| 付丽茹,肖民扬,贾曼红,宋丽军,李雪华,牛瑾,王晓雯,张祖样,马艳玲,罗红兵.云南省1989-2021年报告HIV/AIDS生存时间及影响因素分析[J].中华流行病学杂志,2023,44(6):960-965 |
| 云南省1989-2021年报告HIV/AIDS生存时间及影响因素分析 |
| Analysis on survival time and influencing factors among reported HIV/AIDS in Yunnan Province, 1989-2021 |
| 收稿日期:2022-10-19 出版日期:2023-06-16 |
| DOI：10.3760/cma.j.cn112338-20221019-00890 |
| 中文关键词: 艾滋病病毒/艾滋病 回顾性队列研究 生存分析 影响因素 |
| 英文关键词: HIV/AIDS Retrospective cohort study Survival analysis Influence factor |
| 基金项目:国家科技重大专项（2018ZX10715006） |
| 作者 | 单位 | E-mail | | 付丽茹 | 云南省疾病预防控制中心, 昆明 650022 | | | 肖民扬 | 云南省疾病预防控制中心, 昆明 650022 | | | 贾曼红 | 云南省疾病预防控制中心, 昆明 650022 | | | 宋丽军 | 云南省疾病预防控制中心, 昆明 650022 | | | 李雪华 | 云南省疾病预防控制中心, 昆明 650022 | | | 牛瑾 | 云南省疾病预防控制中心, 昆明 650022 | | | 王晓雯 | 云南省疾病预防控制中心, 昆明 650022 | | | 张祖样 | 云南省疾病预防控制中心, 昆明 650022 | | | 马艳玲 | 云南省疾病预防控制中心, 昆明 650022 | | | 罗红兵 | 云南省疾病预防控制中心, 昆明 650022 | 540122323@qq.com |
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| 中文摘要: |
| 目的 分析1989-2021年云南省报告HIV/AIDS生存时间及影响因素。方法 资料来源于我国艾滋病综合防治信息系统，采用回顾性队列研究方法，使用寿命表描述报告HIV/AIDS生存时间，Kaplan-Meier法拟合不同状态下的生存曲线，Cox比例风险回归模型分析生存时间的影响因素。结果 云南省累计报告174 510例HIV/AIDS全死因死亡密度为4.23/100人年，中位生存时间为20.00（95%CI：19.52~20.48）年，1、10、20和30年的累积生存概率分别为90.75%、67.50%、47.93%和30.85%。Cox比例风险回归模型分析结果显示，0~岁和15~岁的死亡风险是≥50岁的0.44（95%CI：0.34~0.56）倍和0.51（95%CI：0.50~0.52）倍；首次CD4+T淋巴细胞（CD4）计数为200~、350~和≥501个/μl的死亡风险分别是CD4计数为0~199个/μl的0.52（95%CI：0.50~0.53）倍、0.41（95%CI：0.40~0.42）倍和0.35（95%CI：0.34~0.36）倍；未抗病毒治疗者死亡风险是接受治疗者的11.56（95%CI：11.26~11.87）倍；抗病毒治疗中依从性较差而出现失访、停药、失访和停药均存在的病例死亡风险分别是一直治疗病例的1.66（95%CI：1.61~1.72）倍、2.49（95%CI：2.39~2.60）倍和1.65（95%CI：1.53~1.78）倍。结论 1989- 2021年云南省HIV/AIDS确证时的年龄、首次CD4计数水平、是否抗病毒治疗和依从性是HIV/AIDS生存时间的主要影响因素，早发现、早治疗和提高治疗依从性，可以延长HIV/AIDS生存时间。 |
| 英文摘要: |
| Objective To analyze the survival time of reported HIV/AIDS and influencing factors of Yunnan Province from 1989 to 2021. Methods The data were extracted from the Chinese HIV/AIDS comprehensive response information management system. The retrospective cohort study was conducted. The life table method was applied to calculate the survival probability. Kaplan-Meier was used to draw survival curves in different situations. Furthermore, the Cox proportion hazard regression model was constructed to identify the factors related to survival time. Results Of the 174 510 HIV/AIDS, the all-cause mortality density was 4.23 per 100 person-years, the median survival time was 20.00 (95%CI:19.52-20.48) years, and the cumulative survival rates in 1, 10, 20, and 30 years were 90.75%, 67.50%, 47.93% and 30.85%. Multivariate Cox proportional risk regression model results showed that the risk of death among 0-14 and 15-49 years old groups were 0.44 (95%CI: 0.34-0.56) times and 0.51 (95%CI:0.50-0.52) times of ≥50 years old groups. The risk for death among the first CD4+T lymphocytes counts (CD4) counts levels of 200-349 cells/μl, 350-500 cells/μl and ≥501 cells/μl groups were 0.52 (95%CI: 0.50-0.53) times, 0.41 (95%CI: 0.40-0.42) times and 0.35 (95%CI: 0.34-0.36) times of 0-199 cells/μl groups. The risk of death among the cases that have not received antiretroviral therapy (ART) was 11.56 (95%CI: 11.26-11.87) times. The risk for death among the cases losing to ART, stopping to ART, both losing and stopping ART was 1.66 (95%CI:1.61-1.72) times, 2.49 (95%CI:2.39-2.60) times, and 1.65 (95%CI:1.53-1.78) times of the cases on ART. Conclusions The influencing factors for the survival time of HIV/AIDS cases were age at diagnosis in Yunnan province from 1989 to 2021. The first CD4 counts levels, antiretroviral therapy, and ART compliance. Early diagnosis, early antiretroviral therapy, and increasing ART compliance could extend the survival time of HIV/AIDS cases. |
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