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Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.

Publication ,  Journal Article
Hager, R; Tsiatis, AA; Davidian, M
Published in: Biometrics
December 2018

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.

Duke Scholars

Published In

Biometrics

DOI

EISSN

1541-0420

Publication Date

December 2018

Volume

74

Issue

4

Start / End Page

1180 / 1192

Location

England

Related Subject Headings

  • Survival Analysis
  • Support Vector Machine
  • Statistics & Probability
  • Randomized Controlled Trials as Topic
  • Outcome Assessment, Health Care
  • Leukemia
  • Humans
  • Decision Support Techniques
  • Computer Simulation
  • Biometry
 

Citation

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Hager, R., Tsiatis, A. A., & Davidian, M. (2018). Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data. Biometrics, 74(4), 1180–1192. https://doi.org/10.1111/biom.12894
Hager, Rebecca, Anastasios A. Tsiatis, and Marie Davidian. “Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.Biometrics 74, no. 4 (December 2018): 1180–92. https://doi.org/10.1111/biom.12894.
Hager R, Tsiatis AA, Davidian M. Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data. Biometrics. 2018 Dec;74(4):1180–92.
Hager, Rebecca, et al. “Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.Biometrics, vol. 74, no. 4, Dec. 2018, pp. 1180–92. Pubmed, doi:10.1111/biom.12894.
Hager R, Tsiatis AA, Davidian M. Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data. Biometrics. 2018 Dec;74(4):1180–1192.
Journal cover image

Published In

Biometrics

DOI

EISSN

1541-0420

Publication Date

December 2018

Volume

74

Issue

4

Start / End Page

1180 / 1192

Location

England

Related Subject Headings

  • Survival Analysis
  • Support Vector Machine
  • Statistics & Probability
  • Randomized Controlled Trials as Topic
  • Outcome Assessment, Health Care
  • Leukemia
  • Humans
  • Decision Support Techniques
  • Computer Simulation
  • Biometry