomized trial (SMART) is an experimental design that can…

Methodology · Statistics 2024-05-14 Xinru Wang , Nina Deliu , Yusuke Narita , Bibhas Chakraborty

Dynamic treatment regimens (DTRs), also known as treatment algorithms or adaptive interventions, play an increasingly important role in many health domains. DTRs are motivated to address the unique and changing needs of individuals by…

An optimal dynamic treatment regime (DTR) is a sequence of decision rules aimed at providing the best course of treatments individualized to patients. While conventional DTR estimation uses longitudinal data, such data can also be…

Methodology · Statistics 2025-02-06 Larry Dong , Eleanor Pullenayegum , Rodolphe Thiébaut , Olli Saarela

Sequential multiple assignment randomized trials (SMARTs) are used to construct data-driven optimal intervention strategies for subjects based on their intervention and covariate histories in different branches of health and behavioral…

Methodology · Statistics 2022-04-28 Palash Ghosh , Xiaoxi Yan , Bibhas Chakraborty

We propose a flexible joint longitudinal-survival framework to examine the association between longitudinally collected biomarkers and a time-to-event endpoint. More specifically, we use our method for analyzing the survival outcome of…

Applications · Statistics 2018-07-09 Sepehr Akhavan Masouleh , Tracy Holsclaw , Babak Shahbaba , Daniel L. Gillen

The sequential multiple assignment randomized trial (SMART) is the ideal study design for the evaluation of multistage treatment regimes, which comprise sequential decision rules that recommend treatments for a patient at each of a series…

Methodology · Statistics 2024-05-15 Anastasios A. Tsiatis , Marie Davidian

Not only does mobile health technology enable researchers to track changes in multiple longitudinal outcomes of interest and to record the occurrence of health-related events over time, but it also allows for the delivery of repeated…

The individual data collected throughout patient follow-up constitute crucial information for assessing the risk of a clinical event, and eventually for adapting a therapeutic strategy. Joint models and landmark models have been proposed to…

Machine Learning · Statistics 2024-07-17 Anthony Devaux , Robin Genuer , Karine Pérès , Cécile Proust-Lima

Dynamic treatment regimes (DTR) are sequential decision rules corresponding to several stages of intervention. Each rule maps patients' covariates to optional treatments. The optimal dynamic treatment regime is the one that maximizes the…

Methodology · Statistics 2023-10-10 Zhishuai Liu , Zishu Zhan , Jian Liu , Danhui Yi , Cunjie Lin , Yufei Yang

Dynamic treatment regimens (DTRs) aim at tailoring individualized sequential treatment rules that maximize cumulative beneficial outcomes by accommodating patients' heterogeneity in decision-making. For many chronic diseases including type…

Methodology · Statistics 2024-04-23 Mochuan Liu , Yuanjia Wang , Haoda Fu , Donglin Zeng

To achieve the goal of providing the best possible care to each patient, physicians need to customize treatments for patients with the same diagnosis, especially when treating diseases that can progress further and require additional…

Methodology · Statistics 2022-10-25 Xiao Li , Brent R Logan , S M Ferdous Hossain , Erica E M Moodie

Increasing evidence suggests that variability in longitudinal biomarkers, in addition to their mean trajectory, carries prognostic information for time-to-event outcomes. However, standard joint models typically capture only the expected…

Methodology · Statistics 2026-05-08 Felix Boakye Oppong , Dimitris Rizopoulos , Thierry Gorlia , Nicole Erler

Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each stage by potentially time-varying patient features and intermediate outcomes observed in previous stages. The complexity, patient heterogeneity and chronicity…

Methodology · Statistics 2016-11-09 Ying Liu , Yuanjia Wang , Michael R. Kosorok , Yingqi Zhao , Donglin Zeng

One of the main goals of sequential, multiple assignment, randomized trials (SMART) is to find the most efficacious design embedded dynamic treatment regimes. The analysis method known as multiple comparisons with the best (MCB) allows…

Methodology · Statistics 2020-08-07 William J. Artman , Ashkan Ertefaie , Kevin G. Lynch , James R. McKay

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

We are interested in survival analysis of hemodialysis patients for whom several biomarkers are recorded over time. Motivated by this challenging problem, we propose a general framework for multivariate joint longitudinal-survival modeling…

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