Estimating mono- and bi-phasic regression parameters using a mixture piecewise linear Bayesian hierarchical model.

ABSTRACT: The dynamics of tumor burden, secreted proteins or other biomarkers over time, is often used to evaluate the effectiveness of therapy and to predict outcomes for patients. Many methods have been proposed to investigate longitudinal trends to better characterize patients and to understand disease progression. However, most approaches assume a homogeneous patient population and a uniform response trajectory over time and across patients. Here, we present a mixture piecewise linear Bayesian hierarchical model, which takes into account both population heterogeneity and nonlinear relationships between biomarkers and time. Simulation results show that our method was able to classify subjects according to their patterns of treatment response with greater than 80% accuracy in the three scenarios t

SUBMITTER: Zhao R 

PROVIDER: S-EPMC5516991 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature