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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

In precision medicine, one of the most important problems is estimating the optimal individualized treatment rules (ITR), which typically involves recommending treatment decisions based on fully observed individual characteristics of…

Methodology · Statistics 2025-10-15 Yue Zhang , Shanshan Luo , Zhi Geng , Yangbo He

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

Randomized Controlled Trials (RCT) are the current gold standards to empirically measure the effect of a new drug. However, they may be of limited size and resorting to complementary non-randomized data, referred to as observational, is…

Methodology · Statistics 2025-06-11 Ahmed Boughdiri , Julie Josse , Erwan Scornet

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

Estimation and evaluation of individualized treatment rules have been studied extensively, but real-world treatment resource constraints have received limited attention in existing methods. We investigate a setting in which treatment is…

Methodology · Statistics 2022-11-24 Hongxiang Qiu , Marco Carone , Alex Luedtke

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

Data-driven individualized decision making has recently received increasing research interests. Most existing methods rely on the assumption of no unmeasured confounding, which unfortunately cannot be ensured in practice especially in…

Methodology · Statistics 2022-12-26 Zhengling Qi , Rui Miao , Xiaoke Zhang

In causal inference with binary outcomes, there is a growing interest in estimation of treatment harm rate (THR), which is a measure of treatment risk and reveals treatment effect heterogeneity in a subpopulation. The THR is generally…

Methodology · Statistics 2025-05-20 Wei Liang , Changbao Wu

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

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

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

Inferring causal individual treatment effect (ITE) from observational data is a challenging problem whose difficulty is exacerbated by the presence of treatment assignment bias. In this work, we propose a new way to estimate the ITE using…

Machine Learning · Computer Science 2021-03-16 Abhin Shah , Kartik Ahuja , Karthikeyan Shanmugam , Dennis Wei , Kush Varshney , Amit Dhurandhar

Evidence from observational studies has become increasingly important for supporting healthcare policy making via cost-effectiveness (CE) analyses. Similar as in comparative effectiveness studies, health economic evaluations that consider…

Although there is now a large literature on policy evaluation and learning, much of the prior work assumes that the treatment assignment of one unit does not affect the outcome of another unit. Unfortunately, ignoring interference can lead…

Methodology · Statistics 2025-04-02 Yi Zhang , Kosuke Imai

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

Because many illnesses show heterogeneous response to treatment, there is increasing interest in individualizing treatment to patients [Arch. Gen. Psychiatry 66 (2009) 128--133]. An individualized treatment rule is a decision rule that…

Statistics Theory · Mathematics 2011-05-18 Min Qian , Susan A. Murphy

Modern precision medicine aims to utilize real-world data to provide the best treatment for an individual patient. An individualized treatment rule (ITR) maps each patient's characteristics to a recommended treatment scheme that maximizes…

Applications · Statistics 2025-01-07 Andong Wang , Kelly Wentzlof , Johnny Rajala , Miontranese Green , Yunshu Zhang , Shu Yang

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

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