文章摘要
斗智,陈军,江震,宋炜路,徐杰,吴尊友.中国MSM人群HIV感染者病毒载量抽样调查数据分布特征及数据转换研究[J].中华流行病学杂志,2017,38(11):1494-1498
中国MSM人群HIV感染者病毒载量抽样调查数据分布特征及数据转换研究
Data distribution and transformation in population based sampling survey of viral load in HIV positive men who have sex with men in China
收稿日期:2017-01-20  出版日期:2017-11-11
DOI:10.3760/cma.j.issn.0254-6450.2017.11.011
中文关键词: 艾滋病病毒  病毒载量  分布特征
英文关键词: Human immunodeficiency virus  Viral load  Distribution characteristics
基金项目:国家科技重大专项(2012ZX10001007005
作者单位E-mail
斗智 102206 北京, 中国疾病预防控制中心性病艾滋病预防控制中心预防干预室  
陈军 102206 北京, 中国疾病预防控制中心性病艾滋病预防控制中心预防干预室  
江震 102206 北京, 中国疾病预防控制中心性病艾滋病预防控制中心预防干预室 jiangzhen812@126.com 
宋炜路 102206 北京, 中国疾病预防控制中心性病艾滋病预防控制中心预防干预室  
徐杰 102206 北京, 中国疾病预防控制中心性病艾滋病预防控制中心预防干预室  
吴尊友 102206 北京, 中国疾病预防控制中心性病艾滋病预防控制中心  
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中文摘要:
      目的 了解MSM人群的HIV感染者(MSM感染者)人群病毒载量(PVL)数据分布特征,拟合分布函数,探讨评价PVL的合适参数。方法 病毒载量(VL)检测限设定为≤ 50拷贝/ml。描述PVL的一般分布特征,结合Box-Cox转换和正态性检验,根据PVL数据转换后的分布特征,拟合稳定分布函数,并进行拟合优度检验。结果 PVL原始数据为偏态分布,变异系数(CV)为622.24%,经Box-Cox转换,转换参数(λ)最优值=-0.11,为多峰分布;VL原始值>检测限的PVL经Box-Cox数据转换,λ最优值=0,为对数转换,偏态厚尾特征,不满足正态分布,拟合稳定分布函数(α=1.70,β=-1.00,γ=0.78,δ=4.03),呈稳定分布。结论 PVL原始值存在截尾、非正态分布的特征,变异度较大;当VL原始值≤检测限的截尾数据占总体比例较大时,不宜用检测限的1/2代替;VL原始值>检测限的PVL对数值为稳定分布,适合用MIQR来描述集中趋势和离散趋势。
英文摘要:
      Objective To understand the distribution of population viral load (PVL) data in HIV infected men who have sex with men (MSM), fit distribution function and explore the appropriate estimating parameter of PVL. Methods The detection limit of viral load (VL) was ≤ 50 copies/ml. Box-Cox transformation and normal distribution tests were used to describe the general distribution characteristics of the original and transformed data of PVL, then the stable distribution function was fitted with test of goodness of fit. Results The original PVL data fitted a skewed distribution with the variation coefficient of 622.24%, and had a multimodal distribution after Box-Cox transformation with optimal parameter (λ) of -0.11. The distribution of PVL data over the detection limit was skewed and heavy tailed when transformed by Box-Cox with optimal λ=0. By fitting the distribution function of the transformed data over the detection limit, it matched the stable distribution (SD) function (α=1.70, β=-1.00, γ=0.78, δ=4.03). Conclusions The original PVL data had some censored data below the detection limit, and the data over the detection limit had abnormal distribution with large degree of variation. When proportion of the censored data was large, it was inappropriate to use half-value of detection limit to replace the censored ones. The log-transformed data over the detection limit fitted the SD. The median (M) and inter-quartile ranger (IQR) of log-transformed data can be used to describe the centralized tendency and dispersion tendency of the data over the detection limit.
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