Welcome to visit Zhongnan Medical Journal Press Series journal website!

Prediction of incidence and mortality rates of nasopharyngeal carcinoma in China from 2022 to 2026: based on GM(1,1) and ARIMA models

Published on Sep. 26, 2025Total Views: 54 timesTotal Downloads: 30 timesDownloadMobile

Author: LIN Xiaolong 1 ZHANG Jie 2 LIN Wei 3

Affiliation: 1. Department of Otorhinolaryngology Head and Neck Surgery, The Third People's Hospital of Chengdu, Chengdu 610014, China 2. Department of Otorhinolaryngology Head and Neck Surgery, Western Theater Air Force Hospital of PLA, Chengdu 610065, China 3. Department of Disease Control and Prevention, Western Theater Air Force Hospital of PLA, Chengdu 610065, China

Keywords: Nasopharyngeal cancer GM(1 1) model ARIMA model Incidence rate Mortality rate

DOI: 10.12173/j.issn.1004-5511.202412173

Reference: Lin XL, Zhang J, Lin W. Prediction of incidence and mortality rates of nasopharyngeal carcinoma in China from 2022 to 2026: based on GM(1,1) and ARIMA models[J]. Yixue Xinzhi Zazhi, 2025, 35(9): 1017-1023. DOI: 10.12173/j.issn.1004-5511.202412173. [Article in Chinese]

  • Abstract
  • Full-text
  • References
Abstract

Objective  To construct prediction model of nasopharyngeal carcinoma (NPC) to provide a reference for the prevention and control of NPC in China.

Methods  Data on the age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) of NPC among Chinese residents from 2012 to 2021, were extracted from the Global Burden of Diseases Study (GBD) 2021 database. The grey prediction model GM(1,1) and the autoregressive integrated moving average model (ARIMA) were constructed, and the fitting performance of the two models was compared. Predictions for the ASIR and ASMR of NPC in China from 2022 to 2026 were made.

Results  The GM(1,1) model exhibited lower mean absolute error and mean relative error compared to the ARIMA model, indicating better fitting performance. According to the GM(1,1) model predictions, by 2026, the total ASIR, male ASIR, and female ASIR of NPC in China are expected to rise to 3.83/100,000, 5.85/100,000, and 1.82/100,000, respectively, while the total ASMR, male ASMR, and female ASMR are projected to decline to 1.44/100,000, 2.23/100,000, and 0.71/100,000, respectively.

Conclusion  The GM(1,1) model outperforms the ARIMA model in predicting the incidence and mortality rates of NPC in China. The predictions suggest that over the next five years, the incidence of NPC in China will increase annually, while the mortality rate will decrease year by year.

Full-text
Please download the PDF version to read the full text: download
References

1.Campion NJ, Ally M, Jank BJ, et al. The molecular march of primary and recurrent nasopharyngeal carcinoma[J]. Oncogene, 2021, 40(10): 1757-1774. DOI: 10.1038/s41388-020-01631-2.

2.Fierti AO, Yakass MB, Okertchiri EA, et al. The role of epstein-barr virus in modulating key tumor suppressor genes in associated malignancies: epigenetics, transcriptional, and post-translational modifications[J]. Biomolecules, 2022, 12(1): 127. DOI: 10.3390/biom12010127.

3.Yang SP, Rao MY, Chen QS, et al. Causes of death in long-term nasopharyngeal carcinoma survivors[J]. Front Public Health, 2022, 10: 912843. DOI: 10.3389/fpubh.2022.912843.

4.Tang LL, Chen YP, Chen CB, et al. The Chinese Society of Clinical Oncology (CSCO) clinical guidelines for the diagnosis and treatment of nasopharyngeal carcinoma[J]. Cancer Commun (Lond), 2021, 41(11): 1195-1227. DOI: 10.1002/cac2.12218.

5.朱文鹏, 韩梦琦, 王雨欣, 等. 1990—2019年中国鼻咽癌发病与死亡的趋势及预测研究[J]. 中国全科医学, 2023, 26(34): 4269-4276. [Zhu WP, Han MQ, Wang YX, et al. Trends and prediction of nasopharyngeal carcinoma incidence and mortality in China from 1990 to 2019[J]. Chinese General Practice, 2023, 26(34): 4269-4276.] DOI: 10.12114/j.issn.1007-9572.2023.0247.

6.Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. DOI: 10.3322/caac.21660.

7.Chen X, Giles J, Yao Y, et al. The path to healthy ageing in China: a peking university-lancet commission[J]. Lancet, 2022, 400(10367): 1967-2006. DOI: 10.1016/S0140-6736(22)01546-X.

8.梁冠盈, 苗大壮, 范宁宁, 等. 1990-2019年中国鼻咽癌发病和死亡年龄-时期-队列分析及预测[J]. 中华肿瘤防治杂志, 2024, 31(7): 391-398. [Liang GY, Miao DZ, Fan NN, et  al. Age-period-cohort analysis and prediction of nasopharyngeal carcinoma incidence and mortality in China from 1990 to 2019[J]. Chinese Journal of Cancer Prevention and Treatment, 2024, 31(7): 391-398.] DOI: 10.16073/j.cnki.cjcpt.2024.07.01.

