Active Surveillance of the Safety of Antipsychotic Medications in Pregnancy

心理健康问题在怀孕和产后妇女以及非怀孕妇女中很常见 育龄妇女。虽然许多患者需要药物治疗，但精神药物的安全性 怀孕期间的药物治疗是一个证据差距很大的领域。从历史上看，自发的报告，怀孕 暴露登记和病例对照设计是评价阿司匹林安全性的主要方法 怀孕期间服用精神药物，所有这些药物都有众所周知的局限性。近年来，该领域已经 在进行嵌套在大型医疗保健利用数据中的队列研究方面获得了大量专业知识。横跨所有 这些设计、研究倾向于关注一个或几个选定的不良妊娠结局，它们是 在药物进入市场多年后的一个时间点上执行，并已被许多人使用 怀孕的女人。避免母亲和胎儿不必要地接触有害药物或避免 在没有有害影响的情况下，妇女被不必要地剥夺了精神疾病的治疗机会 需要新的和系统的方法来及时地产生精神药物安全性的证据 关于所有相关的孕产妇和胎儿结局，在怀孕期间。 我们将开发和实施基于TreeScan的方法来进行抗精神病药物的主动监测 怀孕期间的用药安全。TreeScan是一种新的药物安全监测方法，它扫描 特定结果以及临床相关结果组的分层树，用于与 利益的处理，同时考虑了相关假设的多重检验。我们将首先发展 基于共享的先天性畸形、母亲和其他新生儿结局的层次树 基础疾病过程，并修改TreeScan方法以适应 妊娠背景下的药物安全性评价。使用分层树提高了临床检测的能力 相关的结果，这将是不可行的，只评估个别诊断。然后我们将实施 TreeScan用于评估与以下各项相关的广泛不良母婴结局的风险 抗精神病药物。抗精神病药物是女性精神分裂症和 双相情感障碍，但对它们在怀孕期间的安全性知之甚少，特别是对新生的 抗精神病药物。我们将在全国范围内使用超过350万名公共和私人保险的怀孕病例 美国，嵌套在医疗保健利用数据库中，其中包含有关混杂因素的丰富信息。在最终的目标中， 我们将扩展该方法，对新批准的 抗精神病药物和其他精神药物，以便尽早发现潜在的安全信号 经批准后。通过为医疗保健提供者提供必要的信息来进行循证 开处方决定，并建议妇女在怀孕期间使用特定的抗精神病药物， 拟议的研究将对围产期精神病学领域的公共卫生产生直接影响。

Mental health conditions are common among pregnant and postpartum women as well as non-pregnant women of reproductive age. While many patients require pharmacologic treatment, the safety of psychotropic medications in pregnancy is an area with large evidence gaps. Historically, spontaneous reports, pregnancy exposure registries, and case-control designs were the main approaches used to evaluate the safety of psychotropic medications in pregnancy, all of which have well-known limitations. In recent years, the field has gained much expertise with the conduct of cohort studies nested in large healthcare utilization data. Across all these designs, studies tend to focus on a single or a few selected adverse pregnancy outcomes, and they are performed at a single time point many years after the drug has entered the market and has been used by many pregnant women. To avoid unnecessary exposure of mother and fetus to harmful medications or to avoid women being unnecessarily deprived of treatments for psychiatric disorders when no harmful effects exist, a new and systematic approach is needed to generate timely evidence on the safety of psychotropic medications in pregnancy with respect to all relevant maternal and fetal outcomes. We will develop and implement a TreeScan based approach to conduct active surveillance of antipsychotic medication safety in pregnancy. TreeScan is a novel method for drug safety surveillance, which scans hierarchical trees of specific outcomes as well as groups of clinically related outcomes for associations with the treatment of interest, while accounting for multiple testing of correlated hypotheses. We will first develop hierarchical trees for congenital malformations, maternal and other neonatal outcomes based on shared underlying disease processes, and modify the TreeScan approach to accommodate the unique challenges of drug safety evaluation in the context of pregnancy. Use of hierarchical trees increases power to detect clinically related outcomes, which would not be feasible by evaluating individual diagnoses only. We will then implement TreeScan to evaluate the risks of a broad range of adverse maternal and neonatal outcomes associated with antipsychotic medications. Antipsychotics are the mainstay of treatment for women with schizophrenia and bipolar disorder, but little is known regarding their safety profile in pregnancy, especially for the newer antipsychotics. We will use nationwide cohorts of over 3.5 million publicly and privately insured pregnancies in the US, nested in healthcare utilization databases that contain rich information on confounders. In the final aim, we will extend the approach to conduct near real-time prospective, sequential surveillance of newly approved antipsychotic and other psychotropic medications in order to detect potential safety signals as early as possible after approval. By providing the necessary information for healthcare providers to make evidence-based prescribing decisions and to counsel women about the use of specific antipsychotics during pregnancy, the proposed studies will have an immediate public health impact within the field of perinatal psychiatry.