The Causal Effect of Effective Depression Treatment on HIV Outcomes in CNICS

描述（由申请人提供）：抑郁症是HIV感染者中非常常见的合并症。 抑郁症与一系列不良健康行为和结果相关，包括降低抗逆转录病毒（ARV）药物依从性，增加HIV传播风险行为，增加病毒学失败和死亡率。 抗抑郁药物和心理治疗对治疗艾滋病毒感染者的抑郁症有效。 因此，对于HIV临床医生、研究人员和政策制定者来说，一个重要的问题是抑郁症治疗在多大程度上可以改善HIV行为、风险传播和临床结果，并帮助实现ARV治疗预防的全部潜力。有限的现实世界，强有力的证据表明，通过投资于艾滋病毒患者的高质量抑郁症治疗，可以实现人口水平对传播和健康的影响。 抑郁症治疗对艾滋病毒结果的影响的精确和有效的因果估计，特别是从大规模和可推广的样本，是必要的，以确定艾滋病毒相关的回报，这种投资。 少数随机对照试验表明，在强化的基于心理治疗的抑郁症治疗干预后，抗逆转录病毒药物的依从性有所改善，但这些试验是在小样本和不可推广的样本中进行的。 一些观察性研究表明抗抑郁治疗与抗逆转录病毒治疗依从性呈正相关，但这些研究通常没有使用适当的因果推断统计方法来解释抑郁症状和治疗之间的动态关系。 迄今为止的研究也通常将所有抗抑郁药治疗归为一类，而不是将充分（最佳实践）治疗与临床惰性（非精神科提供者未能滴定抗抑郁药的倾向）区分开来 剂量以解决持续的症状。 在本项目中，我们将利用来自美国8个CFAR临床中心的25，000名患者的大型和多样化CNICS观察队列中的丰富信息，以完成以下目标：（1）描述 在HIV临床护理中提供的充分与不充分的抗抑郁药治疗;（2）使用最先进的因果推断方法估计抗抑郁药治疗，特别是充分的抗抑郁药治疗对HIV相关行为和健康结果的影响程度;以及（3）评估适当的抑郁症治疗对HIV结果的影响是否因某些亚组而异，例如那些抑郁严重程度更高的亚组，并发焦虑或酗酒或吸毒。 这项工作的范围是重要的，因为我们将（1）确定目前的“抑郁症治疗差距”在艾滋病毒的初级保健，（2）确定人口水平的影响，艾滋病毒的结果可通过减少这一差距，（3）确定亚群的减少治疗差距可能是最有益的。 我们的建议是创新的，在其使用先进的因果推理方法，其重点是区分充分的抗抑郁药治疗不足。 CNICS中所代表的大量和多样化的患者人群将增强这项工作的发现对美国各地从事HIV初级保健的HIV感染患者人群的普遍性。

DESCRIPTION (provided by applicant): Depression is an exceedingly common comorbidity among HIV-infected patients. Depression has been associated with a range of adverse health behaviors and outcomes including reduced antiretroviral (ARV) medication adherence, increased HIV transmission risk behaviors, increased virologic failure, and higher mortality. Antidepressant medications and psychotherapy are effective in treating depression in HIV-infected patients. Consequently, an important question for HIV clinicians, researchers, and policy-makers is the extent to which depression treatment can improve HIV behavioral, risk transmission, and clinical outcomes and help realize the full potential of ARV treatment-as-prevention. Limited real-world, robust evidence exists about the population-level impact on transmission and health that could be achieved by investing in high-quality depression treatment for HIV patients. Precise and valid causal estimates of the effect of depression treatment on HIV outcomes, especially from large and generalizable samples, are necessary to define the HIV-related return on such investment. A small number of randomized controlled trials have demonstrated improvements in ARV adherence after intensive psychotherapy-based depression treatment interventions, but have been conducted in small and non-generalizable samples. Several observational studies have suggested a positive association of antidepressant treatment with ARV adherence, but these studies have generally not used appropriate causal inference statistical methods to account for the dynamic relationship between depressive symptoms and treatment. Studies to date have also generally grouped all antidepressant treatment together, rather than distinguish adequate (best-practices) treatment from clinical inertia - the tendency of non-psychiatric providers to fail to titrate antidepressant doses to address ongoing symptoms. In this project, we will draw on the rich information in the large and diverse CNICS observational cohort, encompassing 25,000 patients from 8 CFAR clinical sites across the US, to complete the following aims: (1) to characterize the frequency of adequate vs. inadequate antidepressant treatment provided within HIV clinical care; (2) to estimate the magnitude of the effect of antidepressant treatment, and specifically adequate antidepressant treatment, on HIV-related behavioral and health outcomes using state-of-the-art causal inference methods; and (3) to assess whether the effect of adequate depression treatment on HIV outcomes differs for certain subgroups, such as those with greater depressive severity, concurrent anxiety, or problematic alcohol or drug use. This scope of work is significant because we will (1) define the current "depression treatment gap" in HIV primary care, (2) define the population-level impact on HIV outcomes achievable by reducing that gap, and (3) define subpopulations for which the reduction of the treatment gap could be most beneficial. Our proposal is innovative in its use of advanced causal inference methods and its focus on distinguishing adequate from inadequate antidepressant treatment. The large and diverse patient population represented in CNICS will enhance the generalizability of this work's findings to the population of HIV-infected patients engaged in HIV primary care across the United States.