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Title of Journal: Sci China Math

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Abbravation: Science China Mathematics

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SP Science China Press

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DOI

10.1002/ece3.1555

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1869-1862

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Dynamic optimal strategy for monitoring disease re

Authors: Hong Li Constantine Gatsonis
Publish Date: 2012/07/18
Volume: 55, Issue: 8, Pages: 1565-1582
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Abstract

Surveillance to detect cancer recurrence is an important part of care for cancer survivors In this paper we discuss the design of optimal strategies for early detection of disease recurrence based on each patient’s distinct biomarker trajectory and periodically updated risk estimated in the setting of a prospective cohort study We adopt a latent class joint model which considers a longitudinal biomarker process and an event process jointly to address heterogeneity of patients and disease to discover distinct biomarker trajectory patterns to classify patients into different risk groups and to predict the risk of disease recurrence The model is used to develop a monitoring strategy that dynamically modifies the monitoring intervals according to patients’ current risk derived from periodically updated biomarker measurements and other indicators of disease spread The optimal biomarker assessment time is derived using a utility function We develop an algorithm to apply the proposed strategy to monitoring of new patients after initial treatment We illustrate the models and the derivation of the optimal strategy using simulated data from monitoring prostate cancer recurrence over a 5year period

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  2. Convergence analysis of the formal energies of symplectic methods for Hamiltonian systems
  3. Distributionally scrambled set and minimal set
  4. Small prime solutions to cubic equations
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  13. Travelling wave solutions of a generalized Camassa-Holm-Degasperis-Procesi equation
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  18. Uniform convergence of the p -Bieberbach polynomials in domains with zero angles
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  23. On Einstein Matsumoto metrics
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