Development and validation of a prognostic model for overall survival in chemotherapy-naïve men with metastatic castration-resistant prostate cancer

Abstract

Background: Prognostic models are needed that reflect contemporary practice for men with metastatic castration-resistant prostate cancer (mCRPC). We sought to identify predictive and prognostic variables for overall survival (OS) in chemotherapy-naïve men with mCRPC treated with enzalutamide.

Patients and methods: Patients from the PREVAIL trial database (enzalutamide versus placebo) were randomly split 2 : 1 into training (n = 1159) and testing (n = 550) sets. Using the training set, 23 predefined variables were analyzed and a multivariable model predicting OS was developed and validated in an independent testing set.

Results: Patient characteristics and outcomes were well balanced between training and testing sets; median OS was 32.7 months in each. The final validated multivariable model included 11 independent prognostic variables. Median OS for low-, intermediate-, and high-risk groups (testing set) defined by prognostic risk tertiles were not yet reached (NYR) (95% CI NYR-NYR), 34.2 months (31.5-NYR), and 21.1 months (17.5-25.0), respectively. Hazard ratios (95% CI) for OS in the low- and intermediate-risk groups versus high-risk group were 0.20 (0.14-0.29) and 0.40 (0.30-0.53), respectively. Secondary outcomes of response and progression differed widely in model-defined risk groups. Enzalutamide improved outcomes in all prognostic risk groups.

Conclusions: Our validated prognostic model incorporates variables routinely collected in chemotherapy-naïve men with mCRPC treated with enzalutamide, identifying subsets of patients with widely differing survival outcomes that provide useful information for external validation, patient care, and clinical trial design.

Trial registration: ClinicalTrials.gov: NCT01212991.

Figure 1.

A nomogram is used to assign each of 11 prognostic factors with a point range from 0 to 100 in a graphic interface, based on the estimated regression coefficients from the final multivariable Cox proportional hazards model predicting overall survival (OS). The nomogram results match with the algorithm. The 1-, 2-, and 3-year survival probability versus total points were also generated to allow the clinical partition to predict OS. The nomogram was developed using SAS^® enterprise version 7.1 and is based on the following article: http://support.sas.com/resources/papers/proceedings13/264-2013.pdf. Instructions to physicians: All of the 11 prognostic factors should be available before using this model. Start from the second top axis by identifying the number of bone metastases. Draw a vertical line to the points axis (top line) to represent the number of prognostic points the patients will receive for number of bone metastases. Do the same for the other prognostic variables. Once all prognostic points for the predictors have been determined, add up the prognostic points for each prognostic variable. On the basis of the total points, one can determine the 1-year survival probability by drawing a vertical line from the total points x-axis to the survival probability. The same process can be performed to estimate the 2-year and 3-year survival probability.

Figure 2.

Analysis of overall survival based on the 11-variable model. Analyses in (A) high- and low-risk patients as stratified by median risk score and (B) high-, intermediate-, and low-risk patients as stratified by tertiles of the risk score. CI, confidence interval; NYR, not yet reached; REF, reference.