文章摘要
张娜,朱晓艳,王国永,陶小润,汪宁,康殿民.山东省抗病毒治疗HIV/AIDS生存状况及影响因素分析[J].中华流行病学杂志,2019,40(1):74-78
山东省抗病毒治疗HIV/AIDS生存状况及影响因素分析
Survival status and influencing factors of HIV/AIDS on highly active anti-retrovial therapy in Shandong province
收稿日期:2018-06-19  出版日期:2019-01-14
DOI:10.3760/cma.j.issn.0254-6450.2019.01.015
中文关键词: 艾滋病  高效抗反转录病毒治疗  竞争风险模型  影响因素
英文关键词: AIDS  Highly active anti-retroviral therapy  Competing risk model  Influencing factor
基金项目:山东省自然科学基金青年基金(ZR2014HQ038)
作者单位E-mail
张娜 山东省疾病预防控制中心艾滋病防制所, 济南 250014  
朱晓艳 山东省疾病预防控制中心艾滋病防制所, 济南 250014  
王国永 山东省疾病预防控制中心艾滋病防制所, 济南 250014  
陶小润 山东省疾病预防控制中心艾滋病防制所, 济南 250014  
汪宁 中国疾病预防控制中心性病艾滋病预防控制中心, 北京 102206 wangnbj@163.com 
康殿民 山东省疾病预防控制中心艾滋病防制所, 济南 250014 dmkang66@163.com 
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中文摘要:
      目的 了解山东省抗病毒治疗HIV/AIDS的生存状况及影响因素。方法 运用Kaplan-Meier(K-M)法及累积发生函数(CIF)估算2003-2015年山东省抗病毒治疗HIV/AIDS的艾滋病相关死亡发生率、部分分布比例风险回归模型(F-G模型)分析生存状况及影响因素。结果 竞争风险存在时,K-M法计算艾滋病相关死亡累积发生率高于CIF。CIF估算5 593例治疗HIV/AIDS随访1、3、5、10年艾滋病相关死亡累积发生率分别为3.08%、4.21%、5.37%和7.59%。大专及以上文化程度(HR=0.40,95% CI:0.24~0.65)HIV/AIDS的艾滋病相关死亡发生危险较低,现住址在鲁西地区(HR=1.33,95% CI:1.01~1.89)、医疗机构检测发现(HR=1.39,95% CI:1.06~1.80)、治疗基线方案含NVP(HR=1.36,95% CI:1.03~1.88)、治疗基线临床症状Ⅲ/Ⅳ期(HR=2.61,95% CI:1.94~3.53)、诊断1年后接受随访(HR=2.02,95% CI:1.30~3.15)、诊断基线CD4+T淋巴细胞计数(CD4)≤ 200个/μl(HR=3.41,95% CI:2.59~4.59)、治疗基线CD4 ≤ 350个/μl(HR=5.48,95% CI:2.32~12.72)的HIV/AIDS发生艾滋病相关死亡风险高。结论 竞争风险存在时,K-M法高估艾滋病相关死亡累积发生率,优选竞争风险模型进行生存分析;早诊断、及时随访、早治疗可降低HIV/AIDS艾滋病相关死亡。
英文摘要:
      Objective To understand the survival status and influencing factors for HIV/AIDS patients on highly active anti-retroviral therapy (HAART) in Shandong province. Methods Both Kaplan-Meier (K-M) method and cumulative incidence function (CIF) were used to calculate the cumulative incidence of AIDS-related death respectively, and Fine-Gray model was used to identify the influencing factors related to survival time. Results Through K-M method, a higher AIDS-related cumulated death rate than the CIF, was estimated. Among all the HIV/AIDS patients who initiated HAART from 2003 to 2015 in Shandong, 5 593 of them met the inclusion criteria. The cumulative incidence rate for AIDS-related death was 3.08% in 1 year, 4.21% in 3 years, 5.37% in 5 years, and 7.59% in 10 years respectively by CIF. Results from the F-G analysis showed that HIV/AIDS patients who were on HAART, the ones who had college degree or above (HR=0.40, 95% CI:0.24-0.65) were less likely to die of AIDS-associated diseases. However, HIV/AIDS patients who were on HAART and living in the western areas of Shandong (HR=1.33, 95% CI:1.01-1.89), diagnosed by medical institutions (HR=1.39, 95% CI:1.06-1.80), started to receive care ≥ 1 year after diagnosis (HR=2.02, 95% CI:1.30-3.15), their CD4 cell count less than 200 cells/μl (HR=3.41, 95% CI:2.59-4.59) at the time of diagnosis, with NVP in antiviral treatment (ART) regime (HR=1.36, 95% CI:1.03-1.88), at Ⅲ/Ⅳ clinical stages (HR=2.61, 95% CI:1.94-3.53) and CD4 cell count less than 350 cells/μl (HR=5.48, 95% CI:2.32-12.72) at initiation of HAART ect., were more likely to die of AIDS-associated diseases. Conclusions With the existence of competing risks, the cumulative incidence rate for AIDS-related death was overestimated by K-M, suggesting that competing risk models should be used in the survival analysis. Measures as early diagnoses followed by timely care and early HAART could end up with the reduction of AIDS-related death.
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