The value of integrating urology and oncology real-world data for understanding prostate cancer management.

e17011 Background: Real-world data (RWD) is essential for understanding current management and outcomes of patients with prostate cancer. Most observational research relies on fragmented RWD generated from single care settings with limited assessment of transition of care (TOC) between multiple specialties. This study evaluates an oncology and urology integrated database to assess the ability and utility of assessing prostate care across settings for a more comprehensive understanding. Methods: A retrospective analysis was conducted using ConcertAI’s Prostate Patient360 (curated EHR+claims) dataset. Patients with prostate cancer diagnosis between 2014–2024 were included and classified into urology, oncology, and integrated (urology+oncology) care settings based on the specialty of the clinical EHR data source or sources. Estimated TOC was defined as time point when care shifted from urology to oncology specialty, was derived across all settings using linked claims data as date where &gt;80% of claims within a rolling 6-day window across a patient record originated from oncology. Descriptive statistics for patient demographics, clinicopathologic characteristics at initial diagnosis, TOC, and outcomes were compared across care settings. Results: The integrated dataset provided insights into patient demographics, baseline characteristics, and care transitions across urology, oncology and integrated care settings. Key findings are summarized in Table 1. Conclusions: The study demonstrates prostate cancer care is distributed across multiple specialties resulting in both co-management as well as clear TOC from urology to oncology associated with more advanced stages of cancer. Integrated RWD dataset from multiple specialties provides a novel view of the prostate cancer patient journey than either urology or oncology alone, with a more comprehensive characterization of demographics, tumor/clinical features, treatment patterns, and care transitions supporting meaningful research on disease monitoring and management of prostate cancer patients. Key clinical and demographic characteristics at initial cancer diagnosis highlighting differences and comparability across care settings. Urology care setting Oncology care setting Integrated care setting N (%) 1,718 (19) 6,916 (76) 409 (5) Median age, yrs 68 69 68 White 86% 73% 86% Non-Hispanic 63% 60% 60% College Educated 36% 27% 25% White Collar 36% 28% 27% Urban 71% 67% 51% Weighted Charlson comorbidity index 3+ 11% 12% 7% ECOG 0-1 47% 41% 48% De novo Stage 4 30% 36% 35% PSA&lt;10 ng/uL 29% 21% 31% Gleason grade group 5 34% 33% 40% BRCA positive 19% 18% 25% AR positive 56% 34% 37% HRR positive 24% 24% 28% Estimated TOC 39% 38% 30% Median time to estimated TOC date, mos 9.1 10.3 12.1 Median rwOS (95% CI), yrs 9.9 (8.7-NA) 6.8 (6.5-7.0) 6.5 (5.9-7.3) <jats:t

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Publication Details

Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.e17011
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

The value of integrating urology and oncology real-world data for understanding prostate cancer management.

Todd Matthew Morgan, Sheenu Chandwani, Ruth PeBenito, Herman E. Ray et al.
Journal of Clinical Oncology
Radiomics and Machine Learning in Medical Imaging
article

The value of integrating urology and oncology real-world data for understanding prostate cancer management.

Todd Matthew Morgan, Sheenu Chandwani, Ruth PeBenito, Herman E. Ray, Brandon Nathasingh
article en

Abstract

e17011 Background: Real-world data (RWD) is essential for understanding current management and outcomes of patients with prostate cancer. Most observational research relies on fragmented RWD generated from single care settings with limited assessment of transition of care (TOC) between multiple specialties. This study evaluates an oncology and urology integrated database to assess the ability and utility of assessing prostate care across settings for a more comprehensive understanding. Methods: A retrospective analysis was conducted using ConcertAI’s Prostate Patient360 (curated EHR+claims) dataset. Patients with prostate cancer diagnosis between 2014–2024 were included and classified into urology, oncology, and integrated (urology+oncology) care settings based on the specialty of the clinical EHR data source or sources. Estimated TOC was defined as time point when care shifted from urology to oncology specialty, was derived across all settings using linked claims data as date where &gt;80% of claims within a rolling 6-day window across a patient record originated from oncology. Descriptive statistics for patient demographics, clinicopathologic characteristics at initial diagnosis, TOC, and outcomes were compared across care settings. Results: The integrated dataset provided insights into patient demographics, baseline characteristics, and care transitions across urology, oncology and integrated care settings. Key findings are summarized in Table 1. Conclusions: The study demonstrates prostate cancer care is distributed across multiple specialties resulting in both co-management as well as clear TOC from urology to oncology associated with more advanced stages of cancer. Integrated RWD dataset from multiple specialties provides a novel view of the prostate cancer patient journey than either urology or oncology alone, with a more comprehensive characterization of demographics, tumor/clinical features, treatment patterns, and care transitions supporting meaningful research on disease monitoring and management of prostate cancer patients. Key clinical and demographic characteristics at initial cancer diagnosis highlighting differences and comparability across care settings. Urology care setting Oncology care setting Integrated care setting N (%) 1,718 (19) 6,916 (76) 409 (5) Median age, yrs 68 69 68 White 86% 73% 86% Non-Hispanic 63% 60% 60% College Educated 36% 27% 25% White Collar 36% 28% 27% Urban 71% 67% 51% Weighted Charlson comorbidity index 3+ 11% 12% 7% ECOG 0-1 47% 41% 48% De novo Stage 4 30% 36% 35% PSA&lt;10 ng/uL 29% 21% 31% Gleason grade group 5 34% 33% 40% BRCA positive 19% 18% 25% AR positive 56% 34% 37% HRR positive 24% 24% 28% Estimated TOC 39% 38% 30% Median time to estimated TOC date, mos 9.1 10.3 12.1 Median rwOS (95% CI), yrs 9.9 (8.7-NA) 6.8 (6.5-7.0) 6.5 (5.9-7.3) <jats:t

Journal of Clinical OncologyVol. 43(16_suppl)
University of Michigan (US), Concert Pharmaceuticals (United States) (US)
Openalex Percentile: Top 82%
Radiomics and Machine Learning in Medical Imaging
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