A novel prediction model for the completion of six cycles of radium-223 treatment and survival in patients with metastatic castration-resistant prostate cancer

Abstract

PurposeWe evaluated the predictive factors for completion of all six cycles of radium-223 (Ra-223) treatment in patients with metastatic castration-resistant prostate cancer (mCRPC). We also developed a novel prediction model for Ra-223 treatment completion using these predictors.MethodsWe retrospectively reviewed data from 122 patients with mCRPC who were treated with Ra-223. The predictive factors for the completion of six cycles of Ra-223 treatment were evaluated. Statistically significant predictive factors were then used to develop a prediction model for treatment completion. Finally, using this prediction model, we classified the overall survival (OS) of the entire cohort into three groups.ResultsWe identified three significant variables as the predictive factors for treatment completion: baseline alkaline phosphatase (ALP) level, baseline hemoglobin (Hb) level, and baseline pain. The three groups generated using the prediction model were: group 1 (patients with three predictive factors, i.e., ALP < median, Hb ≥ median, and no pain), group 2 (patients with one to two predictive factors), and group 3 (patients without any predictive factors). The treatment completion rates differed between the three groups significantly. Furthermore, the OS also differed among the groups significantly.ConclusionOur study suggested that the baseline ALP level, baseline Hb level, and baseline pain were the predictive factors of completion of all six cycles of Ra-223 treatment in patients with mCRPC. Our prediction model consisting of these factors could predict not only the completion of Ra-223 treatment, but also the post-treatment survival. This model can thus be useful for selection of patients for Ra-223 treatment.