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Updated: Mar 6, 2026
A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer
Published on: March 6, 2018
Which Factors Predict Overall Survival in Patients With Metastatic Castration-Resistant Prostate Cancer Treated With
Charles Van Praet1, Sylvie Rottey2, Fransien Van Hende3
1Department of Urology, Ghent University Hospital, Ghent, Belgium.
Background:
Abiraterone acetate (AA) increases overall survival (OS) in patients with metastatic castration-resistant prostate cancer (mCRPC) previously treated with docetaxel. However, survival time varies substantially between individuals. Our goal was to identify prognostic factors that better estimate OS.
Materials And Methods:
This is a retrospective multicentric analysis of 368 patients with mCRPC starting AA with prednisone after docetaxel. Cox proportional hazards statistics were applied. A multivariate model was constructed based on significant univariate predictors by using a manual stepwise forward and backward selection strategy. Model performance was determined by using receiver operating characteristic (ROC) curves.
Results:
Univariate analysis identified 20 significant OS predictors. A multivariate model was constructed, based on 220 patients, incorporating 5 independent risk factors for decreased OS at the time of AA initiation: hemoglobin < 12 g/dL (hazard ratio [HR] 2.02), > 10 metastases (HR 1.80), ECOG performance status ≥ 2 (HR 1.88), radiographic progression (HR 1.50), and time since diagnosis < 90 months (HR 1.66, all P < .05). Patients were stratified into 3 groups: good (0-2 risk factors, median OS 22.6 months), intermediate (3 risk factors, median OS 13.9 months), and poor prognosis (4-5 risk factors, median OS 6.2 months). The area under the ROC curve based on the event "death by the time of median OS (13.3 months)" was 0.736 (95% confidence interval 0.670-0.803).
Conclusion:
We identified 5 readily available risk factors independently associated with decreased OS. The resulting model may be used for patient counseling in daily clinical practice, as well as patient stratification in clinical trials.
