Analysis and prediction of the incidence, morbidity and death of leukemia in China_West China Medical Journal

Authors：

TAN Xiwei ¹ , WANG Shihong ¹ , WANG Shuang ¹ , CAO Rudai ¹ , DING Yuanlin ¹ ,  ZHANG Bingsong ¹ ,  YU Haibing ^1,2,3,4

1. School of Public Health, Guangdong Medical University, Dongguan, Guangdong 523808, P. R. China;
2. the first Dongguan Affiliated Hospital of Guangdong Medical University, Dongguan, Guangdong 523808, P. R. China;
3. State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Dongguan, Guangdong 523808, P. R. China;
4. Dongguan Key Laboratory of Chronic Disease Prevention and Control, Dongguan, Guangdong 523808, P. R. China;

Corresponding?author：

ZHANG Bingsong, Email: zhangbingsong@gdmu.edu.cn; YU Haibing, Email: hby616688@gdmu.edu.cn

Keywords：

Leukemia; global burden of disease; changing trend; forecasting analysis

DOI：

10.7507/1002-0179.202403043

Video：

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Objective To analyze the prevalence of leukemia in China from 1990 to 2019, predict the incidence, morbidity and mortality of leukemia in China from 2020 to 2040, and provides reference for the formulation of leukemia-related prevention and treatment strategies in China. Methods Based on the 2019 Global Burden of Disease database, the incidence, morbidity and mortality data of leukemia in China from 1990 to 2019 were collected, and the rate of change and annual estimated percentage of change (EAPC) were used to describe the epidemic trend of the disease. The Autoregressive Moving Average (ARIMA) model was used to predict the prevalence of leukemia in China from 2020 to 2040. Results In 2019, the age-standardized incidence, age-standardized prevalence and age-standardized mortality rate of leukemia in China decreased by 17.62%, 10.97%, and 41.56%, respectively, compared with 1990, and an average annual decrease of 1.06%, 0.89%, and 2.05%, respectively (P<0.05). From 1990 to 2019, the reduction age-standardized incidence rate, age-standardized prevalence rate and age-standardized mortality rate in Chinese women (EAPC was 1.56%, 1.38%, and 2.62%, respectively) was higher than that of men (EAPC was 0.61%, 0.43%, and 1.59%, respectively). In 2019, the incidence and prevalence were highest in the age group under 5 years of age, and the mortality rate was the highest in the age group over 80 years old. The prediction results of ARIMA model showed that the age-standardized incidence rate and prevalence of leukemia in China showed an increasing trend from 2020 to 2040, while the age-standardized mortality rate showed a decreasing trend. It is estimated that by 2040, the age-standardized incidence rate, age-standardized prevalence rate, and age-standardized mortality rate of leukemia will be 14.06/100 000, 108.23/100 000, and 2.83/100 000. Conclusions From 1990 to 2019, the age-standardized incidence rate, age-standardized prevalence rate and age-standardized mortality rate of leukemia in China decreased year by year, but they were still at a high level. The prediction results show that the age-standardized incidence rate and age-standardized prevalence rate of leukemia in China will continue to increase from 2020 to 2040, and it is necessary to continue to strengthen the surveillance, prevention and control of leukemia in the future.

Citation： TAN Xiwei, WANG Shihong, WANG Shuang, CAO Rudai, DING Yuanlin, ZHANG Bingsong, YU Haibing. Analysis and prediction of the incidence, morbidity and death of leukemia in China. West China Medical Journal, 2024, 39(9): 1427-1434. doi: 10.7507/1002-0179.202403043 Copy

