Hao Shuxiu, Guo Liyuan, Guo Sihong, Feng Chen, Sun Huixin, Du Linlin, Li Guijin, Wang Cheng, Zhang Yu, Lv Cunqi, Zeng Qingyu, Li Jiacheng, Wang Xinshu, Wang Tong, Tang Liping, Li Qi
Institute of Keshan Disease, Chinese Center for Endemic Disease Control, Harbin Medical University, Harbin, 150081, People's Republic of China.
NHC Key Laboratory of Etiology and Epidemiology, Harbin Medical University, 157 Baojian Road, Harbin, 150081, People's Republic of China.
Sci Rep. 2025 May 25;15(1):18191. doi: 10.1038/s41598-025-02164-y.
Cancer registration in mainland China traditionally focuses on household-registered residents (HRR) and does not include the migrant population among permanent residents (PR), leading to significant selection bias. Estimating incidence among permanent residents provides a less biased and more representative measure of the true incidence. We developed a Bayesian Integrated Nested Laplace Approximation with Stochastic Partial Differential Equation model, incorporating inter-provincial migrant population weights to estimate uterine corpus cancer incidence among permanent residents. The findings revealed a substantial interprovincial migrant population of 67,509,881 individuals, with Shanghai and Beijing showing relatively high difference proportions of 39.6% and 37.0%, respectively. Nationally, the differences in estimated uterine corpus cancer incidence between female PR and HRR were marginal, ranging from 0.2/100,000 in Qinghai to - 0.4/100,000 in Shanghai. The analysis estimated that the provinces with the largest differences between incident cases among female PR and HRR were Henan (- 899 cases, 15.7%) and Guangdong (630 cases, 13.7%). This research holds significant implications for countries relying on HRR-based cancer registration system, particularly those contending with substantial migrant populations. The estimated differences in uterine corpus cancer incidence between PR and HRR provide crucial data support for optimizing prevention strategies and enabling precise allocation of regional healthcare resources.
中国大陆的癌症登记传统上侧重于户籍居民，并不包括常住人口中的流动人口，这导致了显著的选择偏差。估算常住人口中的发病率能提供一个偏差较小且更具代表性的真实发病率衡量指标。我们开发了一种带有随机偏微分方程模型的贝叶斯集成嵌套拉普拉斯近似方法，纳入省际流动人口权重来估算常住人口中的子宫体癌发病率。研究结果显示，省际流动人口数量庞大，达67509881人，上海和北京的差异比例相对较高，分别为39.6%和37.0%。在全国范围内，女性常住人口和户籍居民之间估算的子宫体癌发病率差异很小，从青海的每10万人0.2例到上海的每10万人 -0.4例不等。分析估计，女性常住人口和户籍居民之间发病病例差异最大的省份是河南（-899例，15.7%）和广东（630例，13.7%）。这项研究对依赖基于户籍居民的癌症登记系统的国家具有重要意义，特别是那些面临大量流动人口的国家。常住人口和户籍居民之间子宫体癌发病率的估计差异为优化预防策略和实现区域医疗资源的精准分配提供了关键数据支持。
