Active Surveillance of the Safety of Antipsychotic Medications in Pregnancy

妊娠期抗精神病药物安全性的主动监测

基本信息

  • 批准号:
    10391510
  • 负责人:
  • 金额:
    $ 53.22万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-04-12 至 2026-03-31
  • 项目状态:
    未结题

项目摘要

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.
心理健康状况在孕妇和产后妇女以及非孕妇中很常见

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Krista F Huybrechts其他文献

Short-Term Increases in NO2 and O3 Concentrations during Pregnancy and Stillbirth Risk in the U.S.: A Time-Stratified Case-Crossover Study.
美国怀孕期间 NO2 和 O3 浓度的短期增加和死产风险:时间分层病例交叉研究。
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    11.4
  • 作者:
    M. Shupler;Krista F Huybrechts;Michael Leung;Yaguang Wei;Joel Schwartz;Longxiang Li;P. Koutrakis;S. Hernández;Stefania Papatheodorou
  • 通讯作者:
    Stefania Papatheodorou
Emulating a Target Trial of Interventions Initiated During Pregnancy With Healthcare Databases: The Example of COVID-19 Vaccination. The Authors Respond.
利用医疗保健数据库模拟怀孕期间启动的干预措施的目标试验:以 COVID-19 疫苗接种为例。
  • DOI:
    10.1097/ede.0000000000001710
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    5.4
  • 作者:
    Sonia Hernández;Krista F Huybrechts;Miguel A Hernán
  • 通讯作者:
    Miguel A Hernán

Krista F Huybrechts的其他文献

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{{ truncateString('Krista F Huybrechts', 18)}}的其他基金

TreeScan to Evaluate the Safety of New Drugs in Pediatric Populations
TreeScan 评估新药在儿科人群中的安全性
  • 批准号:
    10539032
  • 财政年份:
    2022
  • 资助金额:
    $ 53.22万
  • 项目类别:
TreeScan to Evaluate the Safety of New Drugs in Pediatric Populations
TreeScan 评估新药在儿科人群中的安全性
  • 批准号:
    10673144
  • 财政年份:
    2022
  • 资助金额:
    $ 53.22万
  • 项目类别:
Active Surveillance of the Safety of Antipsychotic Medications in Pregnancy
妊娠期抗精神病药物安全性的主动监测
  • 批准号:
    10611382
  • 财政年份:
    2021
  • 资助金额:
    $ 53.22万
  • 项目类别:
Active Surveillance of the Safety of Antipsychotic Medications in Pregnancy
妊娠期抗精神病药物安全性的主动监测
  • 批准号:
    10179605
  • 财政年份:
    2021
  • 资助金额:
    $ 53.22万
  • 项目类别:
In-utero exposure to psychotropic medications and the risk of neurodevelopmental disorders
子宫内接触精神药物和神经发育障碍的风险
  • 批准号:
    10378117
  • 财政年份:
    2018
  • 资助金额:
    $ 53.22万
  • 项目类别:
In-utero exposure to psychotropic medications and the risk of neurodevelopmental disorders
子宫内接触精神药物和神经发育障碍的风险
  • 批准号:
    10133474
  • 财政年份:
    2018
  • 资助金额:
    $ 53.22万
  • 项目类别:
In-utero exposure to psychotropic medications and the risk of neurodevelopmental disorders
子宫内接触精神药物和神经发育障碍的风险
  • 批准号:
    9893923
  • 财政年份:
    2018
  • 资助金额:
    $ 53.22万
  • 项目类别:
Ondansetron and risk of congenital malformations
昂丹司琼和先天性畸形的风险
  • 批准号:
    9298084
  • 财政年份:
    2017
  • 资助金额:
    $ 53.22万
  • 项目类别:
Improved methods to assess the comparative safety of new psychiatric medications
评估新精神科药物相对安全性的改进方法
  • 批准号:
    8711562
  • 财政年份:
    2013
  • 资助金额:
    $ 53.22万
  • 项目类别:
Improved methods to assess the comparative safety of new psychiatric medications
评估新精神科药物相对安全性的改进方法
  • 批准号:
    8581368
  • 财政年份:
    2013
  • 资助金额:
    $ 53.22万
  • 项目类别:

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