[177Lu]Lu-PSMA-617 (177Lu-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 177Lu-PSMA-617 built using data from VISION, a large prospective phase 3 clinical trial powered for overall survival.
Adults with progressive post androgen receptor pathway inhibitor and taxane prostate-specific membrane antigen (PSMA)-positive mCRPC received 177Lu-PSMA-617 plus protocol-permitted standard of care (SoC) or SoC alone. In this post hoc 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.
Patients were randomised between June 2018 and October 2019. Data from all 551 patients in the 177Lu-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 (SUVmax), 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 SUVmax, 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 SUVmax, lymphocyte count and ALP. Performances of the OS and rPFS models were maintained when they were reconstructed excluding SUVmax.
These models of outcomes with 177Lu-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.
Novartis.
EClinicalMedicine. 2024 Oct 04*** epublish ***
Ken Herrmann, Andrei Gafita, Johann S de Bono, Oliver Sartor, Kim N Chi, Bernd J Krause, Kambiz Rahbar, Scott T Tagawa, Johannes Czernin, Ghassan El-Haddad, Connie C Wong, Zhaojie Zhang, Celine Wilke, Osvaldo Mirante, Michael J Morris, Karim Fizazi
Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK), Essen University Hospital, Essen, Germany., Division of Nuclear Medicine and Molecular Imaging, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Division of Clinical Studies, The Institute of Cancer Research and the Royal Marsden Hospital, London, UK., Department of Medical Oncology, Mayo Clinic, Rochester, MN, USA., Division of Medical Oncology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada., Department of Nuclear Medicine, Rostock University Medical Center, Rostock, Germany., Department of Nuclear Medicine, Münster University Hospital, Münster, Germany., Department of Medicine, Division of Hematology and Medical Oncology and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA., Ahmanson Translational Theranostics Division, Department of Molecular and Medical Pharmacology and Institute of Urologic Oncology, University of California Los Angeles, Los Angeles, CA, USA., Department of Diagnostic Imaging and Interventional Radiology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA., Novartis Pharmaceuticals Corporation, Cambridge, MA, USA., Novartis Pharma AG, Basel, Switzerland., Advanced Accelerator Applications, A Novartis Company, Geneva, Switzerland., Genitourinary Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Medical Oncology Department, Institut Gustave Roussy, University of Paris-Saclay, Villejuif, France.