Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes.
Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes.
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DOI：
10.1016/s0140-6736(10)60666-6
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发表时间：
2010-08-07
期刊：
影响因子：
168.9
通讯作者：
Egger, Matthias
中科院分区：
文献类型：
--
作者：
May, Margaret;Boulle, Andrew;Phiri, Sam;Messou, Eugene;Myer, Landon;Wood, Robin;Keiser, Olivia;Sterne, Jonathan A. C.;Dabis, Francois;Egger, Matthias
已经为高收入国家开始联合抗逆转录病毒疗法（ART）的HIV-1感染患者开发了预后模型，但尚未为撒哈拉以南非洲的患者开发。我们纳入了科特迪瓦、南非和马拉维的10 331名成人患者，他们在2004年至2007年期间开始接受抗逆转录病毒治疗，参加了抗逆转录病毒治疗扩大方案。按意向继续治疗分析数据，忽略治疗变化和中断。我们使用威布尔生存模型构建了两个预后模型：一个包括基线CD 4计数，另一个没有，因为在许多非洲环境中CD 4计数没有常规测量。在开始抗逆转录病毒治疗后的第一年，912例（8.2%）患者死亡。基线CD 4细胞计数（校正风险比0.21 [95% CI 0.17-0.27]，比较≥200与<25个细胞/μL），WHO临床分期（3.45 [2.43-4.90]比较III/IV期和I/II期），体重（0.23 [0.18-0.30]，比较≥60与<45 kg）和贫血（0.27 [0.20-0.36]，比较无与严重）与死亡率强相关。其他独立的危险因素是总淋巴细胞计数低，高龄和男性。CD 4模型包括CD 4计数、临床分期、体重、年龄和性别（160个危险分层）。在替代模型中，用总淋巴细胞计数和贫血程度（288个风险分层）代替CD 4计数。使用CD 4模型，死亡概率范围为最低风险分层患者的0.9%（95% CI 0.6-1.4）至最高风险分层患者的53%（44-62）。总淋巴细胞/血红蛋白模型的相应概率为0.9%（0.5-1.4）和60%（48-71）。基于CD 4细胞计数或总淋巴细胞和血红蛋白的预后模型在预测撒哈拉以南非洲开始抗逆转录病毒治疗的患者的早期死亡率方面提供了类似的强有力的区分。这些模式有助于在人口一级为病人提供咨询、规划保健服务和预测结果。
Prognostic models have been developed for HIV-1 infected patients who start combination antiretroviral therapy (ART) in high-income countries, but not for patients treated in sub-Saharan Africa. We included 10,331 adult patients who started ART between 2004 and 2007 in ART scale-up programmes in Côte d’Ivoire, South Africa and Malawi. Data were analysed by intention-to-continue-treatment, ignoring treatment changes and interruptions. We used Weibull survival models to construct two prognostic models: one that included baseline CD4 count and one that did not, since in many African settings CD4 count is not routinely measured. During the first year after starting ART, 912 (8.2%) patients died. Baseline CD4 cell count (adjusted hazard ratio 0.21 [95% CI 0.17–0.27] comparing ≥200 with <25 cells/μL), WHO clinical stage (3.45 [2.43–4.90] comparing stages III/IV with I/II), body weight (0.23 [0.18–0.30] comparing ≥60 with <45kg) and anaemia (0.27 [0.20–0.36] comparing none with severe) were strongly associated with mortality. Other independent risk factors were low total lymphocyte count, advanced age and male sex. The CD4 model included CD4 count, clinical stage, body weight, age and sex (160 risk strata). In the alternative model CD4 count was replaced by total lymphocyte count and degree of anaemia (288 risk strata). With the CD4 model the probability of death ranged from 0.9% (95% CI 0.6–1.4) in patients in the lowest risk stratum to 53% (44–62) in patients in the highest risk stratum. The corresponding probabilities for the total lymphocyte/haemoglobin model were 0.9% (0.5–1.4) and 60% (48–71). Prognostic models based on the CD4 cell count, or total lymphocytes and haemoglobin provide similarly strong discrimination in predicting early mortality in patients starting ART in sub-Saharan Africa. These models are useful for counselling patients, planning health services and predicting outcomes at the population level.