Background: Radical prostatectomy (RP) has heterogeneous effects on survival of patients with metastatic prostate cancer (mPCa). A reliable model to predict risk of cancer-specific mortality (CSM) and the potential benefit derived from RP is needed.
Methods: Patients diagnosed with mPCa were identified using the Surveillance, Epidemiology, and End Results database (2004-2015) and categorized in RP versus nonlocal treatment (NLT). Based on the Fine and Gray competing risks model in 8,463 NLT patients, a nomogram was created to predict CSM in mPCa patients. Decision tree analysis was then utilized for patient stratification. The effect of RP was evaluated among 3 different subgroups.
Results: A total of 8,863 patients were identified for analysis. Four hundred (4.5%) patients received RP. The 5-year cumulative incidence of CSM was 52.4% for the entire patients. Based on nomogram scores, patients were sorted into three risk groups using decision tree analysis. In the low- and intermediate-risk group, RP was found to be significantly correlated with a 21.7% risk reduction of 5-year CSM, and 25.0% risk reduction of 5-year CSM, respectively, whereas RP was not associated with CSM in high-risk group (hazard ratio =0.748, 95% confidence interval 0.485-1.150; P=0.190).
Conclusions: We developed a novel nomogram and corresponding patient stratification predicting CSM in mPCa patients. A newly identified patient subgroup with low-, and intermediate-risk of CSM might benefit more from RP. These results should be further validated and improved by ongoing prospective trials.
Keywords: Metastatic prostate cancer (mPCa); cancer-specific mortality (CSM); nomogram; radical prostatectomy (RP).
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