PDF(Pubmed)
Abstract：
UNASSIGNED: Racial/ethnic disparities in prostate cancer are reported in the United States (US). However, long-term trends and contributors of racial/ethnic disparities in all-cause and cause-specific death among patients with prostate cancer remain unclear. We analysed the trends and contributors of racial/ethnic disparities in prostate cancer survivors according to the cause of death in the US over 25 years.
UNASSIGNED: In this retrospective, population-based longitudinal cohort study, we identified patients diagnosed with first primary prostate cancer between 1995 and 2019, with follow-up until Dec 31, 2019, using population-based cancer registries\' data from the Surveillance, Epidemiology, and End Results (SEER) Program. We calculated the cumulative incidence of death for each racial/ethnic group (Black, white, Hispanic, Asian or Pacific Islander [API], and American Indian or Alaska Native [AI/AN] people), by diagnostic period and cause of death. We quantified absolute disparities using rate changes for the 5-year cumulative incidence of death between racial/ethnic groups and diagnostic periods. We estimated relative (Hazard ratios [HR]) racial/ethnic disparities and the percentage of potential factors contributed to racial/ethnic disparities using Cox regression models.
UNASSIGNED: Despite a decreasing trend in the cumulative risk of death across five racial/ethnic groups, AI/AN and Black patients consistently had the highest rate of death between 1995 and 2019 with an adjusted HR of 1.48 (1.40-1.58) and 1.40 (1.38-1.42) respectively. The disparities in all-cause mortality between AI/AN and white patients increased over time, with adjusted HR 1.32 (1.17-1.49) in 1995-1999 and 1.95 (1.53-2.49) in 2015-2019. Adjustment of stage at diagnosis, initial treatment, tumor grade, and household income explained 33% and 24% of the AI/AN-white and Black-white disparities in all-cause death among patients with prostate cancer.
UNASSIGNED: The enduring racial/ethnic disparities in patients with prostate cancer, call for new interventions to eliminate health disparities. Our study provides important evidence and ways to address racial/ethnic inequality.
UNASSIGNED: National Key R&D Program of China, National Natural Science Foundation of China, Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support, the Open Research Fund from Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Key Projects of Philosophy and Social Sciences Research, Ministry of Education of China.
UNASSIGNED: In this retrospective, population-based longitudinal cohort study, we identified patients diagnosed with first primary prostate cancer between 1995 and 2019, with follow-up until Dec 31, 2019, using population-based cancer registries\' data from the Surveillance, Epidemiology, and End Results (SEER) Program. We calculated the cumulative incidence of death for each racial/ethnic group (Black, white, Hispanic, Asian or Pacific Islander [API], and American Indian or Alaska Native [AI/AN] people), by diagnostic period and cause of death. We quantified absolute disparities using rate changes for the 5-year cumulative incidence of death between racial/ethnic groups and diagnostic periods. We estimated relative (Hazard ratios [HR]) racial/ethnic disparities and the percentage of potential factors contributed to racial/ethnic disparities using Cox regression models.
UNASSIGNED: Despite a decreasing trend in the cumulative risk of death across five racial/ethnic groups, AI/AN and Black patients consistently had the highest rate of death between 1995 and 2019 with an adjusted HR of 1.48 (1.40-1.58) and 1.40 (1.38-1.42) respectively. The disparities in all-cause mortality between AI/AN and white patients increased over time, with adjusted HR 1.32 (1.17-1.49) in 1995-1999 and 1.95 (1.53-2.49) in 2015-2019. Adjustment of stage at diagnosis, initial treatment, tumor grade, and household income explained 33% and 24% of the AI/AN-white and Black-white disparities in all-cause death among patients with prostate cancer.
UNASSIGNED: The enduring racial/ethnic disparities in patients with prostate cancer, call for new interventions to eliminate health disparities. Our study provides important evidence and ways to address racial/ethnic inequality.
