中国全科医学 ›› 2022, Vol. 25 ›› Issue (13): 1564-1568.DOI: 10.12114/j.issn.1007-9572.2022.0074

所属专题: 肿瘤最新文章合集

• 论著·人群健康与流行病学研究 • 上一篇    下一篇

1993—2017年中国宫颈癌发病率和死亡率长期趋势的年龄-时期-队列模型分析

王瑾瑶1, 张年萍2, 白志强3, 王震坤4,*()   

  1. 1.037009 山西省大同市,山西大同大学医学院预防医学系
    2.037009 山西省大同市,山西大同大学医学院院长办公室
    3.037009 山西省大同市,山西大同大学生命科学学院
    4.430030 湖北省武汉市,华中科技大学同济医学院附属同济医院党委办公室
  • 收稿日期:2022-02-08 修回日期:2022-04-06 出版日期:2022-04-12 发布日期:2022-04-22
  • 通讯作者: 王震坤
  • 王瑾瑶,张年萍,白志强,等. 1993—2017年中国宫颈癌发病率和死亡率长期趋势的年龄-时期-队列模型分析[J].中国全科医学,2022,25(13):1564-1568.[www.chinagp.net]
    作者贡献:王瑾瑶进行文章的构思与设计、统计学处理、结果的分析与解释、论文撰写与修订、文章的质量控制及审校,并对文章整体负责,监督管理;张年萍进行研究的实施与可行性分析;白志强进行数据收集;王震坤进行数据整理。
  • 基金资助:
    国家自然科学基金青年科学基金项目(81903396)——基于时空数据挖掘的国人伤害死亡风险分布特征及影响因素研究

Age-Period-Cohort Analysis of Secular Trends of Cervical Cancer Incidence and Mortality in China, 1993—2017

Jinyao WANG1, Nianping ZHANG2, Zhiqiang BAI3, Zhenkun WANG4,*()   

  1. 1. Department of Preventive Medicine, Shanxi Datong University, Datong 037009, China
    2. The Dean's Office, Shanxi Datong University, Datong 037009, China
    3. School of Life Sciences, Shanxi Datong University, Datong 037009, China
    4. Party Committee Organization Department, Tongji Medical College of Huazhong University of Science & Technology, Wuhan 430072, China
  • Received:2022-02-08 Revised:2022-04-06 Published:2022-04-12 Online:2022-04-22
  • Contact: Zhenkun WANG
  • About author:
    WANG J Y, ZHANG N P, BAI Z Q, et al. Age-period-cohort analysis of secular trends of cervical cancer incidence and mortality in China, 1993—2017[J]. Chinese General Practice, 2022, 25 (13) : 1564-1568.

摘要: 背景 宫颈癌是女性常见的妇科肿瘤之一,占所有女性癌症的12%左右。该病与肝癌一样,约有85%的患者来自欠发达地区。 目的 探讨1993—2017年我国宫颈癌发病率和死亡率的长期趋势。 方法 本研究中所有的发病及死亡数据来源于美国华盛顿大学健康测量与评价中心(IHME)疾病负担网站。本研究首先运用Joinpoint回归分析模型,对中国1993—2017年宫颈癌发病率和死亡率趋势进行分段描述,进一步利用年龄-时期-队列模型和内生因子法估计成年女性宫颈癌发病及死亡风险的年龄效应、时期效应和队列效应。 结果 总的来说,1993—1998年中国宫颈癌发病率和死亡率呈下降趋势,2008—2015年呈上升趋势。Joinpoint回归模型结果显示:1993—2017年,女性宫颈癌的标化发病率从9.54/10万增加到10.88/10万〔AAPC(95%CI)=0.6(0.3,0.9),P<0.05〕,而标化死亡率则从4.88/10万下降到4.48/10万〔AAPC(95%CI)=-0.3(-0.5,-0.1),P<0.05〕。此外,在59岁之前,随着年龄的增长,宫颈癌发病率的年龄效应明显增加,并且发病率和死亡率的周期效应总体呈上升趋势。除某些时期外,出生队列的发病率和死亡率风险呈下降趋势,1916—1920年出生队列的发病率和死亡率风险均达到峰值,然后趋于平稳,在年轻一代中略有下降。 结论 总体而言,队列效应的降低可能导致癌症发病率和死亡率的降低,而年龄效应和周期效应的增加可能导致癌症发病率和死亡率的增加。

关键词: 宫颈肿瘤, 发病率, 死亡率, Joinpoint回归模型, 年龄-时期-队列模型

Abstract:

Background

Cervical cancer is the seventh most common cancer globally, and the fourth most common cancer in women, accounting for about 12% of all cancers diagnosed among females. Cervical cancer and liver cancer are similar with respect to high prevalent region, with about 85% of the sufferers are from less developed regions.

Objective

To assess the long-term trends of cervical cancer incidence and mortality in China.

Methods

Data about cervical cancer incidence and mortality in Chinese adult females were extracted from the Institute for Health Metrics and Evaluation. Joinpoint regression was used for analyzing the trends of cervical cancer incidence and mortality during 1993—2017. The age-period-cohort model and intrinsic estimator method were adopted for analyzing the effects of age, period, and cohort on cervical cancer incidence and mortality.

Results

Overall, the trends of cervical cancer incidence and mortality totally experienced a significant decrease during 1993—1998, and showed an increasing trend during 2008—2015. Joinpoint regression analysis showed that from 1993 to 2017, the standardized incidence ratio of cervical cancer increased from 9.54/100 000 to 10.88/100 000〔AAPC (95%CI) =0.6 (0.3, 0.9) , P<0.05〕, while its standardized mortality ratio decreased from 4.88/100 000 to 4.48/100 000〔AAPC (95%CI) =-0.3 (-0.5, -0.1) , P<0.05〕. Moreover, cervical cancer incidence increased significantly with age before the age of 59, and the period effect exhibited a general upward trend for both incidence and mortality. The incidence and mortality risks by birth cohort showed a declining trend except for some periods and the risks all peaked in the cohort born in 1916—1920, then leveled off and slightly decreased in younger generations.

Conclusion

Taken together, the decrease in the cohort effect might contribute to the decrease in cervical cancer incidence and mortality rates, while the increase of age and period effects might lead to the increase in its morbidity and mortality rates.

Key words: Uterine cervical neoplasms, Incidence, Mortality, Joinpoint regression, Age-period-cohort model