ArticleBiometrics2018
Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.
Article in Biometrics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
11 citing papers in PubMed.
- Censoring-adjusted tree-based policy learning for estimating dynamic treatment regimes with censored outcomes.Scientific reports · 2026Article
- Review
- Language-informed treatment recommendations in psychiatry: bridging the gap in individual predictability.Frontiers in psychiatry · 2026Article
- Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data.Journal of machine learning research : JMLR · 2025Article
- Estimation of optimal treatment regimes with electronic medical record data using the residual life value estimator.Biostatistics (Oxford, England) · 2024Article
- A general framework for subgroup detection via one-step value difference estimation.Biometrics · 2023Article
- Accountable survival contrast-learning for optimal dynamic treatment regimes.Scientific reports · 2023Article
- Joint modeling and multiple comparisons with the best of data from a SMART with survival outcomes.Biostatistics (Oxford, England) · 2022Article
- Optimal treatment regimes for competing risk data using doubly robust outcome weighted learning with bi-level variable selection.Computational statistics & data analysis · 2021Article
- Precision medicine: Statistical methods for estimating adaptive treatment strategies.Bone marrow transplantation · 2020Article
- Constructing dynamic treatment regimes with shared parameters for censored data.Statistics in medicine · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Clinicians often make multiple treatment decisions at key points over the course of a patient's disease. A dynamic treatment regime is a sequence of decision rules, each mapping a patient's observed history to the set of available, feasible treatment options at each decision point, and thus formalizes this process. An optimal regime is one leading to the most beneficial outcome on average if used to select treatment for the patient population. We propose a method for estimation of an optimal regime involving two decision points when the outcome of interest is a censored survival time, which is based on maximizing a locally efficient, doubly robust, augmented inverse probability weighted estimator for average outcome over a class of regimes. By casting this optimization as a classification problem, we exploit well-studied classification techniques such as support vector machines to characterize the class of regimes and facilitate implementation via a backward iterative algorithm. Simulation studies of performance and application of the method to data from a sequential, multiple assignment randomized clinical trial in acute leukemia are presented.
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Registered trials
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.