Abstract

177Lu-PSMA-617 is an effective therapeutic option in metastasized castration-resistant prostate cancer (mCRPC). However, some patients progress under treatment. We hypothesized that the tracer kinetics within the metastases may influence the therapy effectiveness and tested this hypothesis by analyzing uptake parameters on 2 consecutive posttherapy SPECT/CT scans. Methods: mCRPC patients treated with 177Lu-PSMA-617 and with available posttherapy SPECT/CT imaging (24 and 48 h after the first treatment) were enrolled retrospectively. Volumes of interest were defined on lymph node metastasis (LNM) and bone metastasis (BM) on both SPECT/CT scans. The reduction of the percentage injected dose (%IDred) between the 2 SPECT/CT scans was computed. We compared %IDred of responders (prostate-specific antigen drop ≥ 50% after 2 cycles of 177Lu-PSMA-617) and nonresponders. We tested the association of %IDred with progression-free survival and overall survival (OS) using a univariate Kaplan-Meier (KM) analysis and a multivariate Cox regression model. Results: Fifty-five patients (median age, 73 y; range, 54-87 y) were included. %IDred in LNM and BM was greater in nonresponders than in responders (for LNM, 36% in nonresponders [interquartile range (IQR), 26%-47%] vs. 24% in responders [IQR, 12%-33%] [P = 0.003]; for BM, 35% in nonresponders [IQR, 27%-52%] vs. 18% in responders [IQR, 15%-29%] [P = 0.002]). For progression-free survival, in KM analysis, greater %IDred in LNM (P = 0.008) and BM (P = 0.001) was associated with shorter survival, whereas in multivariate analysis, only %IDred in LNM was retained (P = 0.03). In univariate KM analysis of OS, greater %IDred in BM was associated with shorter survival (P = 0.002). In multivariate OS analysis, BM %IDred (P = 0.009) was retained. Conclusion: The 177Lu-PSMA-617 clearance rate from mCRPC metastases appears to be a relevant prognosticator of response and survival, with faster clearing possibly signaling a shorter radiopharmaceutical residence time and absorbed dose. Dual-time-point analysis appears to be a feasible and readily available approach to estimate the likelihood of response and patients' survival.

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