Prognostic models are needed to address the wide spectrum of clinical conditions in chemotherapy-naïve mCRPC. We developed a model that categorized patients with mCRPC treated with abiraterone acetate plus prednisone into 3 risk groups, and showed a threefold difference in progression-free survival between good versus poor risk group. With validation, this model may help guide treatment and clinical trial design. Background: Radiographic progression-free survival (rPFS) is associated with overall survival (OS) in chemotherapy-naïve metastatic castration-resistant prostate cancer (mCRPC) patients. Using readily assessable baseline clinical and laboratory parameters, we developed a prognostic index model for rPFS in chemotherapy-naïve mCRPC patients without visceral disease who were treated with abiraterone acetate plus prednisone. Methods: Data from the abiraterone acetate plus prednisone arm of COU-AA-302 were used. rPFS was defined based on modified Prostate Cancer Working Group 2 criteria. Baseline variables were assessed for association with rPFS through univariate Cox modeling. The lower (LLN) and upper (ULN) limits of laboratory normal were used to dichotomize most laboratory parameters; baseline median was used to dichotomize prostate-specific antigen (PSA). Prognostic factors for rPFS were identified by multivariate Cox modeling. Model accuracy was estimated by the C-index. Results: Presence of lymph node metastasis (hazard ratio [HR] = 1.76, P <.0001), lactate dehydrogenase > ULN (234 IU/L) (HR = 1.71, P =.0001), ≥ 10 bone metastases (HR = 1.71, P =.0015), hemoglobin ≤ LLN (12.7 g/dL) (HR = 1.47, P =.0030) and PSA > 39.5 ng/mL (HR = 1.42, P =.0078) were associated with poor outcome. Patients were categorized into 3 prognostic groups (good, n = 230; intermediate, n = 152; poor, n = 164) based on number of risk factors. Median rPFS was calculated (27.6, 16.6, and 8.3 months for good, intermediate, and poor, respectively). The C-index was 0.83 (95% confidence interval = 0.73-0.91). Conclusions: The prognostic index model for rPFS reveals differential outcomes based on factors readily available in clinical practice. If validated, this model can be integrated into clinical practice and design of risk-stratified trials.
Bibliographical noteFunding Information:
C.J. Ryan has received honoraria from Janssen Research & Development. T. Kheoh, J. Li, and P. De Porre are employed by Janssen Research & Development and own stock or hold an ownership interest with Johnson & Johnson. A. Molina was an employee of Janssen Research & Development during the time of this analysis and has owned stock or held an ownership interest with Johnson & Johnson. J. Carles has served as consultant/advisor to and received honoraria from Janssen Research & Development. E. Efstathiou has served as a consultant/advisor for AstraZeneca, Janssen Research & Development, Sanofi, and Tokai Pharmaceuticals; received institutional research funding from Janssen Research & Development; and received honoraria from AstraZeneca, Janssen Research & Development, Sanofi, and Takeda. P.W. Kantoff and K.N. Chi serve on the advisory board for and receive clinical research funding from Janssen Research & Development. P.F.A. Mulders has no direct or indirect commercial incentive associated with publishing this article. F. Saad is a consultant/advisor to and has received honoraria and research funding from Astellas and Janssen Research & Development.
Writing assistance was provided by Lashon Pringle, PhD, of PAREXEL and was funded by Janssen Global Services, LLC.
© 2017 Elsevier Inc.
Copyright 2018 Elsevier B.V., All rights reserved.
- Cox models
- Laboratory marker
- Risk group
- Statistical regression