在美国，子宫癌发病率正在上升，其中少数族裔的发病率增幅最大。我们使用新方法进行了年龄-时期-队列分析，以检查诊断年龄 (age)、诊断年份 (period) 和出生队列 (cohort) 对子宫癌发病率趋势的影响。我们使用子宫癌发病率数据来自监测、流行病学和最终结果 (SEER) 12 数据库 (1992-2019) 的数据，并进行了子宫切除术校正。我们生成了六幅图来可视化年龄、周期和队列效应，并使用互信息来估计年龄、周期和队列效应（单独和组合）对子宫癌发病率（总体以及按种族、民族和组织学）的贡献百分比。显示出子宫癌在后期有所增加，并且 1933 年左右的队列效应显示，与早期和后期队列相比，子宫癌的发病率较低。年龄、时期和队列效应合计对发病率贡献了 86.6%（95% CI：86.4%、86.9%）。年龄效应的贡献最大（65.1%，95% CI：64.3%，65.9），其次是队列（20.7%，95% CI：20.1%，21.3%）和时期（14.2%，95% CI：13.7%， 14.8%）的影响。 Hexmaps 显示近年来非西班牙裔黑人和非子宫内膜样肿瘤的发病率较高。年龄效应对子宫癌发病率的影响最大，其次是总体和跨种族、族裔群体和组织学的队列和时期效应。这些发现可以为子宫癌提供信息针对针对不同年龄、时期或队列的风险因素的干预措施效果的癌症模型研究。版权所有 © 2024 Elsevier Inc. 保留所有权利。

In the U.S., uterine cancer incidence is rising, with racial and ethnic minorities experiencing the largest increases. We performed age-period-cohort analyses using novel methods to examine the contribution of age at diagnosis (age), year of diagnosis (period), and birth cohort (cohort), to trends in uterine cancer incidence.We used uterine cancer incidence data from the Surveillance, Epidemiology, and End Result (SEER) 12 database (1992-2019), and performed hysterectomy-correction. We generated hexamaps to visualize age, period, and cohort effects, and used mutual information to estimate the percent contribution of age, period, and cohort effects, individually and combined, on uterine cancer incidence, overall and by race and ethnicity and histology.Hexamaps showed an increase in uterine cancer in later time periods, and a cohort effect around 1933 showing a lower incidence compared with earlier and later cohorts. Age, period, and cohort effects combined contributed 86.6% (95% CI: 86.4%, 86.9%) to the incidence. Age effects had the greatest contribution (65.1%, 95% CI: 64.3%, 65.9), followed by cohort (20.7%, 95% CI: 20.1%, 21.3%) and period (14.2%, 95% CI: 13.7%, 14.8%) effects. Hexamaps showed higher incidence in recent years for non-Hispanic Blacks and non-endometrioid tumors.Age effects had the largest contribution to uterine cancer incidence, followed by cohort and period effects overall and across racial and ethnic groups and histologies.These findings can inform uterine cancer modeling studies on the effects of interventions that target risk factors which may vary across age, period, or cohort.Copyright © 2024 Elsevier Inc. All rights reserved.