Caniglia Ellen C, Sabin Caroline, Robins James M, Logan Roger, Cain Lauren E, Abgrall Sophie, Mugavero Michael J, Hernandez-Diaz Sonia, Meyer Laurence, Seng Remonie, Drozd Daniel R, Seage George R, Bonnet Fabrice, Dabis Francois, Moore Richard R, Reiss Peter, van Sighem Ard, Mathews William C, Del Amo Julia, Moreno Santiago, Deeks Steven G, Muga Roberto, Boswell Stephen L, Ferrer Elena, Eron Joseph J, Napravnik Sonia, Jose Sophie, Phillips Andrew, Olson Ashley, Justice Amy C, Tate Janet P, Bucher Heiner C, Egger Matthias, Touloumi Giota, Sterne Jonathan A, Costagliola Dominique, Saag Michael, Hernán Miguel A
1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; 2University College London, London, United Kingdom; 3Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA; 4Sorbonne Universités, UPMC Univ Paris 06, INSERM, Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136), Paris, France; 5Assistance Publique-Hopitaux de Paris (AP-HP), Hopital Antoine Béclère, Service de Médecine Interne, Clamart, France; 6University of Alabama at Birmingham, Birmingham, AL; 7Université Paris Sud, INSERM CESP U1018, and AP-HP, Hopital de Bicêtre, Service de Santé Publique, le Kremlin Bicêtre, France; 8Division of Allergy and Infectious Diseases, School of Medicine, University of Washington, Seattle, WA; 9Bordeaux University, ISPED, INSERM U897 CHU de Bordeaux, Bordeaux, France; 10INSERM U897, Centre Inserm Epidémiologie et Biostatistique, Université de Bordeaux, and Department of Internal Medicine, Bordeaux University Hospital, Bordeaux, France; 11School of Medicine, Johns Hopkins University, Baltimore, MD; 12Stichting HIV Monitoring, Amsterdam, Netherlands; Academic Medical Center, Department of Global Health and Division of Infectious Diseases, University of Amsterdam, and Amsterdam Institute for Global Health and Development, Amsterdam, Netherlands; 13Stichting HIV Monitoring, Amsterdam, Netherlands; 14Internal Medicine, Johns Hopkins University, Baltimore, MD; 15National Centre of Epidemiology, Instituto de Salud Carlos III, Madrid, Spain; Consorcio de Investigación Biomédica de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; 16Ramón y Cajal Hospital, IRYCIS, Madrid, Spain, University of Alcalá de Henares, Madrid, Spain; 17Positive Health Program, San Francisco General Hospital, San Francisco, CA; 18Servei de Medicina Interna, Hospital Universitari Germans Trias i Pujol, Universitat Autònoma de Barcelona, Badalona, Spain; 19Fenway Health, Boston, MA; 20Hospital Universitari d
J Acquir Immune Defic Syndr. 2016 Jun 1;72(2):214-21. doi: 10.1097/QAI.0000000000000956.
To illustrate an approach to compare CD4 cell count and HIV-RNA monitoring strategies in HIV-positive individuals on antiretroviral therapy (ART).
Prospective studies of HIV-positive individuals in Europe and the USA in the HIV-CAUSAL Collaboration and The Center for AIDS Research Network of Integrated Clinical Systems.
Antiretroviral-naive individuals who initiated ART and became virologically suppressed within 12 months were followed from the date of suppression. We compared 3 CD4 cell count and HIV-RNA monitoring strategies: once every (1) 3 ± 1 months, (2) 6 ± 1 months, and (3) 9-12 ± 1 months. We used inverse-probability weighted models to compare these strategies with respect to clinical, immunologic, and virologic outcomes.
In 39,029 eligible individuals, there were 265 deaths and 690 AIDS-defining illnesses or deaths. Compared with the 3-month strategy, the mortality hazard ratios (95% CIs) were 0.86 (0.42 to 1.78) for the 6 months and 0.82 (0.46 to 1.47) for the 9-12 month strategy. The respective 18-month risk ratios (95% CIs) of virologic failure (RNA >200) were 0.74 (0.46 to 1.19) and 2.35 (1.56 to 3.54) and 18-month mean CD4 differences (95% CIs) were -5.3 (-18.6 to 7.9) and -31.7 (-52.0 to -11.3). The estimates for the 2-year risk of AIDS-defining illness or death were similar across strategies.
Our findings suggest that monitoring frequency of virologically suppressed individuals can be decreased from every 3 months to every 6, 9, or 12 months with respect to clinical outcomes. Because effects of different monitoring strategies could take years to materialize, longer follow-up is needed to fully evaluate this question.
阐述一种在接受抗逆转录病毒治疗(ART)的HIV阳性个体中比较CD4细胞计数和HIV-RNA监测策略的方法。
欧洲和美国针对HIV阳性个体开展的HIV-CAUSAL协作研究以及综合临床系统艾滋病研究网络中心的前瞻性研究。
对开始接受ART且在12个月内实现病毒学抑制的初治个体,从抑制之日起进行随访。我们比较了3种CD4细胞计数和HIV-RNA监测策略:(1)每3±1个月一次,(2)每6±1个月一次,(3)每9 - 12±1个月一次。我们使用逆概率加权模型,就临床、免疫和病毒学结局比较这些策略。
在39029名符合条件的个体中,有265例死亡以及690例艾滋病定义疾病或死亡。与每3个月监测一次的策略相比,每6个月监测一次的策略的死亡风险比(95%置信区间)为0.86(0.42至1.78),每9 - 12个月监测一次的策略为0.82(0.46至1.47)。病毒学失败(RNA>200)的18个月风险比(95%置信区间)分别为0.74(0.46至1.19)、2.35(1.56至3.54),18个月平均CD4差异(95%置信区间)分别为 - 5.3( - 18.6至7.9)和 - 31.7( - 52.0至 - 11.3)。各策略在2年艾滋病定义疾病或死亡风险的估计值相似。
我们的研究结果表明,就临床结局而言,病毒学抑制个体的监测频率可从每3个月一次降至每6、9或12个月一次。由于不同监测策略的效果可能需要数年才能显现,因此需要更长时间的随访来全面评估这个问题。