1.	Whiteley AE, Price TT, Cantelli G, et al. Leukaemia: a model metastatic disease. Nat Rev Cancer, 2021, 21(7): 461-475.
2.	GBD 2017 Disease and Injury Incidence and Prevalence Collaborators, Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet, 2018, 392(18): 1789-1858.
3.	Siegel RL, Miller KD, Wagle NS, et al. Cancer statistics, 2023. CA Cancer J Clin, 2023, 73(1): 17-48.
4.	劉蓓. 急性髓系白血病的免疫治療現狀. 蘭州大學學報(醫學版), 2021, 47(6): 1-9.
5.	Yang X, Wang J. Precision therapy for acute myeloid leukemia. J Hematol Oncol, 2018, 11(1): 3.
6.	Wu X, Du J, Li L, et al. Bayesian age-period-cohort prediction of mortality of type 2 diabetic kidney disease in China: a modeling study. Front Endocrinol (Lausanne), 2021, 12: 767263.
7.	Chen R, Sang L, Jiang M, et al. Longitudinal hematologic and immunologic variations associated with the progression of COVID-19 patients in China. J Allergy Clin Immunol, 2020, 146(1): 89-100.
8.	Wang KW, Deng C, Li JP, et al. Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network. Epidemiol Infect, 2017, 145(6): 1118-1129.
9.	Torre LA, Siegel RL, Ward EM, et al. Global cancer incidence and mortality rates and trends--an update. Cancer Epidemiol Biomarkers Prev, 2016, 25(1): 16-27.
10.	中華人民共和國國家衛生健康委員會醫療應急司. 健康中國行動——癌癥防治行動實施方案(2023—2030 年). 中國腫瘤, 2023, 32(12): 887-890.
11.	湯靜燕. 兒童常見腫瘤診斷治療的進步. 中國小兒血液與腫瘤雜志, 2020, 25(6): 313-315.
12.	王躍, 王恒哲, 毛開云, 等. 全球免疫細胞治療藥物開發現狀與趨勢. 中國生物工程雜志, 2018, 38(10): 90-102.
13.	陳云. 兒童急性淋巴細胞白血病免疫治療進展. 中外醫學研究, 2022, 20(32): 180-184.
14.	Lin X, Wang J, Huang X, et al. Global, regional, and national burdens of leukemia from 1990 to 2017: a systematic analysis of the global burden of disease 2017 study. Aging (Albany NY), 2021, 13(7): 10468-10489.
15.	Malvezzi M, Carioli G, Bertuccio P, et al. European cancer mortality predictions for the year 2016 with focus on leukaemias, Ann Oncol, 2016, 27(4): 725-731.
16.	Singh GK, Siahpush M. Widening rural-urban disparities in all-cause mortality and mortality from major causes of death in the USA, 1969-2009. J Urban Health, 2014, 91(2): 272-292.
17.	Pei L, Choi JH, Liu J, et al. Genome-wide DNA methylation analysis reveals novel epigenetic changes in chronic lymphocytic leukemia. Epigenetics, 2012, 7(6): 567-578.
18.	陳繼超, 崔楚平, 王藝英, 等. 云浮市 1300 家企業職業病危害現狀與對策. 職業與健康, 2015, 31(13): 1859-1861,1864.
19.	Ni X, Li Z, Li X, et al. Socioeconomic inequalities in cancer incidence and access to health services among children and adolescents in China: a cross-sectional study. Lancet, 2022, 400(10357): 1020-1032.
20.	夏俊杰, 袁冬妹, 蔣偉超, 等. 甲醛接觸、全基因組 DNA 甲基化與兒童急性淋巴細胞白血病關系. 中國職業醫學, 2018, 45(3): 335-337,341.
21.	李會寧, 劉彥權, 付海英, 等. 室內裝修污染與白血病的相關性研究. 醫學信息, 2019, 32(22): 27-30.
22.	Oran B, Weisdorf DJ. Survival for older patients with acute myeloid leukemia: a population-based study. Haematologica, 2012, 97(12): 1916-1924.
23.	Koh Y, Kim I, Bae JY, et al. Prognosis of secondary acute myeloid leukemia is affected by the type of the preceding hematologic disorders and the presence of trisomy 8. Jpn J Clin Oncol, 2010, 40(11): 1037-1045.
24.	陳偉鋒, 宇傳華, 胡櫻. 1990—2017 年中國白血病疾病負擔分析. 中國慢性病預防與控制, 2021, 29(10): 797-800.
25.	楊麗, 彭瑞, 葉曉雯. 1990—2019 年中國白血病歸因于各類危險因素的疾病負擔分析與模型預測. 現代預防醫學, 2023, 50(2): 205-209, 256.
26.	Greaves MF. Aetiology of acute leukaemia. Lancet, 1997, 349(9048): 344-349.
27.	國家統計局, 國務院第七次全國人口普查領導小組辦公室. 第七次全國人口普查公報(第五號)——人口年齡構成情況. 中國統計, 2021(5): 10-11.
28.	Devine SM, Larson RA. Acute leukemia in adults: recent developments in diagnosis and treatment. CA Cancer J Clin, 1994, 44(6): 326-352.
29.	Daver N, Alotaibi AS, Bücklein V, et al. T-cell-based immunotherapy of acute myeloid leukemia: current concepts and future developments. Leukemia, 2021, 35(7): 1843-1863.
30.	Brunning RD. Classification of acute leukemias. Semin Diagn Pathol, 2003, 20(3): 142-153.

1. Whiteley AE, Price TT, Cantelli G, et al. Leukaemia: a model metastatic disease. Nat Rev Cancer, 2021, 21(7): 461-475.
2. GBD 2017 Disease and Injury Incidence and Prevalence Collaborators, Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet, 2018, 392(18): 1789-1858.
3. Siegel RL, Miller KD, Wagle NS, et al. Cancer statistics, 2023. CA Cancer J Clin, 2023, 73(1): 17-48.
4. 劉蓓. 急性髓系白血病的免疫治療現狀. 蘭州大學學報(醫學版), 2021, 47(6): 1-9.
5. Yang X, Wang J. Precision therapy for acute myeloid leukemia. J Hematol Oncol, 2018, 11(1): 3.
6. Wu X, Du J, Li L, et al. Bayesian age-period-cohort prediction of mortality of type 2 diabetic kidney disease in China: a modeling study. Front Endocrinol (Lausanne), 2021, 12: 767263.
7. Chen R, Sang L, Jiang M, et al. Longitudinal hematologic and immunologic variations associated with the progression of COVID-19 patients in China. J Allergy Clin Immunol, 2020, 146(1): 89-100.
8. Wang KW, Deng C, Li JP, et al. Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network. Epidemiol Infect, 2017, 145(6): 1118-1129.
9. Torre LA, Siegel RL, Ward EM, et al. Global cancer incidence and mortality rates and trends--an update. Cancer Epidemiol Biomarkers Prev, 2016, 25(1): 16-27.
10. 中華人民共和國國家衛生健康委員會醫療應急司. 健康中國行動——癌癥防治行動實施方案(2023—2030 年). 中國腫瘤, 2023, 32(12): 887-890.
11. 湯靜燕. 兒童常見腫瘤診斷治療的進步. 中國小兒血液與腫瘤雜志, 2020, 25(6): 313-315.
12. 王躍, 王恒哲, 毛開云, 等. 全球免疫細胞治療藥物開發現狀與趨勢. 中國生物工程雜志, 2018, 38(10): 90-102.
13. 陳云. 兒童急性淋巴細胞白血病免疫治療進展. 中外醫學研究, 2022, 20(32): 180-184.
14. Lin X, Wang J, Huang X, et al. Global, regional, and national burdens of leukemia from 1990 to 2017: a systematic analysis of the global burden of disease 2017 study. Aging (Albany NY), 2021, 13(7): 10468-10489.
15. Malvezzi M, Carioli G, Bertuccio P, et al. European cancer mortality predictions for the year 2016 with focus on leukaemias, Ann Oncol, 2016, 27(4): 725-731.
16. Singh GK, Siahpush M. Widening rural-urban disparities in all-cause mortality and mortality from major causes of death in the USA, 1969-2009. J Urban Health, 2014, 91(2): 272-292.
17. Pei L, Choi JH, Liu J, et al. Genome-wide DNA methylation analysis reveals novel epigenetic changes in chronic lymphocytic leukemia. Epigenetics, 2012, 7(6): 567-578.
18. 陳繼超, 崔楚平, 王藝英, 等. 云浮市 1300 家企業職業病危害現狀與對策. 職業與健康, 2015, 31(13): 1859-1861,1864.
19. Ni X, Li Z, Li X, et al. Socioeconomic inequalities in cancer incidence and access to health services among children and adolescents in China: a cross-sectional study. Lancet, 2022, 400(10357): 1020-1032.
20. 夏俊杰, 袁冬妹, 蔣偉超, 等. 甲醛接觸、全基因組 DNA 甲基化與兒童急性淋巴細胞白血病關系. 中國職業醫學, 2018, 45(3): 335-337,341.
21. 李會寧, 劉彥權, 付海英, 等. 室內裝修污染與白血病的相關性研究. 醫學信息, 2019, 32(22): 27-30.
22. Oran B, Weisdorf DJ. Survival for older patients with acute myeloid leukemia: a population-based study. Haematologica, 2012, 97(12): 1916-1924.
23. Koh Y, Kim I, Bae JY, et al. Prognosis of secondary acute myeloid leukemia is affected by the type of the preceding hematologic disorders and the presence of trisomy 8. Jpn J Clin Oncol, 2010, 40(11): 1037-1045.
24. 陳偉鋒, 宇傳華, 胡櫻. 1990—2017 年中國白血病疾病負擔分析. 中國慢性病預防與控制, 2021, 29(10): 797-800.
25. 楊麗, 彭瑞, 葉曉雯. 1990—2019 年中國白血病歸因于各類危險因素的疾病負擔分析與模型預測. 現代預防醫學, 2023, 50(2): 205-209, 256.
26. Greaves MF. Aetiology of acute leukaemia. Lancet, 1997, 349(9048): 344-349.
27. 國家統計局, 國務院第七次全國人口普查領導小組辦公室. 第七次全國人口普查公報(第五號)——人口年齡構成情況. 中國統計, 2021(5): 10-11.
28. Devine SM, Larson RA. Acute leukemia in adults: recent developments in diagnosis and treatment. CA Cancer J Clin, 1994, 44(6): 326-352.
29. Daver N, Alotaibi AS, Bücklein V, et al. T-cell-based immunotherapy of acute myeloid leukemia: current concepts and future developments. Leukemia, 2021, 35(7): 1843-1863.
30. Brunning RD. Classification of acute leukemias. Semin Diagn Pathol, 2003, 20(3): 142-153.

West China Medical Journal

Analysis and prediction of the incidence, morbidity and death of leukemia in China

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