Impact of 68Ga-PSMA PET/CT in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with enzalutamide

Background We evaluated the impact of 68Ga prostate specific membrane antigen positron emission tomography/computed tomography (68Ga-PSMA PET/CT) in patients treated with enzalutamide as first-line therapy for mCRPC. Methods In an observational prospective study, 67 consecutive mCRPC patients were treated with enzalutamide in first-line for mCRPC. 68Ga-PSMA PET/CT was performed at baseline, after 1 and 3 months and at progression. We measured the sum of metabolic total volume (SMTV), mean standardized uptake volume (SSUVmean), maximum standardized uptake volume (SSUVmax) and total lesion activity (STLA), which is the product of SMTV and SSUVmean, for a maximum of 20 lesions. These parameters together with PSA level, Eastern Cooperative Oncology Group performance status (ECOG PS), Gleason Score (GS) and age were analyzed by univariate and multivariate Cox regression models as potential predictors of progression-free survival (PFS) and overall survival (OS). Results 58 mCRPC patients were considered fully evaluable. Median age was 75 years (range, 47-91), ECOG PS was 0 in 47 cases (81%), GS was 8-10 in 36 (62%), the median baseline PSA was 2.66 µg/L (range 0.09-197), median number of lesion was 3. We observed a median SMTV of 73 cm3, median SSUVmax of 44.85, median SSUVmean of 25.80 and median STLA of 59.66. At the median follow-up of 52 months, median PFS was 28.9 months (95% CI 16.3-43.6), median OS was not reached (95% CI 36.8-not reached). In univariate analysis, SSUVmax and STLA were significant for PFS (p=0.015 and p=0.001, respectively) and OS (p=0.026 and p=0.019, respectively), while SSUVmean and number of lesions were significant only for OS (p=0.028 and p=0.004, respectively). On multivariate analysis, STLA only remained significant for PFS (p=0.0004) and OS (p=0.019). Conclusions: In he assessment of mCRPC by 68Ga-PSMA PET/CT before enzalutamide, STLA appeared the strongest parameter able to predict PFS and OS.