Abstract
To evaluate the Bone Scan Index (BSI) for prediction of castration resistance and prostate cancer-specific survival (PCSS). In this retrospective study, we used novel computer-assisted software for automated detection/quantification of bone metastases by BSI. Patients with prostate cancer are M-staged by whole-body bone scintigraphy (WBS) and categorised as M0 or M1. Within the M1 group, there is a wide range of clinical outcomes. The BSI was introduced a decade ago providing quantification of bone metastases by estimating the percentage of bone involvement. Being too time consuming, it never gained widespread clinical use. In all, 88 patients with prostate cancer awaiting initiation of androgen-deprivation therapy due to metastases were included. WBS was performed using a two-headed γ-camera. BSI was obtained using the automated platform EXINI bone (EXINI Diagnostics AB, Lund, Sweden). In Cox proportional hazard models, time to castration-resistant prostate cancer (CRPC) and PCSS were modelled as the dependent variables, whereas prostate-specific antigen (PSA) level, Gleason score and BSI were used as explanatory factors. For Kaplan-Meier estimates, BSI groups were dichotomously split into: BSI <1 and BSI ≥1. Discrimination between prognostic models was explored using the concordance index (C-index). The mean (range) age of the patients was 72 (52-92) years, the median (range) PSA level was 73 (4-5 740) ng/mL, the mean (range) Gleason score was 7.7 (2-10), and the mean (range) BSI was 1.0 (0-9.2). During a mean (range) follow-up of 26 (8-49) months, 48 patients became castration resistant and 15 had died; most (13) from prostate cancer. In multivariate analysis including PSA level, Gleason score and BSI, only prediction by BSI was statistically significant. This was true both for time to CRPC (hazard ratio [HR] 1.45, 95% confidence interval [CI] 1.22-1.74; C-index increase from 0.49 to 0.69) and for PCSS (HR 1.34, 95% CI 1.07-1.67; C-index increase from 0.76 to 0.95). BSI obtained using a novel automated computer-assisted algorithm appears to be a useful predictor of outcome for time to CRPC and PCSS in patients with hormone-sensitive metastatic prostate cancer.
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