Effectiveness Research for Common Mental Disorders in Low and Middle Income Countries: A sequential, multiple assignment randomized trial for non-specialist treatment strategies in Kenya

项目摘要 精神障碍是全球残疾的主要原因，主要由抑郁和焦虑驱动。 大多数疾病负担在低收入和中等收入国家(LMIC)，在那里75%的成年人患有精神疾病 障碍患者没有获得服务的途径。尽管近15年的疗效研究表明，当地非 专家可以为LMIC患者的抑郁和焦虑提供循证护理，很少有研究取得进展 到关键的下一步：确定非专科医生如何最好地应用在 使用现有的交付平台并回应常见的临床难题，例如 从治疗开始，以及如何和何时修改治疗。 我们的研究团队已经在肯尼亚西部工作了5年，与加州大学旧金山分校和肯尼亚的合作(家庭 艾滋病护理和教育服务[FACES])，在70多所小学支持艾滋病毒综合服务 基苏木县的医疗设施。肯尼亚初级保健人群中主要疾病的患病率很高 抑郁障碍(MDD)(26%)和创伤后应激障碍(PTSD)(35%)--分别高2倍和4倍 分别超过了美国。考虑到需要个人化治疗以实现缓解(“治愈”或 没有疾病)和低收入国家缺乏心理健康专家，成功地减少了人口-- 抑郁和焦虑导致的残疾水平需要(1)针对一线和 由非专科医生提供的二线(非汇款)治疗，以及(2)确定患者级别 治疗结果主持人为个性化、资源高效的非专科治疗提供信息 算法。 为了满足这些需求，我们建议与地方和国家精神卫生利益攸关方合作，在 肯尼亚将确定(1)循证治疗一线和二线治疗战略，由非 与初级保健相结合的专家(目标1)，并调查(2)治疗结果的推定调解人 (目标2)确定(3)患者级别的治疗效果主持人，以提供个性化、资源高效的信息 非专科治疗算法(目标3)。我们将使用序贯、多任务随机试验 (SMART)将2,710名患有MDD和/或创伤后应激障碍的参与者随机分为非专科医生 人际心理治疗(IPT)或氟西汀；未缓解的患者将被重新随机分配到转换治疗或 为了联合治疗。 这项研究的结果将在三个方面具有重要意义：(1)它们将决定 非专科医生为LMIC中的MDD和/或PTSD提供一线和二线治疗，(2)他们将 研究IPT和氟西汀在大量人群中的假定作用机制，(3)它们将产生 预测算法对于在低资源下对MDD和/或PTSD的治疗进行最优排序至关重要 环境--解决全球主要残疾原因的关键障碍。

Project Abstract Mental disorders are a leading cause of global disability, driven primarily by depression and anxiety. Most of the disease burden is in Low and Middle Income Countries (LMICs), where 75% of adults with mental disorders have no service access. Despite nearly 15 years of efficacy studies showing that local non- specialists can provide evidence-based care for depression and anxiety in LMICs, few studies have advanced to the critical next step: identifying how non-specialists might best apply treatments with proven efficacy in the “real world” using existing delivery platforms and responding to common clinical dilemmas, such as what treatment to start with, and how and when to modify treatment. Our research team has worked in western Kenya for 5 years with a UCSF-Kenya collaboration (Family AIDS Care and Education Services [FACES]) that supports integrated HIV services at over 70 primary healthcare facilities in Kisumu County. Primary care populations in Kenya have high prevalence of Major Depressive Disorder (MDD) (26%) and Posttraumatic Stress Disorder (PTSD) (35%) – 2 and 4 times higher than in the U.S., respectively. Given the need for personalized treatment to achieve remission (“cure” or absence of disease) and the scarcity of mental health specialists in LMICs, successful reduction of population- level disability caused by depression and anxiety requires (1) evidence-based strategies for first-line and second-line (non-remitter) treatment delivered by non-specialists, and (2) identification of patient-level moderators of treatment outcome to inform personalized, resource-efficient non-specialist treatment algorithms. To address these needs, we propose to partner with local and national mental health stakeholders in Kenya to identify (1) evidence-based strategies for first-line and second-line treatment delivered by non- specialists integrated with primary care (Aim 1), and investigate (2) presumed mediators of treatment outcome (Aim 2) and determine (3) patient-level moderators of treatment effect to inform personalized, resource-efficient non-specialist treatment algorithms (Aim 3). We will use a Sequential, Multiple Assignment Randomized Trial (SMART) in which 2,710 participants with MDD, PTSD, or both will be randomized to non-specialist-delivered Interpersonal Psychotherapy (IPT) or to fluoxetine; non-remitters will be re-randomized to switch treatment or to combination therapy. The results of this research will be significant in three ways: (1) they will determine the effectiveness of non-specialist delivered first- and second-line treatment for MDD and/or PTSD in LMICs, (2) they will investigate presumed mechanisms of action for IPT and fluoxetine in a large population, (3) they will produce predictive algorithms essential for optimal sequencing of treatment for MDD and/or PTSD in low resource settings – a critical barrier for addressing a leading global cause of disability.