Despite earlier detection, de novo metastatic PCa remains associated with a high risk of 5-year disease-specific mortality. The reduced 5-year PCa mortality in the Danish cohort is largely explained by lead-time. Early detection strategies do indeed decrease the incidence of de novo metastatic PCa, as observed in the SEER cohort. This achievement, however, must be weighed against the unsolved issue of overdetection and overtreatment of indolent PCa. Cancer 2018;124:2931-8. © 2018 American Cancer Society.

BackgroundHaving performed analytical validation studies, we are now assessing the clinical utility of the upgraded automated Bone Scan Index (BSI) in metastatic castration-resistant prostate cancer (mCRPC). In the present study, we retrospectively evaluated the discriminatory strength of the automated BSI in predicting overall survival (OS) in mCRPC patients being treated with enzalutamide.MethodsRetrospectively, we included patients who received enzalutamide as a clinically approved therapy for mCRPC and had undergone bone scan prior to starting therapy. Automated BSI, prostate-specific antigen (PSA), hemoglobin (HgB), and alkaline phosphatase (ALP) were obtained at baseline. Change in automated BSI and PSA were obtained from patients who have had bone scan at week 12 of treatment follow-up. Automated BSI was obtained using the analytically validated EXINI BoneBSI version 2. Kendall’s tau (τ) was used to assess the correlation of BSI with other blood-based biomarkers. Concordance index (C-index) was used to evaluate the discriminating strength of automated BSI in predicting OS.ResultsEighty mCRPC patients with baseline bone scans were included in the study. There was a weak correlation of automated BSI with PSA (τ = 0.30), with HgB (τ = −0.17), and with ALP (τ = 0.56). At baseline, the automated BSI was observed to be predictive of OS (C-index 0.72, standard error (SE) 0.03). Adding automated BSI to the blood-based model significantly improved the C-index from 0.67 to 0.72, p = 0.017. Treatment follow-up bone scans were available from 62 patients. Both change in BSI and percent change in PSA were predictive of OS. However, the combined predictive model of percent PSA change and change in automated BSI (C-index 0.77) was significantly higher than that of percent PSA change alone (C-index 0.73), p = 0.041.ConclusionsThe upgraded and analytically validated automated BSI was found to be a strong predictor of OS in mCRPC patients. Additionally, the change in automated BSI demonstrated an additive clinical value to the change in PSA in mCRPC patients being treated with enzalutamide.

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