Sampling-based approaches to improve estimation of mortality among patient dropouts: experience from a large PEPFAR-funded program in Western Kenya.
Sampling-based approaches to improve estimation of mortality among patient dropouts: experience from a large PEPFAR-funded program in Western Kenya.
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DOI：
10.1371/journal.pone.0003843
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发表时间：
2008
期刊：
影响因子：
3.7
通讯作者：
Kimaiyo S
中科院分区：
文献类型：
--
作者：
Yiannoutsos CT;An MW;Frangakis CE;Musick BS;Braitstein P;Wools-Kaloustian K;Ochieng D;Martin JN;Bacon MC;Ochieng V;Kimaiyo S
艾滋病毒护理和治疗方案的监测和评估（M&E）受到患者群体中随访损失（LTFU）的影响。这种影响的严重性是不可否认的，但其程度是未知的。追踪所有丢失的患者可以解决这个问题，但在发展中国家迅速扩大艾滋病毒治疗的项目中，人口普查方法并不可行。基于抽样的方法和统计调整是唯一可扩展的方法，可以准确估计M&E指数。在肯尼亚西部的一个大型抗逆转录病毒治疗（ART）项目中，我们评估了LTFU对8,977名成年客户估计患者死亡率的影响，其中3,624人是LTFU。总体而言，辍学者多为男性（36.8%对33.7%,p = 0.003），年龄小于非辍学者（35.3对35.7,p = 0.020），入组时CD4细胞计数中位数较低（160对189个细胞/ml， p<0.001），世卫组织3-4期疾病（47.5%对41.1%,p<0.001）。非辍学率为75.0%，辍学率为70.3% （p<0.001）。在3624名辍学者中，有1143人被寻找，621人的生命状况得到了确定。统计技术用于根据从定位的LTFU患者获得的信息调整死亡率估计。入组后一年观察到的死亡率估计值为1.7% (95% CI 1.3%-2.0%)，当加入通过外展发现的死亡并根据所使用的方法通过统计建模调整为9.2%（7.8%-10.6%）和9.9%（8.4%-11.5%）时，修正为2.8%（2.3%-3.1%）。抗逆转录病毒治疗开始后12个月的估计分别为1.7%（1.3%-2.2%）、3.4%（2.9%-4.0%）、10.5%（8.7%-12.3%）和10.7%（8.9%-12.6%）。评估LTFU的影响在项目评估中至关重要，因为基于被动监测的估计死亡率可能低估真实死亡率高达80%。这种偏差可以通过追踪辍学者样本和统计调整死亡率估计来改善，以正确评估和指导大型艾滋病毒护理和治疗计划。
Monitoring and evaluation (M&E) of HIV care and treatment programs is impacted by losses to follow-up (LTFU) in the patient population. The severity of this effect is undeniable but its extent unknown. Tracing all lost patients addresses this but census methods are not feasible in programs involving rapid scale-up of HIV treatment in the developing world. Sampling-based approaches and statistical adjustment are the only scaleable methods permitting accurate estimation of M&E indices. In a large antiretroviral therapy (ART) program in western Kenya, we assessed the impact of LTFU on estimating patient mortality among 8,977 adult clients of whom, 3,624 were LTFU. Overall, dropouts were more likely male (36.8% versus 33.7%; p = 0.003), and younger than non-dropouts (35.3 versus 35.7 years old; p = 0.020), with lower median CD4 count at enrollment (160 versus 189 cells/ml; p<0.001) and WHO stage 3–4 disease (47.5% versus 41.1%; p<0.001). Urban clinic clients were 75.0% of non-dropouts but 70.3% of dropouts (p<0.001). Of the 3,624 dropouts, 1,143 were sought and 621 had their vital status ascertained. Statistical techniques were used to adjust mortality estimates based on information obtained from located LTFU patients. Observed mortality estimates one year after enrollment were 1.7% (95% CI 1.3%–2.0%), revised to 2.8% (2.3%–3.1%) when deaths discovered through outreach were added and adjusted to 9.2% (7.8%–10.6%) and 9.9% (8.4%–11.5%) through statistical modeling depending on the method used. The estimates 12 months after ART initiation were 1.7% (1.3%–2.2%), 3.4% (2.9%–4.0%), 10.5% (8.7%–12.3%) and 10.7% (8.9%–12.6%) respectively. Assessment of the impact of LTFU is critical in program M&E as estimated mortality based on passive monitoring may underestimate true mortality by up to 80%. This bias can be ameliorated by tracing a sample of dropouts and statistically adjust the mortality estimates to properly evaluate and guide large HIV care and treatment programs.