Multivariable models of outcomes with [Lu]Lu-PSMA-617: analysis of the phase 3 VISION trial.

Background: [Lu]Lu-PSMA-617 (Lu-PSMA-617) prolonged life in patients with metastatic castration-resistant prostate cancer (mCRPC) in VISION (NCT03511664). However, distinguishing between patients likely and unlikely to respond remains a clinical challenge. We present the first multivariable models of outcomes with Lu-PSMA-617 built using data from VISION, a large prospective phase 3 clinical trial powered for overall survival.

Methods: Adults with progressive post androgen receptor pathway inhibitor and taxane prostate-specific membrane antigen (PSMA)-positive mCRPC received Lu-PSMA-617 plus protocol-permitted standard of care (SoC) or SoC alone. In this analysis, multivariable Cox proportional hazards models of overall survival (OS) and radiographic progression-free survival (rPFS), and a logistic regression model of prostate-specific antigen response (≥50% decline; PSA50) were constructed and evaluated using C-index or receiver operating characteristic (ROC) analyses with bootstrapping validation. Nomograms were constructed for visualisation.

Findings: Patients were randomised between June 2018 and October 2019. Data from all 551 patients in the Lu-PSMA-617 arm were analysed in multivariable modelling. The OS nomogram (C-index, 0.73; 95% confidence interval [CI], 0.70-0.76) included whole-body maximum standardised uptake value (SUV), time since diagnosis, opioid analgesic use, aspartate aminotransferase, haemoglobin, lymphocyte count, presence of PSMA-positive lesions in lymph nodes, lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and neutrophil count. The rPFS nomogram (C-index, 0.68; 0.65-0.72) included SUV, time since diagnosis, opioid analgesic use, lymphocyte count, presence of liver metastases by computed tomography, LDH, and ALP. The PSA50 nomogram (area under ROC curve, 0.72; 95% CI, 0.68-0.77) included SUV, lymphocyte count and ALP. Performances of the OS and rPFS models were maintained when they were reconstructed excluding SUV.

Interpretation: These models of outcomes with Lu-PSMA-617 are the first built using prospective phase 3 data. They show that a combination of pretreatment laboratory, clinical, and imaging parameters, reflecting both patient and tumour status, influences outcomes. These models are important for aiding treatment selection, patient management, and clinical trial design.

Funding: Novartis.