The Cambridge Prognostic Groups for improved prediction of disease mortality at diagnosis in primary non-metastatic prostate cancer: a validation study.
Purpose: To validate a new 5-tier prognostic classification system to better discriminate cancer specific mortality in men diagnosed with primary non-metastatic prostate cancer.
Patients and Methods: We applied a recently described 5 strata model (Cambridge Prognostic Groups-CPG) in 2 international cohorts and tested prognostic performance against the current standard 3 strata classification of low, intermediate or high-risk disease. Diagnostic clinico-pathological data of men from Prostate Cancer Data Base Sweden (PCBaSe) and the Singapore Health Study were used. The main outcome measure was prostate cancer mortality (PCM) stratified by age group and treatment modality.
Results: The PCBaSe cohort included 72,337 men, of whom 7,162 died of prostate cancer. The CPG model successfully classified men with different risks of PCM with competing risk-regression confirming significant intergroup distinction (p<0.0001). The CPGs were significantly better at stratified prediction of PCM compared to the current 3-tier system (C-Index 0.81 vs. 0.77, p<0.0001). This superiority was maintained for every age group division (p<0.0001). Also in the ethnically different Singapore cohort of 2,550 men with 142 prostate cancer deaths, the CPG model outperformed the 3 strata categories (C-Index 0.79 vs. 0.76, p<0.0001). The model also retained superior prognostic discrimination in treatment sub-groups - Radical prostatectomy (n=20,586): C-Index 0.77 vs. 074, radiotherapy (n=11,872): C-Index 0.73 vs. 0.68, and conservative management (n=14,950): C-Index 0.74 vs. 0.73. The CPG groups that sub-divided the old intermediate (CPG2 vs. CPG3) and high-risk categories (CPG4 vs.CPG5) significantly discriminated PCM outcomes after radical therapy or conservative management (p<0.0001).
Conclusion: This validation study of nearly 75,000 men, confirms that the CPG 5-tiered prognostic model has superior discrimination in predicting prostate cancer death over the 3-tier model across different age and treatment groups. Crucially, it identifies distinct sub-groups of men within the old intermediate-risk and high-risk criteria who have very different prognostic outcomes We therefore propose adoption of the CPG model as a simple to use but more accurate prognostic stratification tool to help guide management for men with newly diagnosed prostate cancer.
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