Philip Sutera1, Kim Van Der Eecken2, Amar U Kishan3, Anis Hamid4, Emily Grist5, Gerhardt Attard6, Tamara Lotan7, Adrianna A Mendes7, Channing J Paller8, Michael A Carducci8, Ashley Ross9, Hao Wang10, Ken Pienta8,11, Felix Y Feng12, Emmanuel S Antonarakis8, Piet Ost13, Daniel Y Song1,8,11, Stephen Greco1, Curtiland Deville1, Theodore DeWeese1,8,11, Phuoc T Tran1,8,11, Matthew P Deek14,15. 1. Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 2. Departments of Pathology and human structure and repair, University of Ghent, Ghent, Belgium. 3. Department of Radiation Oncology, UCLA, Los Angeles, CA, USA. 4. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA. 5. Department of Oncology, UCL Cancer Institute, London, UK. 6. Division of Molecular Pathology, The Institute of Cancer Research, London, UK. 7. Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA. 8. Department of Oncology, Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 9. Department of Urology, Northwestern University, Chicago, IL, USA. 10. Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 11. James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 12. Departments of Radiation Oncology, Medicine and Urology, UCSF, San Francisco, CA, USA. 13. Department of Radiation Oncology, Iridium Network, Antwerp, Belgium and Department of human structure and repair, Ghent University, Ghent, Belgium. 14. Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA. matthewdeek@gmail.com. 15. Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, USA. matthewdeek@gmail.com.
Abstract
BACKGROUND: Several definitions have attempted to stratify metastatic castrate-sensitive prostate cancer (mCSPC) into low and high-volume states. However, at this time, comparison of these definitions is limited. Here we aim to compare definitions of metastatic volume in mCSPC with respect to clinical outcomes and mutational profiles. METHODS: We performed a retrospective review of patients with biochemically recurrent or mCSPC whose tumors underwent somatic targeted sequencing. 294 patients were included with median follow-up of 58.3 months. Patients were classified into low and high-volume disease per CHAARTED, STAMPEDE, and two numeric (≤3 and ≤5) definitions. Endpoints including radiographic progression-free survival (rPFS), time to development of castration resistance (tdCRPC), and overall survival (OS) were evaluated with Kaplan-Meier survival curves and log-rank test. The incidence of driver mutations between definitions were compared. RESULTS: Median OS and tdCRPC were shorter for high-volume than low-volume disease for all four definitions. In the majority of patients (84.7%) metastatic volume classification did not change across all four definitions. High volume disease was significantly associated with worse OS for all four definitions (CHAARTED: HR 2.89; p < 0.01, STAMPEDE: HR 3.82; p < 0.01, numeric ≤3: HR 4.67; p < 0.01, numeric ≤5: HR 3.76; p < 0.01) however, were similar for high (p = 0.95) and low volume (p = 0.79) disease across all four definitions. Those with discordant classification tended to have more aggressive clinical behavior and mutational profiles. Patients with low-volume disease and TP53 mutation experienced a more aggressive course with rPFS more closely mirroring high-volume disease. CONCLUSIONS: The spectrum of mCSPC was confirmed across four different metastatic definitions for clinical endpoints and genetics. All definitions were generally similar in classification of patients, outcomes, and genetic makeup. Given these findings, the simplicity of numerical definitions might be preferred, especially when integrating metastasis directed therapy. Incorporation of tumor genetics may allow further refinement of current metastatic definitions.
BACKGROUND: Several definitions have attempted to stratify metastatic castrate-sensitive prostate cancer (mCSPC) into low and high-volume states. However, at this time, comparison of these definitions is limited. Here we aim to compare definitions of metastatic volume in mCSPC with respect to clinical outcomes and mutational profiles. METHODS: We performed a retrospective review of patients with biochemically recurrent or mCSPC whose tumors underwent somatic targeted sequencing. 294 patients were included with median follow-up of 58.3 months. Patients were classified into low and high-volume disease per CHAARTED, STAMPEDE, and two numeric (≤3 and ≤5) definitions. Endpoints including radiographic progression-free survival (rPFS), time to development of castration resistance (tdCRPC), and overall survival (OS) were evaluated with Kaplan-Meier survival curves and log-rank test. The incidence of driver mutations between definitions were compared. RESULTS: Median OS and tdCRPC were shorter for high-volume than low-volume disease for all four definitions. In the majority of patients (84.7%) metastatic volume classification did not change across all four definitions. High volume disease was significantly associated with worse OS for all four definitions (CHAARTED: HR 2.89; p < 0.01, STAMPEDE: HR 3.82; p < 0.01, numeric ≤3: HR 4.67; p < 0.01, numeric ≤5: HR 3.76; p < 0.01) however, were similar for high (p = 0.95) and low volume (p = 0.79) disease across all four definitions. Those with discordant classification tended to have more aggressive clinical behavior and mutational profiles. Patients with low-volume disease and TP53 mutation experienced a more aggressive course with rPFS more closely mirroring high-volume disease. CONCLUSIONS: The spectrum of mCSPC was confirmed across four different metastatic definitions for clinical endpoints and genetics. All definitions were generally similar in classification of patients, outcomes, and genetic makeup. Given these findings, the simplicity of numerical definitions might be preferred, especially when integrating metastasis directed therapy. Incorporation of tumor genetics may allow further refinement of current metastatic definitions.
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