9.谢梦娇. 中国鼻咽癌发病和死亡的趋势分析及预测研究 [D]. 辽宁: 中国医科大学, 2023. [Xie MJ. Trend analysis and prediction of nasopharyngeal carcinoma incidence and mortality in China[D]. Liaoning: China Medical University, 2023.] DOI: 10.27652/d.cnki.gzyku.2023.000883.

10.邓芷晴, 周利华, 叶久红, 等. ARIMA模型在肺癌发病率预测中的应用[J]. 医学新知杂志, 2019, 29(4): 414-417. [Deng ZQ, Zhou LH, Ye JH, et al. Application of ARIMA model in forecast of the incidence of lung cancer[J]. Journal of New Medicine, 2019, 29(4): 414-417.] DOI: 10.3969/j.issn.1004-5511.2019.04.020.

11.文静, 殷成宇, 廖国伟, 等. 应用GM(1,1)灰色模型预测全国甲状腺癌发病趋势[J]. 现代肿瘤医学, 2022, 30(5): 899-902. [Wen J, Yin CY, Liao GW, et al. Application of GM(1,1) grey model in predicting the incidence trend of thyroid cancer in China[J]. Journal of Modern Oncology, 2022, 30(5): 899-902.] DOI: 10.3969/j.issn.1672-4992.2022.05.030.

12.Wang X, Cheng F, Fu Q, et al. Time trends in maternal hypertensive disorder incidence in Brazil, Russian Federation, India, China, and South Africa (BRICS): an age-period-cohort analysis for the GBD 2021[J]. BMC Pregnancy Childbirth, 2024, 24(1): 731. DOI: 10.1186/s12884-024-06931-z.

13.Tu C, Pan Q, Jiang C, et al. Trends and predictions in the physical shape of Chinese preschool children from 2000 to 2020[J]. Front Public Health, 2023, 11: 1148415. DOI: 10.3389/fpubh.2023.1148415.

14.鲍晓露, 向国春, 史卢少博, 等. 基于灰色GM(1,1)-SVM组合模型的广东省卫生总费用预测研究[J]. 现代预防医学, 2022, 49(5): 856-859. [Bao XL, Xiang GC, Shi LSB, et  al. Prediction of total health expenditure in Guangdong based on GM(1,1)-SVM combination model[J]. Modern Preventive Medicine, 2022, 49(5): 856-859.] https://d.wanfangdata.com.cn/periodical/xdyfyx202205018

15.Yan J, Li Y, Zhou P. Impact of COVID-19 pandemic on the epidemiology of STDs in China: based on the GM (1,1) model[J]. BMC Infect Dis, 2022, 22(1): 519. DOI: 10.1186/s12879-022-07496-y.

16.Gao J, Li J, Wang M. Time series analysis of cumulative incidences of typhoid and paratyphoid fevers in China using both Grey and SARIMA models[J]. PLoS One, 2020, 15(10): e241217. DOI: 10.1371/journal.pone.0241217.

17.程龙慧, 任琼琼, 肖培, 等. 我国常见细菌耐药趋势预测研究: 基于灰色GM(1,1)模型[J]. 中国感染控制杂志, 2022, 21(12): 1164-1170. [Cheng LH, Ren QQ, Xiao P, et al. Prediction of drug resistance trends of common bacteria in China based on grey prediction model GM(l,1)[J]. Chinese Journal of Infection Control, 2022, 21(12): 1164-1170.] DOI: 10.12138/j.issn.1671-9638.20223282.

18.张彬, 张龙秀, 王瑞, 等. 基于GM(1,1)和ARIMA模型的安徽省孕产妇及儿童死亡率的预测研究[J]. 中国妇幼卫生杂志, 2023, 14(1): 1-6. [Zhang B, Zhang LX, Wang R, et al. Prediction of maternal and child mortality in Anhui Province based on GM(1,1) and ARIMA combination model [J]. Chinese Journal of Women and Children Health, 2023, 14(1): 1-6.] DOI: 10.19757/j.cnki.issn1674-7763.2023.01.001.

19.俞玉琪, 李德富, 刘勇, 等. 江西省儿童流感样病例就诊率ARIMA模型的建立及应用[J]. 南昌大学学报(医学版), 2023, 63(1): 73-76. [Yu YQ, Li DF, Liu Y, et al. Establishment and application of ARIMA model for influenza-like illness consultation rate among children in Jiangxi Province[J]. Journal of Nanchang University (Medical Sciences), 2023, 63(1): 73-76.] DOI: 10.13764/j.cnki.ncdm.2023.01.014.

20.尤金辉, 范国锋. ARIMA模型与GM(1,1)模型对兴化市结核病发病数预测效果比较[J]. 江苏预防医学, 2022, 33(5): 551-553. [You JH, Fan GF. Comparative study of ARIMA and GM(1,1) models in predicting the incidence of tuberculosis in Xinghua City[J]. Jiangsu Journal of Preventive Medicine, 2022, 33(5): 551-553.] DOI: 10.13668/j.issn.1006-9070.2022.05.016.

21.Hassan NMA, 韦彗琳, 胡艳玲. 1990—2019年中国鼻咽癌疾病负担变化趋势分析及预测[J]. 蛇志, 2023, 35(2): 191-197. [Hassan NMA, Wei HL, Hu YL. Trend analysis and prediction of nasopharyngeal carcinoma disease burden in China from 1990 to 2019[J]. Journal of Snake, 2023, 35(2): 191-197.] DOI: 10.3969/j.issn.1001-5639.2023.02.012.

22.Zhang R, He Y, Wei B, et al. Nasopharyngeal carcinoma burden and its attributable risk factors in China: estimates and forecasts from 1990 to 2050[J]. Int J Environ Res Public Health, 2023, 20(4): 2926. DOI: 10.3390/ijerph20042926.

23.Yu MC, Nichols PW, Zou XN, et al. Induction of malignant nasal cavity tumours in Wistar rats fed Chinese salted fish[J]. Br J Cancer, 1989, 60(2): 198-201. DOI: 10.1038/bjc.1989.250.

24.Da CV, Marques-Silva AC, Moreli ML. The Epstein-Barr virus latent membrane protein-1 (LMP1) 30-bp deletion and XhoI-polymorphism in nasopharyngeal carcinoma: a Meta-analysis of observational studies[J]. Syst Rev, 2015, 4: 46. DOI: 10.1186/s13643-015-0037-z.

25.Jin N, Li J, Jin M, et al. Spatiotemporal variation and determinants of population's PM(2.5) exposure risk in China, 1998-2017: a case study of the Beijing-Tianjin-Hebei region[J]. Environ Sci Pollut Res Int, 2020, 27(25): 31767-31777. DOI: 10.1007/s11356-020-09484-8.

26.Chen Y, Chang ET, Liu Q, et al. Occupational exposures and risk of nasopharyngeal carcinoma in a high-risk area: a population-based case-control study[J]. Cancer, 2021, 127(15): 2724-2735. DOI: 10.1002/cncr.33536.

27.Lin JH, Jiang CQ, Ho SY, et al. Smoking and nasopharyngeal carcinoma mortality: a cohort study of 101,823 adults in Guangzhou, China[J]. BMC Cancer, 2015, 15: 906. DOI: 10.1186/s12885-015-1902-9.

28.Zhang Y, Cao Y, Luo L, et al. The global, regional, and national burden of nasopharyngeal carcinoma and its attributable risk factors in 204 countries and territories, 1990-2019[J]. Acta Otolaryngol, 2022, 142(7-8): 590-609. DOI: 10.1080/00016489.2022.2111711.

29.王明君. 灰色系统理论GM(1,1)模型在青海省碘盐监测中的应用初探[J]. 医学信息, 2023, 36(2): 24-27. [Wang  MJ. Preliminary application of grey system theory GM(1,1) model in iodine salt monitoring in Qinghai Province[J]. Journal of Medical Information, 2023, 36(2): 24-27.] DOI: 10.3969/j.issn.1006-1959.2023.02.004.

30.Wang YW, Shen ZZ, Jiang Y. Comparison of ARIMA and GM(1,1) models for prediction of hepatitis B in China[J]. PLoS One, 2018, 9(13): e201987. DOI: 10.1371/journal.pone.0201987.

31.侯晓澈. 利用灰色GM(1,1)模型预测某三甲医院消化内科住院患者医院感染发生率[J]. 中国消毒学杂志, 2020, 37(3): 207-209. [Hou XC. Prediction of hospital infection incidence rate among gastroenterology inpatients in a tertiary hospital using GM(1,1) grey model[J]. Chinese Journal of Disinfection, 2020, 37(3): 207-209.] DOI: 10.11726/j.issn.1001- 7658.2020.03.017.

32.石雷. 辽阳市肺结核病流行趋势的灰色模型分析[J]. 中国热带医学, 2010, 10(4): 429-430. [Shi L. Grey model analysis of tuberculosis epidemic trend in Liaoyang City[J]. Chinese Journal of Tropical Medicine, 2010, 10(4): 429-430.] https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISD3pncmR5eDIwMTAwNDAxOBoIaXRtdnBvaGI%3D

33.宋媛媛, 王雷, 熊甜, 等. ARIMA模型与GM(1,1)模型在痢疾发病数预测中的比较研究[J]. 实用预防医学, 2019, 26(7): 888-892. [Song YY, Wang L, Xiong T, et al. Comparative study of ARIMA and GM(1,1) models in predicting the incidence of dysentery[J]. Practical Preventive Medicine, 2019, 26(7): 888-892.] DOI: 10.3969/j.issn.1006-3110.2019.07.034.