Analysis of mortality factors and prediction of mortality trend of lung cancer in the elderly in Luzhou city from 2015 to 2020. [J]. Journal of Southwest Medical University 45(6):518-522(2022)
DOI:
Analysis of mortality factors and prediction of mortality trend of lung cancer in the elderly in Luzhou city from 2015 to 2020. [J]. Journal of Southwest Medical University 45(6):518-522(2022) DOI: 10.3969/j.issn.2096-3351.2022.06.011.
Analysis of mortality factors and prediction of mortality trend of lung cancer in the elderly in Luzhou city from 2015 to 2020
Objective To analyze and predict the trend of lung cancer mortality among the elderly in Luzhou city,and to provide scientific basis for the government to formulate and improve cancer prevention and control policies. Methods The method of time series analysis and prediction was adopted. Excel 2017 was used to calculate lung cancer mortality rate of the elderly in Luzhou city from 2015 to 2020,and Joinpoint4.8.0.1 was used to calculate the Annual Percent Change(APC) of the lung cancer mortality rate of the elderly,using SAS9.4 software to establish ARIMA model to forecast the mortality rate of lung cancer in the elderly from 2021 to 2023. Results From 2015 to 2020,the lung cancer mortality rate of the elderly male in Luzhou rose from 320.42 per 100 000 to 354.89 per 100 000(APC = 2.9%,P<0.05) ,and that of the elderly female rose from 118.64% per 100 000 to 127.15 per 100 000(APC = -0.7%,P>0.05),the overall mortality rate of lung cancer increased from 218.93/100 000 to 239.01/100 000 (APC = 2.4%,P < 0.05). The ARIMA model predicted that the overall mortality rate of the elderly would continue to increase from 2021 to 2023. Conclusion The mortality rate of lung cancer among the elderly would continue to increase from 2021 to 2023. There were many factors affecting the mortality of elderly patients with lung cancer,including population ageing,smoking,early diagnosis,early treatment and screening methods,pathological types of lung cancer,detection of driver genes,etc. Government should take measures against the above factors to change the situation.
关键词
老年人肺癌死亡率时间序列分析ARIMA模型
Keywords
ElderlyLung cancer mortalityTime series analysisARIMA model