Snoeck Joke, Van Laethem Kristel, Hermans Philippe, Van Wijngaerden Eric, Derdelinckx Inge, Schrooten Yoeri, van de Vijver David A M C, De Wit Stéphanie, Clumeck Nathan, Vandamme Anne-Mieke
Rega Institute for Medical Research, Katholieke Universiteit Leuven, Belgium.
J Acquir Immune Defic Syndr. 2004 Mar 1;35(3):279-85. doi: 10.1097/00126334-200403010-00009.
This study documented the HIV-1 subtype distribution in 2 Belgian hospitals and determined predictive demographics for non-B subtypes. Overall, subtype B was the most prevalent subtype in this population, followed by subtypes A and C. Several recombinants were detected, circulating recombinants as well as new ones. We found a rise in non-B subtypes from 0% in 1983 to 57% in 2001. The Cochran-Armitage trend test (P < 0.001) as well as the correlation analysis (R = 0.71, P = 0.0006) was highly significant. Recombinants were also increasing in this patient population from 0% in 1983 to 10% in 2001, with good support from the statistical analyses (trend test P < 0.001; correlation analysis R = 0.67, P = 0.0016). Heterosexual route of infection, black African race, African origin of the virus, and year of diagnosis were predictors for infection with non-B subtypes in multivariate analysis. This analysis indicates that the prevalence of non-B subtypes and recombinants in this patient population is high and increasing. Gathering demographic and sequence information from newly diagnosed patients could be useful to further follow the spread of non-B subtypes in Belgium and Europe, but subtyping based on sequence information still remains the most reliable method.
本研究记录了比利时两家医院中HIV-1亚型的分布情况,并确定了非B亚型的预测性人口统计学特征。总体而言,B亚型是该人群中最常见的亚型,其次是A亚型和C亚型。检测到了几种重组体,包括流行的重组体和新出现的重组体。我们发现非B亚型的比例从1983年的0%上升到了2001年的57%。 Cochr an-Armitage趋势检验(P < 0.001)以及相关性分析(R = 0.71,P = 0.0006)具有高度显著性。在该患者群体中,重组体也在增加,从1983年的0%增加到2001年的10%,统计分析提供了有力支持(趋势检验P < 0.001;相关性分析R = 0.67,P = 0.0016)。在多变量分析中,异性传播途径、非洲黑人种族、病毒的非洲起源以及诊断年份是感染非B亚型的预测因素。该分析表明,该患者群体中非B亚型和重组体的流行率很高且在上升。收集新诊断患者的人口统计学和序列信息可能有助于进一步追踪非B亚型在比利时和欧洲的传播情况,但基于序列信息进行亚型分类仍然是最可靠的方法。