Personalizing Androgen Suppression for Prostate Cancer Using Mathematical Modeling.

ABSTRACT: Using a dataset of 150 patients treated with intermittent androgen suppression (IAS) through a fixed treatment schedule, we retrospectively designed a personalized treatment schedule mathematically for each patient. We estimated 100 sets of parameter values for each patient by randomly resampling each patient's time points to take into account the uncertainty for observations of prostate specific antigen (PSA). Then, we identified 3 types and classified patients accordingly: in type (i), the relapse, namely the divergence of PSA, can be prevented by IAS; in type (ii), the relapse can be delayed by IAS later than by continuous androgen suppression (CAS); in type (iii) IAS was not beneficial and therefore CAS would have been more appropriate in the long run. Moreover, we obtained a treatment

SUBMITTER: Hirata Y 

PROVIDER: S-EPMC5805696 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature