SCH: Prediction of Preterm Birth in Nulliparous Women

SCH：未产妇早产的预测

• 批准号: 10018949
• 负责人: Alexander M Friedman
• 金额: $ 25.26万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-16 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10018949
• 关键词: Address; Algorithms; Behavioral; Caring; Clinical; Clinical Data; Data; Data Collection; Data Set; Decision Making; Diagnostic tests; Effectiveness; Emotional; Etiology; Family; Female; Future; Genes; Genetic; Geography; Hospitals; Individual; Infant; Instruction; Intervention; Journals; Knowledge; Learning; Literature; Medical; Medical Genetics; Methods; Modeling; Mothers; National Institute of Child Health and Human Development; New York; Nulliparity; Paper; Patient Schedules; Patients; Pattern; Phenotype; Population Heterogeneity; Pregnancy; Pregnancy Histories; Premature Birth; Presbyterian Church; Prospective cohort study; Public Health; Recording of previous events; Research; Risk; Risk Factors; Series; Social Impacts; Societies; Testing; Time; United States; United States National Institutes of Health; Variant; Visit; Woman; Work; base; clinical practice; design; disability; effectiveness testing; genetic association; genetic information; genome wide association study; graduate student; high risk; improved; insight; intervention cost; minority student; mortality; multidisciplinary; neonate; non-genetic; phenotypic data; predictive modeling; racial and ethnic; recruit; support vector machine; symposium; undergraduate research

Preterm Birth (PTB) is a major long-lasting public health problem being the leading cause of mortality and long-term disabilities among neonates, with heavy emotional and financial consequences to families and society. Prediction of PTB risk has been an exceedingly challenging problem, in particular for first time mothers (nulliparous women) due to the lack of prior pregnancy history. Most studies to date have examined individual risk factors, genetic, environmental, or behavioral, through univariate analyses of their association with PTB, including GWAS identifying modest contribution of common variants across six gene regions. The challenge of improving PTB prediction is due to the inherent complexity of its multifactorial etiology and the lack of approaches capable of integrating and interpreting large multidisciplinary data. Our previous work [NSF Eager 1454855, 1454814] developed predictive models for PTB based on non-genetic maternal attributes. An important question is to know whether factors other than history of PTB can be used to identify a nullipara patient at risk. We plan on devising longitudinal risk prediction methods for PTB that integrate every piece of available data. We will address three important gaps in current literature as our three project objectives: a focused study of nulliparous women and their risk for PTB; combining genetic factors with other clinical factors to determine risk ; and using longitudinal data and models to optimize scheduling of patient visits, testing and treatment. We will focus on a recently released NIH-NICHD dataset called nuMoM2b, which is a prospective cohort study of a racially/ethnically/geographically diverse population of10 ,038 nulliparous women with singleton gestation . Our aims are as follows: (1) Longitudinal Preterm Birth Prediction ; (2) Combining clinical and genetic features for risk prediction ; (3) Assessing the effectiveness of the methods in clinical practice. RELEVANCE (See instructions) . Over 26 billion dollars are spent annually on the delivery and care of the 12% of infants who are born preterm in the United States. A crucial challenge is to identify women who are at the highest risk for early preterm birth and to develop interventions. Equally important, would be the ability to identify women at the lowest risk to avoid unnecessary and costly interventions. Our project has the potential to advance knowledge about this long-lasting public health problem.

早产（PTB）是一个主要的长期公共卫生问题，是死亡的主要原因， 新生儿长期残疾，给家庭带来严重的情感和经济后果， 社会肺结核风险的预测一直是一个极具挑战性的问题，特别是首次 母亲（未经产的妇女）由于缺乏既往妊娠史。迄今为止，大多数研究都 通过单变量分析，研究了个体风险因素，遗传的，环境的，或行为的， 与PTB相关，包括GWAS确定了六个基因中常见变异的适度贡献 地区改善PTB预测的挑战是由于其多因素的固有复杂性 病因学和缺乏能够整合和解释大型多学科数据的方法。我们 以前的工作[NSF Eager 1454855，1454814]开发了基于非遗传的PTB预测模型 母性属性一个重要的问题是要知道是否可以使用除PTB病史以外的因素 来确定一个未产妇的风险。我们计划为PTB设计纵向风险预测方法， 整合所有可用数据。我们将解决当前文献中的三个重要空白， 三个项目目标：对未经产妇女及其患肺结核的风险进行重点研究; 因素与其他临床因素确定风险;并使用纵向数据和模型来优化 安排患者访视、检测和治疗。我们将重点关注最近发布的NIH-NICHD数据集 称为nuMoM 2b，这是一项针对种族/民族/地理多样性的前瞻性队列研究。 10，038名单胎妊娠的未经产妇女。 我们的目标如下：（1）纵向早产预测;（2）结合临床和遗传学 （3）评估方法在临床实践中的有效性。 相关性（参见说明）。 每年有超过260亿美元用于12%婴儿的分娩和护理 美国的早产儿。一个关键的挑战是确定早期妊娠风险最高的妇女。 早产和制定干预措施。同样重要的是，有能力确定妇女在 降低风险，避免不必要和昂贵的干预。我们的项目有潜力推进 了解这个长期存在的公共卫生问题。