Developing methods of simultaneously analysing occurrence of several birth defects to improve identification of teratogenic medications

开发同时分析多种出生缺陷发生情况的方法，以提高致畸药物的识别能力

• 批准号: 2444769
• 金额: --
• 依托单位: St George's, University of London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2444769
• 关键词: Developing; methods; simultaneously; analysing; occurrence

Many pregnant women take prescribed or over-the counter medications in the 1st trimester of their pregnancy. In many cases, the medication is imperative to the health of the woman and cannot be avoided. In some cases, a woman who is taking medication may not know she is pregnant until after organogenesis has begun. Some medications are known to be teratogenic when taken in the 1st trimester of pregnancy, however, the risk to the fetus of most drugs is uncertain. Clinical trials do not assess possible effects of new medications on a fetus as pregnant women are purposefully excluded, and the effects of medications on animal models are not always comparative to humans due to differences in developmental pathways. Identification of teratogenic medications, therefore, requires careful analysis of observational data on congenital anomalies occurring in exposed pregnancies in the clinical setting. Although around 2-3% of pregnancies are affected by a birth defect, specific birth defects are rare. Therefore, the analysis of very large numbers of exposures is required to identify statistically significant effects for specific birth defects. Previous statistical methods for teratogen identification have focused on identifying increased occurrence of single defects. However, teratogen exposure often results in constellations of defects dependant on timing, dosage, and genetic interactions. Analysis of a group of birth defects may produce a statistically significant result when separate analysis of the single defects did not, implicating the medication as associated to the pattern of defects. EUROmediCAT has established a unique database containing information on the medications 33,000 mothers were prescribed during the first trimester of pregnancy, and the congenital anomalies the fetus had, from 15 countries in Europe from 1995-2016. This project will build upon the quantitative skills and knowledge developed during the Medical Statistics MSc (MRC-LID funded). Statistical and computational methods will be explored and applied to the EUROmediCAT dataset, in order to produce a methodology with increased ability to identify teratogenic medications, through the analysis of groups of birth defects. This will provide information on potential teratogens and will therefore influence targeted evidence gathering for these medications. This evidence can be used to help women and healthcare providers make better decisions when balancing the risk and benefit of medications taken during pregnancy.

许多孕妇在怀孕前三个月服用处方药或非处方药。在许多情况下，这种药物对妇女的健康是必不可少的，而且是不可避免的。在某些情况下，正在服药的女性可能直到器官发生开始后才知道自己怀孕了。一些药物在怀孕前三个月服用时会产生致畸作用，然而，大多数药物对胎儿的风险尚不确定。临床试验不会评估新药对胎儿的可能影响，因为故意将孕妇排除在外，而且由于发育途径的差异，药物在动物模型上的效果并不总是与人类相当。因此，识别致畸药物需要仔细分析临床环境中暴露的妊娠中发生的先天性异常的观察数据。虽然大约2%-3%的怀孕会受到出生缺陷的影响，但特定的出生缺陷很少见。因此，需要对大量暴露进行分析，以确定对特定出生缺陷的统计显著影响。以往用于畸胎鉴定的统计方法主要集中在识别单一缺陷的增加。然而，致畸剂的暴露往往会导致取决于时间、剂量和遗传交互作用的一系列缺陷。当单独分析单个缺陷时，对一组出生缺陷的分析可能会产生统计上显著的结果，这表明药物与缺陷的模式有关。EUROmediCAT建立了一个独特的数据库，其中包含1995年至2016年期间来自欧洲15个国家的3.3万名母亲在怀孕前三个月开的药物以及胎儿先天畸形的信息。该项目将建立在医学统计学硕士期间发展的量化技能和知识(MRC-LID资助)。将探索统计和计算方法，并将其应用于EUROmediCAT数据集，以便通过对出生缺陷组的分析，制定一种具有更强的识别致畸药物能力的方法。这将提供有关潜在致畸物质的信息，因此将影响这些药物的有针对性的证据收集。这些证据可以用来帮助妇女和医疗保健提供者在平衡怀孕期间服用药物的风险和好处时做出更好的决定。