Prostate cancer temporal and regional trends in Brazil.

OBJECTIVES

The Brazilian Unified Health System (Sistema Único de Saúde-SUS) is the universal public healthcare system of Brazil that maintains a nationwide database of its patients. Our primary objective was to analyze regional and temporal trends, while our secondary goal was to establish correlations between states' health economy status and their prostate cancer (PCa) epidemiology.

METHODS

We analyzed Brazil's nationwide data on prostate cancer (PCa) incidence, mortality, and care gathered between 2013 and 2021 by the Information Technology Department of SUS (DATA-SUS), updated monthly using the International Classification of Diseases (ICD-10) code.

RESULTS

In the period, 273,933 new cases of PCa and 135,336 PCa deaths were reported in men aged 50 years or over in Brazil. The median annual PCa-specific incidence rate (PCSIR) ranged from 14.7 in the Southeast to 6.9 in the North region and the median annual PCa-specific mortality rate (PCSMR) ranged from 7.7 in the Northeast to 6.0 in the South region (per 10,000 men >50). The median annual mortality to incidence ratio (MIR) was highest in the North (0.88) and lowest in the Southeast region (0.44). There were significant regional differences in PCa treatment rates (per new cases); the Midwest region had the highest median annual surgery rate (0.63) while the North region had the highest median annual systemic therapy rate (0.75) and the lowest radiation therapy rate (0.06). Temporal analysis of the data showed significant change in annual rate trends after the year 2018 for PCSIR (coefficient [] = +3.66, < 0.001), any treatment ( = -0.06, = 0.016), surgery ([SR] = +0.05, = 0.017) radiation therapy ([RTR] = -0.06, = 0.005) and systemic therapy ([STR] = -0.10, = 0.002). After the 2020 pandemic, annual PCSIR decreased ( = -2.15, = 0.002) but annual PCSMR, MIR, and treatment rates remained stable. Correlation studies showed that the PCSIR was strongly negatively correlated with STR ( < 0.001) and positively correlated with RTR ( = 0.004). MIR was positively correlated with STR ( < 0.001) and negatively correlated with the number of robotic surgical systems per million population ( = 0.003).

CONCLUSION

Our data shows that PCa care is dependent on the region and is likely influenced by access to treatment options. Furthermore, changes after the year 2018 underscore the influence of international guidelines on Brazilian clinicians' decision-making especially concerning population screening which in turn affected incidence and treatment rates. Limitation of our study includes limited patient-related information and data on private practices as well as an unknown impact of traveling patients.