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Optimization of individualized dynamic treatment regimes for recurrent diseases
Author(s) -
Huang Xuelin,
Ning Jing,
Wahed Abdus S.
Publication year - 2014
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6104
Subject(s) - stage (stratigraphy) , disease , medicine , intensive care medicine , cancer treatment , disease treatment , cancer , computer science , oncology , biology , paleontology
Patients with cancer or other recurrent diseases may undergo a long process of initial treatment, disease recurrences, and salvage treatments. It is important to optimize the multi‐stage treatment sequence in this process to maximally prolong patients' survival. Comparing disease‐free survival for each treatment stage over penalizes disease recurrences but under penalizes treatment‐related mortalities. Moreover, treatment regimes used in practice are dynamic; that is, the choice of next treatment depends on a patient's responses to previous therapies. In this article, using accelerated failure time models, we develop a method to optimize such dynamic treatment regimes. This method utilizes all the longitudinal data collected during the multi‐stage process of disease recurrences and treatments, and identifies the optimal dynamic treatment regime for each individual patient by maximizing his or her expected overall survival. We illustrate the application of this method using data from a study of acute myeloid leukemia, for which the optimal treatment strategies for different patient subgroups are identified. Copyright © 2014 John Wiley & Sons, Ltd.