English
Related papers

Related papers: Variable Selection for Individualized Treatment Ru…

200 papers

An individualized treatment regime (ITR) is a decision rule that assigns treatments based on patients' characteristics. The value function of an ITR is the expected outcome in a counterfactual world had this ITR been implemented. Recently,…

Methodology · Statistics 2023-01-16 Pan Zhao , Julie Josse , Shu Yang

Individualized treatment rules/recommendations (ITRs) aim to improve patient outcomes by tailoring treatments to the characteristics of each individual. However, when there are many treatment groups, existing methods face significant…

Methodology · Statistics 2025-05-27 Ke Zhu , Jianing Chu , Ilya Lipkovich , Wenyu Ye , Shu Yang

The individualized treatment rule (ITR), which recommends an optimal treatment based on individual characteristics, has drawn considerable interest from many areas such as precision medicine, personalized education, and personalized…

Methodology · Statistics 2023-09-28 Qi Xu , Haoda Fu , Annie Qu

Multistate process data are common in studies of chronic diseases such as cancer. These data are ideal for precision medicine purposes as they can be leveraged to improve more refined health outcomes, compared to standard survival outcomes,…

Methodology · Statistics 2022-11-28 Giorgos Bakoyannis

Personalized medicine has received increasing attention among statisticians, computer scientists, and clinical practitioners. A major component of personalized medicine is the estimation of individualized treatment rules (ITRs). Recently,…

Methodology · Statistics 2015-08-14 Xin Zhou , Nicole Mayer-Hamblett , Umer Khan , Michael R. Kosorok

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

One primary goal of precision medicine is to estimate the individualized treatment rules (ITRs) that optimize patients' health outcomes based on individual characteristics. Health studies with multiple treatments are commonly seen in…

Methodology · Statistics 2025-05-07 Xuqiao Li , Qiuyan Zhou , Ying Wu , Ying Yan

Identifying patients who benefit from a treatment is a key aspect of personalized medicine, which allows the development of individualized treatment rules (ITRs). Many machine learning methods have been proposed to create such rules.…

Medical treatments tailored to a patient's baseline characteristics hold the potential of improving patient outcomes while reducing negative side effects. Learning individualized treatment rules (ITRs) often requires aggregation of multiple…

Machine Learning · Statistics 2022-12-15 Jay Jojo Cheng , Jared D. Huling , Guanhua Chen

Estimating individualized treatment rules (ITRs) is fundamental to precision medicine, where the goal is to tailor treatment decisions to individual patient characteristics. While numerous methods have been developed for ITR estimation,…

Methodology · Statistics 2026-05-15 Eun Jeong Oh , Min Qian

In many decision-making problems, the primary outcome is expensive, time-consuming, or difficult to observe, so individualized treatment rules (ITRs) may be instead learned from surrogate endpoints. However, a surrogate that is highly…

Methodology · Statistics 2026-04-13 Zeyu Xu , Xiaojie Mao , Hao Mei , Yue Liu

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

Personalized medicine has gained much popularity recently as a way of providing better healthcare by tailoring treatments to suit individuals. Our research, motivated by the UK INTERVAL blood donation trial, focuses on estimating the…

Methodology · Statistics 2023-02-24 Yuejia Xu , Angela M. Wood , David J. Roberts , Brian D. M. Tom

In this paper, we outline a principled approach to estimate an individualized treatment rule that is appropriate for data from observational studies where, in addition to treatment assignment not being independent of individual…

Methodology · Statistics 2019-06-05 Jeremy Roth , Noah Simon

In recent years, there has been a growing interest in the prediction of individualized treatment effects. While there is a rapidly growing literature on the development of such models, there is little literature on the evaluation of their…

Methodology · Statistics 2023-12-22 J Hoogland , O Efthimiou , TL Nguyen , TPA Debray

Individualized treatment rules (ITRs) have been widely applied in many fields such as precision medicine and personalized marketing. Beyond the extensive studies on ITR for binary or multiple treatments, there is considerable interest in…

Methodology · Statistics 2024-03-08 Qi Xu , Xiaoke Cao , Geping Chen , Hanqi Zeng , Haoda Fu , Annie Qu

Background: Adaptive interventions provide a guide for using ongoing information about individuals to decide whether and how to modify the type, amount, delivery modality, or timing of treatment, to improve intervention effectiveness while…

Methodology · Statistics 2026-03-12 John J. Dziak , Inbal Nahum-Shani

The complexity of human cancer often results in significant heterogeneity in response to treatment. Precision medicine offers potential to improve patient outcomes by leveraging this heterogeneity. Individualized treatment rules (ITRs)…

Individualized treatment rules (ITRs) have gained significant attention due to their wide-ranging applications in fields such as precision medicine, ridesharing, and advertising recommendations. However, when ITRs are influenced by…

Machine Learning · Statistics 2025-08-01 Wenhai Cui , Xiaoting Ji , Wen Su , Xiaodong Yan , Xingqiu Zhao

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