Real-Time Evaluation of Emerging Treatments for Suicide Risk

自杀风险新兴治疗方法的实时评估

• 批准号: 10021735
• 负责人: GREGORY E. SIMON
• 金额: --
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-23 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10021735
• 关键词: Adverse effects; Cessation of life; Clinical Research; Clinical Trials; Collection; Complex; Cycloserine; Data; Development; Evaluation; Feeling suicidal; Generations; Gleevec; Glutamate Receptor; Health system; Heterogeneity; Hospitalization; Infusion procedures; Intravenous; Ketamine; Libraries; Licensure; Machine Learning; Mental Depression; Mental Health; Methods; Modeling; Outcome; Outpatients; Oxycodone; Patient Outcomes Assessments; Patients; Pattern; Pharmaceutical Preparations; Phenotype; Physician Executives; Provider; Recording of previous events; Research; Risk Factors; Sequential Treatment; Series; Suicide attempt; Time; Translating; Work; analytical method; data infrastructure; depressive symptoms; design; innovation; interest; off-label use; outcome prediction; practice-based research network; psychotic symptoms; public health priorities; reduce symptoms; suicidal behavior; suicidal morbidity; suicidal risk; treatment duration; treatment effect; treatment risk; treatment-resistant depression

Reducing risk of suicidal behavior is an urgent public health priority. Evidence that intravenous ketamine infusion could rapidly reduce symptoms of depression and suicidal ideation led to a series of small clinical trials, as well as increasing off-label use for treatment of severe depression. Findings regarding effects of ketamine infusion on suicidal ideation have inspired development of new medications designed to mimic ketamine's glutamate receptor modulator activity. Two of those products (intranasal esketamine and a sequential treatment of ketamine infusion followed by lurasidone plus d-cycloserine) have been designated by the FDA as potential breakthrough treatments, with rapid approval expected. Clinical trials completed prior to licensure will likely demonstrate that these new products (and similar products to follow) rapidly reduce symptoms of depression and suicidal ideation – leading to approval for those specific indications. Pre-approval trials, however, will not address questions of greatest interest to patients, providers, and health systems: Will short-term reductions in suicidal ideation actually translate to reduced risk of suicidal behavior? Enthusiasm regarding the potential benefits of new ketamine-like drugs is tempered by concerns regarding adverse effects, tolerance/rebound, and potential for misuse. Intravenous ketamine infusion can precipitate dissociative or psychotic symptoms, and ketamine has a long history of recreational misuse. During our discussions with health system leaders regarding this proposed research, one medical director pointed out, “Esketamine could be the next Gleevec or the next Oxycontin. We had better find out which.” We propose to use innovative methods to rapidly evaluate the effect of these anticipated new treatments on risk of suicidal behavior among outpatients with treatment-resistant depression. This work will take advantage of unique capabilities of our network, including comprehensive longitudinal data infrastructure, routine collection of patient-reported outcome data, an extensive library of computable EHR phenotypes regarding suicidal behavior risk factors and outcomes, machine-learning models to accurately predict suicidal behavior, and analytic methods for causal inference for rare exposures and outcomes. The proposed research will use data from three MHRN health systems to: 1) Rapidly evaluate patterns of use of newly approved therapies for treatment-resistant depression 2) Extract comprehensive predictor and outcome data regarding patients receiving and not receiving emerging treatments with potential to reduce risk of suicidal behavior 3) Develop and implement variable selection approaches for weighted propensity score analyses 4) Use these data and methods to evaluate impact of emerging treatments on risk of suicide death, suicide attempt, or psychiatric hospitalization within 90 days of a treatment decision. 5) Examine heterogeneity of treatment effects according to pre-treatment risk of suicidal behavior

降低自杀行为的风险是一项紧迫的公共卫生优先事项。有证据表明静脉注射氯胺酮 输液可迅速减轻抑郁症状和自杀意念导致一系列小型临床研究 试验，以及增加用于治疗严重抑郁症的超说明书用药。关于影响的调查结果 氯胺酮输注对自杀意念的影响激发了新药物的开发，旨在模仿 氯胺酮的谷氨酸受体调节剂活性。其中两种产品（鼻内艾氯胺酮和 氯胺酮输注序贯治疗，然后鲁拉西酮加 d-环丝氨酸）已被指定为 FDA 将其视为潜在的突破性治疗方法，预计将迅速获得批准。之前完成的临床试验 许可可能会证明这些新产品（以及后续的类似产品）会迅速减少 抑郁症和自杀意念的症状——导致批准这些特定的适应症。前置审批 然而，试验不会解决患者、提供者和卫生系统最感兴趣的问题： 自杀意念的短期减少实际上意味着自杀行为风险的降低？热情 关于新型氯胺酮类药物的潜在益处的考虑因对​​不良反应的担忧而减弱， 耐受性/反弹以及误用的可能性。静脉输注氯胺酮可导致解离或 精神病症状，而氯胺酮有着悠久的娱乐滥用历史。在我们的讨论中 对于这项拟议的研究，卫生系统领导者指出，“艾氯胺酮可以 成为下一个格列卫或下一个奥施康定。我们最好找出是哪一个。” 我们建议使用创新方法来快速评估这些预期新产品的效果 治疗难治性抑郁症门诊患者的自杀行为风险。这项工作将 利用我们网络的独特功能，包括全面的纵向数据基础设施， 例行收集患者报告的结果数据、可计算 EHR 表型的广泛库 关于自杀行为的风险因素和结果，机器学习模型可以准确预测自杀行为 行为，以及对罕见暴露和结果进行因果推断的分析方法。拟议的研究 将使用来自三个 MHRN 卫生系统的数据来： 1) 快速评估新批准的难治性抑郁症疗法的使用模式 2) 提取有关接受和未接受治疗的患者的综合预测因素和结果数据 可能降低自杀行为风险的新兴治疗方法 3) 开发并实施加权倾向评分分析的变量选择方法 4) 使用这些数据和方法来评估新兴治疗方法对自杀死亡、自杀风险的影响 尝试，或在做出治疗决定后 90 天内住院治疗。 5）根据治疗前的自杀行为风险检查治疗效果的异质性