2012—2020 年云南省肿瘤登记地区老年人 恶性肿瘤发病和死亡趋势分析.
Published In: Chinese Journal of Oncology, 2026, v. 48, n. 2. P. 203 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: 文洪梅; 陈杨; 李云飞; 李蔚; 石青萍; 唐娴; 邵英; 伍福仙; 李明松; 李吉; 杨建华 3 of 3
Abstract
Objective To analyze the incidence, mortality, and changing trends of malignant tumors among the elderly in tumor registration areas of Yunnan Province from 2012 to 2020. Methods Tumor registry data from qualified registration sites in Yunnan Province from 2012 to 2020 were obtained from the Yunnan Tumor Follow-up Registration System. The annual and overall (2012-2020) incidence and mortality rates of all and major malignant tumors were calculated. The age-standardized rates were calculated using the 2000 Chinese standard population and Segi's world standard population. Joinpoint 4.9 software was used to calculate the average annual percentage change (AAPC) in the incidence and mortality rates of all and major malignant tumors from 2012 to 2020. Results From 2012 to 2020, the incidence of malignant tumors among the elderly in tumor registry areas of Yunnan Province was 720.10/100 000, with a Chinese age-standardized rate of 708.83/100 000 and a world age-standardized rate of 691.71/100 000. Among them, the incidence rate was 901.52/100 000 for males and 550.45/100 000 for females. During the same period, the mortality rate of malignant tumors among the elderly in tumor registry areas of Yunnan Province was 538.76/100 000, with a Chinese age-standardized rate of 516.24/100 000 and a world age-standardized rate of 498.32/100 000. Among them, the mortality rate was 706.15/ 100 000 for males and 382.24/100 000 for females. Age-specific analysis of incidence and mortality showed that the 60~age group had the lowest incidence rate (556.23/100 000), while the 75~ age group had the highest incidence rate (927.82/100 000). The 60~ age group also had the lowest mortality rate (335.81/100 000), whereas the 80~ age group had the highest mortality rate (855.31/100 000). From 2012 to 2020, the top five malignant tumors in terms of incidence were lung cancer, colorectal cancer, liver cancer, prostate cancer, and stomach cancer, while the top five in terms of mortality were lung cancer, liver cancer, colorectal cancer, stomach cancer, and prostate cancer. From 2012 to 2020, the incidence rate of all malignant tumors among the elderly in Yunnan Province showed no significant upward or downward trend (AAPC= − 0.04%, 95% CI: − 1.23% to 1.17%). Among major malignant tumors, the incidence rates of liver cancer and esophageal cancer showed an increasing trend, with an AAPC of 2.07% and 7.57%, respectively; while the incidence rates of bladder cancer and pancreatic cancer showed a decreasing trend, with an AAPC of −3.36% and − 2.86%, respectively. The mortality rate of all malignant tumors also showed no significant upward or downward trend (AAPC=0.09%, 95% CI: − 1.17% to 1.37%). Among major malignant tumors, the mortality rates of liver cancer and esophageal cancer showed an increasing trend, with AAPCs of 2.73% and 8.92%, respectively, while the mortality rate of breast cancer showed a decreasing trend (AAPC=−7.34%). Conclusions From 2012 to 2020, the incidence and mortality of malignant tumors among the elderly in Yunnan Province remained relatively high, with no obvious downward trend. Lung cancer has long been the leading cause of both incidence and mortality in this population, while the trends of liver cancer and esophageal cancer remain concerning and warrant attention. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Chinese Journal of Oncology. 2026/02, Vol. 48, Issue 2, p203
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2026
- ISSN:0253-3766
- DOI:10.3760/cma.j.cn112152-20250702-00311
- Accession Number:192322413
- Copyright Statement:Copyright of Chinese Journal of Oncology is the property of Chinese Journal of Oncology / Zhonghua Zhongliu Zazhi and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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