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An individualized treatment rule (ITR) is a decision rule that aims to improve individual patients health outcomes by recommending optimal treatments according to patients specific information. In observational studies, collected data may…

Methodology · Statistics 2023-10-03 Zeyu Bian , Erica EM Moodie , Susan M Shortreed , Sylvie D Lambert , Sahir Bhatnagar

Recent development in the data-driven decision science has seen great advances in individualized decision making. Given data with individual covariates, treatment assignments and outcomes, policy makers best individualized treatment rule…

Machine Learning · Statistics 2020-06-29 Weibin Mo , Zhengling Qi , Yufeng Liu

To promote precision medicine, individualized treatment regimes (ITRs) are crucial for optimizing the expected clinical outcome based on patient-specific characteristics. However, existing ITR research has primarily focused on scenarios…

Methodology · Statistics 2024-02-20 Chang Wang , Lu Wang

Integrative analysis of multiple datasets for estimating optimal individualized treatment rules (ITRs) can enhance decision efficiency. A central challenge is posterior shift, wherein the conditional distribution of potential outcomes given…

Machine Learning · Statistics 2026-03-09 Wenhai Cui , Wen Su , Xingqiu Zhao

In survival contexts, substantial literature exists on estimating optimal treatment regimes, where treatments are assigned based on personal characteristics to maximize the survival probability. These methods assume that a set of covariates…

Methodology · Statistics 2025-07-24 Junwen Xia , Zishu Zhan , Jingxiao Zhang

Individualized treatment rules (ITRs) are considered a promising recipe to deliver better policy interventions. One key ingredient in optimal ITR estimation problems is to estimate the average treatment effect conditional on a subject's…

Methodology · Statistics 2021-03-16 Hongming Pu , Bo Zhang

Precision medicine involves developing individualized treatment regimes (ITRs) which allow for treatment decisions to be tailored to patient characteristics. Naturally, the identification of the optimal regime, that is, the rule which…

Methodology · Statistics 2025-09-30 Misha Dolmatov , Erica E. M. Moodie , David A. Stephens , Dipankar Bandyopadhyay

Learning individualized treatment rules (ITRs) is an important topic in precision medicine. Current literature mainly focuses on deriving ITRs from a single source population. We consider the observational data setting when the source…

Machine Learning · Statistics 2023-07-04 Rui Chen , Jared D. Huling , Guanhua Chen , Menggang Yu

With the emergence of precision medicine, estimating optimal individualized decision rules (IDRs) has attracted tremendous attention in many scientific areas. Most existing literature has focused on finding optimal IDRs that can maximize…

Methodology · Statistics 2022-06-28 Zhengling Qi , Jong-Shi Pang , Yufeng Liu

Precision medicine is an emerging scientific topic for disease treatment and prevention that takes into account individual patient characteristics. It is an important direction for clinical research, and many statistical methods have been…

Methodology · Statistics 2017-02-17 Jingxiang Chen , Haoda Fu , Xuanyao He , Michael R. Kosorok , Yufeng Liu

Individualized treatment rules (ITRs) for treatment recommendation is an important topic for precision medicine as not all beneficial treatments work well for all individuals. Interpretability is a desirable property of ITRs, as it helps…

Methodology · Statistics 2023-11-06 Jacob M. Maronge , Jared D. Huling , Guanhua Chen

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 field of precision medicine aims to tailor treatment based on patient-specific factors in a reproducible way. To this end, estimating an optimal individualized treatment regime (ITR) that recommends treatment decisions based on patient…

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

We develop a mathematical framework to define an optimal individualized treatment rule (ITR) within the context of prioritized outcomes in a randomized controlled trial. Our optimality criterion is based on the framework of generalized…

Methodology · Statistics 2025-06-17 François Petit , Gérard Biau , Raphaël Porcher

Individualized treatment rule (ITR) recommends treatment on the basis of individual patient characteristics and the previous history of applied treatments and their outcomes. Despite the fact there are many ways to estimate ITR with binary…

Methodology · Statistics 2017-08-15 Pavel Shvechikov , Evgeniy Riabenko

Inverse probability of treatment weighting (IPTW) is a popular method for estimating the average treatment effect (ATE). However, empirical studies show that the IPTW estimators can be sensitive to the misspecification of the propensity…

Methodology · Statistics 2021-08-04 Jianqing Fan , Kosuke Imai , Inbeom Lee , Han Liu , Yang Ning , Xiaolin Yang

Individualized treatment rules, cornerstones of precision medicine, inform patient treatment decisions with the goal of optimizing patient outcomes. These rules are generally unknown functions of patients' pre-treatment covariates, meaning…

Methodology · Statistics 2025-04-23 Philippe Boileau , Ning Leng , Sandrine Dudoit

Individualized treatment regimes (ITRs) aim to improve clinical outcomes by assigning treatment based on patient-specific characteristics. However, existing methods often struggle with high-dimensional covariates, limiting accuracy,…

Machine Learning · Statistics 2026-01-13 Sungtaek Son , Eardi Lila , Kwun Chuen Gary Chan

In cluster-randomized trials (CRTs), missing data can occur in various ways, including missing values in outcomes and baseline covariates at the individual or cluster level, or completely missing information for non-participants. Among the…

Methodology · Statistics 2025-11-06 Bingkai Wang , Fan Li , Rui Wang
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