UNASSIGNED: National Key R&D Program of China, National Natural Science Foundation of China, Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support, the Open Research Fund from Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Key Projects of Philosophy and Social Sciences Research, Ministry of Education of China.
摘要：
■在美国(US)报道了前列腺癌的种族/种族差异。然而,前列腺癌患者全因死亡和特定原因死亡的长期趋势和种族/族裔差异的成因尚不清楚.根据美国25年的死亡原因，我们分析了前列腺癌幸存者种族/民族差异的趋势和贡献者。
■在这次回顾中，基于人群的纵向队列研究，我们确定了1995年至2019年间诊断为第一原发性前列腺癌的患者，随访至2019年12月31日，使用来自监测的基于人群的癌症登记数据，流行病学,和最终结果（SEER）计划。我们计算了每个种族/族裔群体的累计死亡发生率(黑人，白色,西班牙裔,亚洲或太平洋岛民[API]，和美洲印第安人或阿拉斯加原住民[AI/AN]人)，诊断期和死因。我们使用种族/族裔群体和诊断期之间5年累计死亡发生率的比率变化来量化绝对差异。我们使用Cox回归模型估计了相对（危害比[HR]）种族/族裔差异以及导致种族/族裔差异的潜在因素百分比。
■尽管五个种族/民族的累计死亡风险呈下降趋势，AI/AN和Black患者在1995年至2019年期间的死亡率始终最高，调整后的HR分别为1.48（1.40-1.58）和1.40（1.38-1.42）。AI/AN和白人患者之间的全因死亡率差异随着时间的推移而增加，1995-1999年调整后HR1.32（1.17-1.49），2015-2019年调整后HR1.95（1.53-2.49）。诊断阶段的调整，初始治疗,肿瘤分级,和家庭收入解释了33％和24％的AI/AN-白色和黑白差异前列腺癌患者的全因死亡。
■前列腺癌患者中持久的种族/民族差异，呼吁采取新的干预措施来消除健康差距。我们的研究提供了解决种族/民族不平等的重要证据和方法。
■国家重点研发计划,国家自然科学基金,北京市医院临床医学管理局发展专项资金支持，北京基于大数据的精准医学先进创新中心开放研究基金，哲学社会科学研究重点项目,中国教育部。
■在这次回顾中，基于人群的纵向队列研究，我们确定了1995年至2019年间诊断为第一原发性前列腺癌的患者，随访至2019年12月31日，使用来自监测的基于人群的癌症登记数据，流行病学,和最终结果（SEER）计划。我们计算了每个种族/族裔群体的累计死亡发生率(黑人，白色,西班牙裔,亚洲或太平洋岛民[API]，和美洲印第安人或阿拉斯加原住民[AI/AN]人)，诊断期和死因。我们使用种族/族裔群体和诊断期之间5年累计死亡发生率的比率变化来量化绝对差异。我们使用Cox回归模型估计了相对（危害比[HR]）种族/族裔差异以及导致种族/族裔差异的潜在因素百分比。
■尽管五个种族/民族的累计死亡风险呈下降趋势，AI/AN和Black患者在1995年至2019年期间的死亡率始终最高，调整后的HR分别为1.48（1.40-1.58）和1.40（1.38-1.42）。AI/AN和白人患者之间的全因死亡率差异随着时间的推移而增加，1995-1999年调整后HR1.32（1.17-1.49），2015-2019年调整后HR1.95（1.53-2.49）。诊断阶段的调整，初始治疗,肿瘤分级,和家庭收入解释了33％和24％的AI/AN-白色和黑白差异前列腺癌患者的全因死亡。
■前列腺癌患者中持久的种族/民族差异，呼吁采取新的干预措施来消除健康差距。我们的研究提供了解决种族/民族不平等的重要证据和方法。
■国家重点研发计划,国家自然科学基金,北京市医院临床医学管理局发展专项资金支持，北京基于大数据的精准医学先进创新中心开放研究基金，哲学社会科学研究重点项目,中国教育部。
