ArticleBiometrics2012
A robust method for estimating optimal treatment regimes.
Article in Biometrics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 181 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
181 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Estimating individualized treatment effects using an individual participant data meta-analysis.BMC medical research methodology · 2024Pooled it
- Adaptive, Stepped-Care for Cancer-Related PTSD Symptoms in HCT Survivors: Results From a SMART Trial.Psycho-oncology · 2026Trial
- Trial
- Evaluating biomarkers for treatment selection from reproducibility studies.Biostatistics (Oxford, England) · 2022Trial
- Estimating individualized treatment regimes from crossover designs.Biometrics · 2020Trial
- Adjusting for covariates in evaluating markers for selecting treatment, with application to guiding chemotherapy for treating estrogen-receptor-positive, node-positive breast cancer.Contemporary clinical trials · 2017Trial
- Optimizing delivery of a behavioral pain intervention in cancer patients using a sequential multiple assignment randomized trial SMART.Contemporary clinical trials · 2017Trial
- Evaluating marker-guided treatment selection strategies.Biometrics · 2014Trial
- Reluctant Transfer Learning in Penalized Regressions for Individualized Treatment Rules Under Effect Heterogeneity.Statistics in medicine · 2026Article
- Variable selection for estimating optimal treatment regimes with multiple treatments.Scientific reports · 2026Article
- Integrative learning of individualized treatment rules from multiple studies with partially overlapping treatments.Biometrics · 2026Article
- Data driven versus standard practice policies for personalized antidepressant treatment: a retrospective cohort study of electronic health records.BMC psychiatry · 2026Article
- Within-trial data borrowing for sequential multiple assignment randomized trials.Biostatistics (Oxford, England) · 2025Article
- A multiagent reinforcement learning algorithm for personalized recommendations in bipolar disorder.PNAS nexus · 2025Article
- FEDERATED LEARNING OF ROBUST INDIVIDUALIZED DECISION RULES WITH APPLICATION TO HETEROGENEOUS MULTIHOSPITAL SEPSIS POPULATION.The annals of applied statistics · 2025Article
- Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data.Journal of machine learning research : JMLR · 2025Article
- Nonparametric Biomarker Based Treatment Selection With Reproducibility Data.Statistics in medicine · 2024Article
- Estimating Optimal Treatment Rule for Major Depressive Disorder Using Penalized Regression Method.Oman medical journal · 2024Article
- Toward Precision in Critical Care Research: Methods for Observational and Interventional Studies.Critical care medicine · 2024Review
- Estimating individualized treatment rules by optimizing the adjusted probability of a longer survival.Statistical methods in medical research · 2024Article
121 more citing papers are in PubMed but not listed here.
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4 authors.
Funding
Abstract
A treatment regime is a rule that assigns a treatment, among a set of possible treatments, to a patient as a function of his/her observed characteristics, hence "personalizing" treatment to the patient. The goal is to identify the optimal treatment regime that, if followed by the entire population of patients, would lead to the best outcome on average. Given data from a clinical trial or observational study, for a single treatment decision, the optimal regime can be found by assuming a regression model for the expected outcome conditional on treatment and covariates, where, for a given set of covariates, the optimal treatment is the one that yields the most favorable expected outcome. However, treatment assignment via such a regime is suspect if the regression model is incorrectly specified. Recognizing that, even if misspecified, such a regression model defines a class of regimes, we instead consider finding the optimal regime within such a class by finding the regime that optimizes an estimator of overall population mean outcome. To take into account possible confounding in an observational study and to increase precision, we use a doubly robust augmented inverse probability weighted estimator for this purpose. Simulations and application to data from a breast cancer clinical trial demonstrate the performance of the method.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.