Defining Long-term Prostate Cancer Treatment Patterns and Adverse Urologic Events: A Methodological Framework and...

To develop and apply a framework using the Utah Population Database (UPDB) to identify PCa patients, characterize treatment patterns, and quantify long-term urologic adverse events (UAEs) given that prostate cancer (PCa) is a leading malignancy in men with high survival rates but limited data on long-term urologic morbidity.

We conducted a retrospective matched cohort study of men aged 18-85 with localized PCa diagnosed between 1996-2023 in the UPDB. Age- and sex-matched controls were selected 2:1. Exclusions included prior UAE, metastatic disease, or missing data. Treatments were classified into 9 standard groups, and UAEs were categorized as low- or high-grade using diagnosis and procedure codes. Temporal analyses were performed at 1, 5, 10, 15, and 20 years post-diagnosis.

After exclusions, 36,482 cases and 69,722 controls were included (median follow-up: 8.0 and 7.8 years, respectively). Forty percent of cases and controls had a minimum 10-year follow-up after prostate cancer diagnosis. Nearly 36% of PCa patients were under age 65 and would have been excluded from SEER-Medicare studies. By 20 years, 50% of cases had at least 1 low-grade diagnosis (vs 39% controls) and 15.1% had a high-grade diagnosis (vs 6.7%). Secondary urologic malignancy risk was 2.6-fold higher in PCa patients.

Leveraging the UPDB enables comprehensive, long-term evaluation of treatment-related morbidity in diverse PCa patients, including younger populations often excluded from national datasets. This approach supports more accurate survivorship research and can inform predictive modeling to guide patient counseling and treatment planning.