根据组织学亚型划分的卵巢癌的全球发病率:一项基于人群的癌症登记研究。
Global Incidence of Ovarian Cancer According to Histologic Subtype: A Population-Based Cancer Registry Study.
发表日期:2024 May
作者:
Minmin Wang, Yanxin Bi, Yinzi Jin, Zhi-Jie Zheng
来源:
MOLECULAR & CELLULAR PROTEOMICS
摘要:
卵巢癌可分为不同的组织学亚型,具有不同的可识别危险因素、分子组成、临床特征和治疗。卵巢癌亚型的全球发病率仍然有限,特别是在没有高质量癌症登记系统的低收入和中等收入国家 (LMIC)。我们使用来自五大洲癌症发病率项目的基于人口的癌症登记处的数据来计算卵巢癌浆液性、粘液性、子宫内膜样癌、透明细胞癌和其他组织学亚型的比例。将比例应用于 2020 年全球癌症观察站估计的卵巢癌患者人数。计算了年龄标准化发病率。全球估计有 133,818 名新发浆液性癌患者、35,712 名新发粘液癌患者、29,319 名新发子宫内膜样癌患者,2020年新发现17,894名透明细胞癌患者。卵巢癌组织学亚型的分布呈现区域差异。东欧的浆液性癌和粘液性癌的发病率最高,而北非和东亚的子宫内膜样癌和透明细胞癌的负担最高。这项研究提供了卵巢癌组织学亚型的全球发病率概况,特别是在缺乏全面的中低收入国家登记系统。我们的分析为疾病负担提供了宝贵的见解,并为预防卵巢癌的定制策略提供了指导。
Ovarian cancer can be categorized into distinct histologic subtypes with varying identifiable risk factors, molecular composition, clinical features, and treatment. The global incidence of ovarian cancer subtypes remains limited, especially in low- and middle-income countries (LMICs) without high-quality cancer registry systems.We used data from population-based cancer registries of the Cancer Incidence in Five Continents project to calculate the proportions of serous, mucinous, endometrioid, clear cell, and other histologic subtypes of ovarian cancer. Proportions were applied to the estimated numbers of patients with ovarian cancer from Global Cancer Observatory 2020. Age-standardized incidence rates were calculated.Globally, an estimated 133,818 new patients of serous cancer, 35,712 new patients of mucinous cancer, 29,319 new patients of endometrioid cancer, and 17,894 new patients of clear cell cancer were identified in 2020. The distribution of ovarian cancer histologic subtypes exhibited regional variation. Eastern Europe had the highest rate of serous and mucinous carcinomas, whereas Northern Africa and Eastern Asia had the highest burden of endometrioid and clear cell carcinomas, respectively.This study provides a global incidence landscape of histologic subtypes of ovarian cancer, particularly in LMICs lacking comprehensive registry systems. Our analysis offers valuable insights into disease burden and guidance for tailored strategies for prevention of ovarian cancer.