Washington Iii Samuel L, Fakunle Mary, Wang Lufan, Braun Avery E, Leapman Michael, Cowan Janet E, Cooperberg Matthew R
Department of Urology, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA 94143, United States.
Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA 94143, United States.
JNCI Cancer Spectr. 2024 Nov 1;8(6). doi: 10.1093/jncics/pkae109.
Local conditions where people live continue to influence prostate cancer outcomes. By examining local characteristics associated with trends in Black-White differences in prostate cancer-specific mortality over time, we aim to identify factors driving county-level prostate cancer-specific mortality disparities over a 15-year period.
We linked county-level data (Area Health Resource File) with clinicodemographic data of men with prostate cancer (Surveillance, Epidemiology, and End Results registry) from 2005 to 2020. Generalized linear mixed models evaluated associations between race and county-level age-standardized prostate cancer-specific mortality, adjusting for age; year of death; rurality; county-level education; income; uninsured rates; and densities of urologists, radiologists, primary care practitioners, and hospital beds.
In 1085 counties, 185 390 patients were identified of which 15.8% were non-Hispanic Black. Racial disparities in prostate cancer-specific mortality narrowed from 2005 to 2020 (25.4 per 100 000 to 19.2 per 100 000 overall, 57.9 per 100 000 to 38 per 100 000 for non-Hispanic Black patients, and 23.4 per 100 000 to 18.3 per 100 000 for non-Hispanic White patients). For non-Hispanic Black and non-Hispanic White patients, county prostate cancer-specific mortality changes varied greatly (-65% to +77% and -61% to +112%, respectively). From 2016 to 2020, non-Hispanic Black patients harbored greater prostate cancer-specific mortality risk (relative risk = 2.09, 95% confidence interval [CI] = 2.01 to 2.18); higher radiation oncologist density was associated with lower mortality risk (relative risk = 0.93, 95% CI = 0.89 to 0.98), while other practitioner densities were not.
Although overall rates improved, specific counties experienced worsening race-based disparities over time. Identifying locations of highest (and lowest) mortality disparities remains critical to development of location-specific solutions to racial disparities in prostate cancer outcomes.
人们生活的当地环境持续影响前列腺癌的治疗结果。通过研究与前列腺癌特异性死亡率的黑白差异趋势相关的当地特征，我们旨在确定15年间驱动县级前列腺癌特异性死亡率差异的因素。
我们将县级数据（区域卫生资源文件）与2005年至2020年前列腺癌男性患者的临床人口统计学数据（监测、流行病学和最终结果登记处）相链接。广义线性混合模型评估了种族与县级年龄标准化前列腺癌特异性死亡率之间的关联，并对年龄、死亡年份、农村地区、县级教育程度、收入、未参保率以及泌尿科医生、放射科医生、初级保健医生和医院床位密度进行了调整。
在1085个县中，共识别出185390名患者，其中15.8%为非西班牙裔黑人。2005年至2020年期间，前列腺癌特异性死亡率的种族差异有所缩小（总体上从每10万人25.4例降至每10万人19.2例，非西班牙裔黑人患者从每10万人57.9例降至每10万人38例，非西班牙裔白人患者从每10万人23.4例降至每10万人18.3例）。对于非西班牙裔黑人和非西班牙裔白人患者，各县前列腺癌特异性死亡率变化差异很大（分别为-65%至+77%和-61%至+112%）。2016年至2020年期间，非西班牙裔黑人患者的前列腺癌特异性死亡风险更高（相对风险=2.09，95%置信区间[CI]=2.01至2.18）；放射肿瘤学家密度较高与较低的死亡风险相关（相对风险=0.93，95%CI=0.89至0.98），而其他从业者密度则不然。
尽管总体发病率有所改善，但随着时间的推移，特定县的种族差异却在恶化。确定死亡率差异最高（和最低）的地点对于制定针对前列腺癌治疗结果种族差异的特定地点解决方案仍然至关重要。
