1. A novel prediction model for the completion of six cycles of radium-223 treatment and survival in patients with metastatic castration-resistant prostate cancer.
- Author
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Miyoshi, Yasuhide, Tsutsumi, Sohgo, Yasui, Masato, Kawahara, Takashi, Uemura, Ko-ichi, Hayashi, Naruhiko, Nozawa, Masahiro, Yoshimura, Kazuhiro, Uemura, Hiroji, and Uemura, Hirotsugu
- Subjects
CASTRATION-resistant prostate cancer ,OVERALL survival ,PREDICTION models ,ALKALINE phosphatase - Abstract
Purpose: We 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. Methods: We 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. Results: We 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. Conclusion: Our 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. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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