Analysis on age-period-cohort model of incidence and mortality of prostate cancer in China from 1992 to 2021 and grey prediction_Chinese Journal of Evidence-Based Medicine

Authors：

CAI Hongxia , YIN Ruoyun , QIAN Meng , XIONG Huan ,  YANG Xiujuan

Medical Quality Management Department, Chengdu Seventh People's Hospital (Chengdu Cancer Hospital/Affiliated Cancer Hospital of Chengdu Medical College), Chengdu 610041, P. R. China;

Corresponding author：

YANG Xiujuan, Email: 3296736657@qq.com

Keywords：

Prostate cancer; Incidence; Mortality; Age-period-cohort model; Grey prediction model; China

DOI：

10.7507/1672-2531.202408100

Video：

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Objective To analyze the epidemic trend of prostate cancer in China from 1992 to 2021, and predict its epidemic trend from 2022 to 2032. Methods Based on the data of Chinese population and prostate cancer incidence and mortality from Global Burden of Disease Database, the Joinpoint log-linear model was used to analyze the trend of prostate cancer incidence and mortality, use the age-period-cohort model to analyze the effects of age, period and cohort on changes in incidence and mortality, and the gray prediction model was used to predict the trend of prostate cancer. Results From 1992 to 2021, the incidence and mortality of prostate cancer in China showed an upward trend, with AAPC of 5.652% (P<0.001) and 3.466% (P<0.001), and the AAPC of age-standardized incidence decreased to 1.990% (P<0.001), the age-standardized mortality showed a downward trend and was not statistically significant. The results of the age-period-cohort model showed that the net drift values of prostate cancer incidence and mortality were 3.03% and -1.06%, respectively, and the risk of incidence and mortality gradually increased with age and period. The results of the grey prediction model showed that the incidence and mortality of prostate cancer showed an upward trend from 2022 to 2032, and the incidence trend was more obvious. Conclusion The incidence and mortality of prostate cancer in China showed an increasing trend, with a heavy disease burden and severe forms of prevention and control, so it is necessary to do a good job in monitoring the incidence and mortality of prostate cancer, and strengthen the efficient screening, early diagnosis and treatment of prostate cancer.

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9.	林建潮. 灰色预测模型在Excel中的实现及运用. 中国医院统计, 2021, 28(3): 286-288.
10.	张敏, 段朝晖, 徐杰茹, 等. 基于GBD数据分析与预测2000-2030年中国胰腺癌发病与死亡趋势. 中国肿瘤, 2022, 31(11): 862-868.
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18.	周孟孟, 徐文超, 俞浩. 1990-2019年江苏省男性前列腺癌疾病负担分析. 实用肿瘤学杂志, 2023, 37(1): 1-5.
19.	王丹, 邹雪平, 成姝雯, 等. 2015-2019年四川省肿瘤登记地区前列腺癌流行特征及早死疾病负担趋势分析. 中国肿瘤, 2024, 33(9): 709-715.
20.	刘硕, 王硕, 李慧超, 等. 2000-2017年北京市前列腺癌发病和死亡流行趋势及发病年龄变化特征分析. 中国肿瘤, 2021, 30(7): 495-505.
21.	国务院第七次全国人口普查领导小组办公室. 2020年第七次全国人口普查主要数据. 中国统计出版社, 2021, 7(1): 66.
22.	Schwartz SM. Epidemiology of cancer. Clin Chem, 2024, 70(1): 140-149.
23.	Popovici D, Stanisav C, Pricop M, et al. Associations between body mass index and prostate cancer: the impact on progression-free survival. Medicina (Kaunas), 2023, 59(2): 289.
24.	Rahmati S, Azami M, Delpisheh A, et al. Total calcium (dietary and supplementary) intake and prostate cancer: a systematic review and meta-analysis. Asian Pac J Cancer Prev, 2018, 19(6): 1449-1456.
25.	Key TJ, Bradbury KE, Perez-Cornago A, et al. Diet, nutrition, and cancer risk: what do we know and what is the way forward. BMJ, 2020, 368: m511.
26.	徐杰茹, 陈磊, 张敏, 等. 1990-2019年中国卵巢癌发病与死亡趋势及其年龄-时期-队列模型分析. 中国肿瘤, 2022, 31(4): 276-283.

1. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2024, 74(3): 229-263.
2. 郑荣寿, 陈茹, 韩冰峰, 等. 2022年中国恶性肿瘤流行情况分析. 中华肿瘤杂志, 2024, 46(3): 221-231.
3. 刘灿, 李想, 王雷, 等. 2005-2014年中国前列腺癌流行特征. 中华疾病控制杂志, 2021, 25(7): 806-811.
4. 董娟, 孔虹倩, 文洪梅, 等. 云南省肿瘤登记地区2020年前列腺癌发病和死亡情况及2012-2020年趋势分析. 实用肿瘤学杂志, 2024, 38(6): 383-387.
5. GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet, 2024, 403(10440): 2133-2161.
6. GBD 2021 Risk Factors Collaborators. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet, 2024, 403(10440): 2162-2203.
7. 李辉章, 杜灵彬. Joinpoint回归模型在肿瘤流行病学时间趋势分析中的应用. 中华预防医学杂志, 2020, 54(8): 908-912.
8. 蔡迎彬, 刘广超, 梁智超, 等. 2002-2021年中国城乡居民胃癌死亡趋势年龄-时期-队列模型分析. 中华肿瘤防治杂志, 2024, 31(8): 478-485.
9. 林建潮. 灰色预测模型在Excel中的实现及运用. 中国医院统计, 2021, 28(3): 286-288.
10. 张敏, 段朝晖, 徐杰茹, 等. 基于GBD数据分析与预测2000-2030年中国胰腺癌发病与死亡趋势. 中国肿瘤, 2022, 31(11): 862-868.
11. 成晓芬, 闵淑慧, 郭芮绮, 等. 1990-2019年中国胃癌发病与死亡率年龄-时期-队列分析及2020-2030年变化趋势预测. 中国肿瘤, 2023, 32(6): 454-461.
12. Siegel RL, Giaquinto AN, Jemal A. Cancer statistics, 2024. CA Cancer J Clin, 2024, 74(1): 12-49.
13. Liu X, Yu C, Bi Y, et al. Trends and age-period-cohort effect on incidence and mortality of prostate cancer from 1990 to 2017 in China. Public Health, 2019, 172: 70-80.
14. Zeng H, Chen W, Zheng R, et al. Changing cancer survival in China during 2003-15: a pooled analysis of 17 population-based cancer registries. Lancet Glob Health, 2018, 6(5): e555-e567.
15. Zhu Y, Mo M, Wei Y, et al. Epidemiology and genomics of prostate cancer in Asian men. Nat Rev Urol, 2021, 18(5): 282-301.
16. 孙金义, 严亚琼, 郭燕, 等. 2010-2019年武汉市前列腺癌疾病负担分析及死亡率预测. 公共卫生与预防医学, 2024, 35(1): 39-44.
17. 洪思捷, 宋芯蕊, 陈丹琪, 等. 2013-2017年广东省男性前列腺癌流行特征及趋势. 现代预防医学, 2023, 50(8): 1356-1360.
18. 周孟孟, 徐文超, 俞浩. 1990-2019年江苏省男性前列腺癌疾病负担分析. 实用肿瘤学杂志, 2023, 37(1): 1-5.
19. 王丹, 邹雪平, 成姝雯, 等. 2015-2019年四川省肿瘤登记地区前列腺癌流行特征及早死疾病负担趋势分析. 中国肿瘤, 2024, 33(9): 709-715.
20. 刘硕, 王硕, 李慧超, 等. 2000-2017年北京市前列腺癌发病和死亡流行趋势及发病年龄变化特征分析. 中国肿瘤, 2021, 30(7): 495-505.
21. 国务院第七次全国人口普查领导小组办公室. 2020年第七次全国人口普查主要数据. 中国统计出版社, 2021, 7(1): 66.
22. Schwartz SM. Epidemiology of cancer. Clin Chem, 2024, 70(1): 140-149.
23. Popovici D, Stanisav C, Pricop M, et al. Associations between body mass index and prostate cancer: the impact on progression-free survival. Medicina (Kaunas), 2023, 59(2): 289.
24. Rahmati S, Azami M, Delpisheh A, et al. Total calcium (dietary and supplementary) intake and prostate cancer: a systematic review and meta-analysis. Asian Pac J Cancer Prev, 2018, 19(6): 1449-1456.
25. Key TJ, Bradbury KE, Perez-Cornago A, et al. Diet, nutrition, and cancer risk: what do we know and what is the way forward. BMJ, 2020, 368: m511.
26. 徐杰茹, 陈磊, 张敏, 等. 1990-2019年中国卵巢癌发病与死亡趋势及其年龄-时期-队列模型分析. 中国肿瘤, 2022, 31(4): 276-283.

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Latest ArticlesAnalysis on age-period-cohort model of incidence and mortality of prostate cancer in China from 1992 to 2021 and grey prediction

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