Retrospective mathematical analysis of serial prostate specific antigen (PSA) measurements for patients with M0 prostate cancer treated with intermittent androgen suppression (IAS).

Abstract

e15201 Background: Recently a phase III trial demonstrated that IAS was non-inferior to continuous AS in men with M0 disease after primary or salvage radiation and quality of life was better in the intermittent arm (Crook ASCO 2011). In that trial, men were treated with 8 months of AS followed by a variable time off AS driven by the absolute PSA value. The Hirata mathematical model describes the dynamics of prostate cancer treated with IAS (Hirata et al, J of Theoretical Biol 2010). In the model, there are three classes of cancer cells: a class of androgen dependent (AD) cells and two classes of androgen independent (AI:X1 and AI:X2) cells. During AS, AD cells will change to the two AI classes, and during the off treatment period, AI:X1 cells will revert to AD cells whereas AI:X2 cells cannot revert to either AD or AI:X1 cells. Methods: After IRB approval, we applied the Hirata model using serial monthly PSAs from men with M0 disease treated with IAS from Japan, Canada, and the United States. The proportions of men from each country who fell into the 3 categories of patients previously defined by the Hirata model were compared. Results: Serial PSAs from 26 men from Japan, 72 from Canada, and 79 from US were put into the model. The 3 categories of patients from the model include: (i) those with disease that will remain androgen sensitive and will respond to IAS without development of castration resistance (CRPC) (ii) those who will benefit from IAS but will develop CRPC sooner than those in group (i), (iii) those for whom continuous AS is superior to IAS. The datasets from each country show a similar distribution among the categories, and overall there were 42%, 51%, and 7% falling into groups i, ii, and iii respectively. Conclusions: This retrospective analysis shows that men with M0 disease treated with IAS fall into the 3 categories predicted by the Hirata model in similar proportions, regardless of country of origin. The ability to apply this model to the individual patient in the clinic is currently under development. The model may ultimately be able to optimize both the on and off treatment durations of IAS and to predict those patients who will most benefit from this approach.