Clinicopathologic factors that influence prognosis and survival outcomes in men with metastatic castration-resistant prostate cancer treated with Radium-223.

BACKGROUND

In men with metastatic castration-resistant prostate cancer (mCRPC) with primarily bone metastases, radium-223 ( Ra) improves overall survival (OS). However, the selection of Ra is not guided by specific validated clinicopathologic factors, and thus outcomes are heterogeneous.

PATIENTS AND METHODS

This retrospective survival analysis was performed in men with mCRPC treated with Ra at our cancer center. Demographics and disease characteristics were collected. OS was calculated using the Kaplan-Meier method (log-rank). The potential prognostic factors were determined using both univariable (UVA) and multivariable analysis (MVA) (Cox-regression) methods.

RESULTS

In total, 150 patients with a median age of 74 years (52-93) received Ra between May 2015 and July 2018, and 58% had 6-20 bone metastases. Ninety-four (63%) patients received >4 Ra doses, and 56 (37%) received ≤4. The following pre-treatment factors were analyzed (median [range]): eastern cooperative oncology group performance status (ECOG PS), (1 [0-3]); Albumin (ALB), (39 g/L [24-47]); alkaline phosphatase (ALP), (110 U/L [35-1633]); and prostate-specific antigen (PSA), (49 µg/L [0.83-7238]). The median OS for all patients was 14.5 months (95% CI: 11.2-18). These factors were associated with poor survival outcomes in UVA and MVA: ALB <35 g/L, ALP >150 U/L, ECOG PS 2-3, and PSA >80 µg/L. By assigning one point for each of these factors, a prognostic model was developed, wherein three distinct risk groups were identified: good, 0-1 (n = 103); intermediate, 2 (n = 30); and poor risk, 3-4 points (n = 17). The median OS was 19.4, 10.0, and 3.1 months, respectively (p < 0.001).

CONCLUSIONS

Pre-treatment ALB, ALP, ECOG, and PSA, were significantly correlated with OS and could guide treatment selection for men with mCRPC by identifying those who are most or least likely to benefit from Ra. Validation in an independent dataset is required prior to widespread clinical utilization.