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巴西前列腺癌的时间和地域趋势。

Prostate cancer temporal and regional trends in Brazil.

机构信息

UroScience, School of Medical Sciences, State University of Campinas, Campinas, 13083-872, Brazil.

Division of Urology, Faculdade de Medicina do ABC, São Paulo, 09051-040, Brazil.

出版信息

Oncol Res. 2024 Sep 18;32(10):1565-1573. doi: 10.32604/or.2024.052179. eCollection 2024.

DOI:10.32604/or.2024.052179
PMID:39308515
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11413836/
Abstract

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.

摘要

目的

巴西统一卫生系统(Sistema Único de Saúde-SUS)是巴西的全民公共医疗体系,拥有全国性的患者数据库。我们的主要目标是分析地区和时间趋势,而我们的次要目标是确定各州卫生经济状况与前列腺癌(PCa)流行病学之间的相关性。

方法

我们分析了巴西全国范围内 2013 年至 2021 年间通过 SUS 的信息技术部门(DATA-SUS)收集的前列腺癌(PCa)发病率、死亡率和治疗数据,每月使用国际疾病分类(ICD-10)代码更新。

结果

在此期间,巴西 50 岁及以上男性中报告了 273,933 例新的前列腺癌病例和 135,336 例前列腺癌死亡病例。中位年度前列腺癌特异性发病率(PCSIR)范围为东南部 14.7 例,北部 6.9 例,中位年度前列腺癌特异性死亡率(PCSMR)范围为东北部 7.7 例,南部 6.0 例(每 10,000 名 50 岁以上男性)。北部的中位年度死亡率与发病率比(MIR)最高(0.88),东南部最低(0.44)。前列腺癌治疗率(每例新发病例)存在显著的地区差异;中西部地区的中位年度手术率最高(0.63),而北部地区的中位年度系统治疗率最高(0.75),放射治疗率最低(0.06)。数据的时间分析显示,2018 年后 PCSIR(系数[]=+3.66,<0.001)、任何治疗(= -0.06,=0.016)、手术([SR]=+0.05,=0.017)、放射治疗([RTR]=-0.06,=0.005)和系统治疗([STR]=-0.10,=0.002)的年度率趋势发生了显著变化。2020 年大流行后,PCSIR 年度下降(= -2.15,=0.002),但 PCSMR、MIR 和治疗率保持稳定。相关性研究表明,PCSIR 与 STR 呈强烈负相关(<0.001),与 RTR 呈正相关(=0.004)。MIR 与 STR 呈正相关(<0.001),与每百万人口的机器人手术系统数量呈负相关(=0.003)。

结论

我们的数据表明,前列腺癌的治疗取决于地区,并且可能受到治疗选择的影响。此外,2018 年后的变化突显了国际指南对巴西临床医生决策的影响,特别是对人群筛查的影响,这反过来又影响了发病率和治疗率。本研究的局限性包括患者相关信息和私人诊所数据的局限性,以及对流动患者的未知影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2869/11413836/8780db162627/OncolRes-32-52179-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2869/11413836/a253fd06dc72/OncolRes-32-52179-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2869/11413836/00ef5da22f3e/OncolRes-32-52179-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2869/11413836/41118174e4a8/OncolRes-32-52179-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2869/11413836/8780db162627/OncolRes-32-52179-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2869/11413836/a253fd06dc72/OncolRes-32-52179-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2869/11413836/00ef5da22f3e/OncolRes-32-52179-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2869/11413836/41118174e4a8/OncolRes-32-52179-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2869/11413836/8780db162627/OncolRes-32-52179-f004.jpg

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