Long-term Impact of Fertility Treatment Study

生育治疗研究的长期影响

基本信息

批准号：
9361656
负责人：
MIGUEL HERNAN
金额：
$ 66.52万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-02 至 2022-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9361656
关键词：
Address Adolescence Adoption Adult Aftercare Animals Assisted Reproductive Technology Asthma Birth Characteristics Child Child Development Child health care Childbirth Clinic Clinical Clinical Treatment Country Couples Data Data Analyses Data Set Data Sources Denmark Development Diabetes Mellitus Diagnosis Disease Education Epigenetic Process Event Fertility Fertilization in Vitro Glucose Intolerance Health Health Services Accessibility Healthcare Hospitalization Human Hypertension Income Individual Infertility Insurance Coverage Intellectual functioning disability Intracytoplasmic Sperm Injections Investments Life Literature Malignant Childhood Neoplasm Malignant Neoplasms Massachusetts Maternal Age Measures Medical Metabolic Methodology Modernization Nature Netherlands Neurodevelopmental Impairment Outcome Parents Patients Population Pregnancy Probability Research Research Project Grants Resources Risk Sentinel Series Socioeconomic Status Source Statistical Methods Sweden Techniques Thyroid Diseases Time Variant Weight analytical method base cohort cost emerging adult evidence base follow-up functional outcomes infancy infertility treatment population based premature success trait treatment choice treatment effect treatment strategy

项目摘要

Use of fertility treatments is growing with as many as 10% of births occurring after use of assisted reproductive technologies (ART) or non-IVF fertility treatments (NIFT). These treatments often require substantial societal and individual investments of resources and time, yet there is little information on the long-term health or development outcomes for children born after treatment. Indeed, most of the existing literature centers around events occurring during birth or infancy, with limited and mixed findings about events later in life. This limited literature also reflects major methodological challenges, including (i) insufficient follow-up time to assess the development of medical conditions past adolescence and into adulthood; (ii) numerous potential confounders, including the original reason for needing treatment (infertility), and variation in access to and use of treatments, e.g., differential access by income or education; and (iii) use of analytic approaches that either do not address relevant sources of bias, or rely on ill-defined assumptions to assess treatment effects. To both address the need for more evidence and mitigate the methodological concerns, we propose to compare the risk of outcomes associated with different fertility treatments using multiple population-based, nationwide rich datasets combined with modern causal inference approaches. Our aims are to examine the impact of fertility treatments (stratified by the type of infertility) on two types of outcomes: 1) clinical events; and 2) educational events. We will study nearly 400,000 children born after fertility treatments during 1980-2020 in four populations (in Denmark, the Netherlands, Sweden, and Massachusetts). Across these populations, we have comprehensive, individual-level information on our outcomes and potential cofounders, e.g., types of infertility, treatments, education, income, and clinic traits. We will perform both predictive and causal analyses in order to inform clinicians and potential parents as they first consider use of fertility treatments, then choose between available treatments. Our statistical methods encompass a series of approaches starting with traditional survival and repeated measures analyses, and more recently developed techniques for causal analysis with observational data, e.g., inverse-probability weighting. We also will explore alternative approaches using instrumental variables and the g-formula. In short, this study provides the best opportunity to assess long-term outcomes in children born after fertility treatments, with the longest follow-up time, most extensive set of demographic, clinical, and treatment characteristics, and use of state-of-the-art analytic approaches.

生育治疗的使用正在增长，多达 10% 的婴儿是在使用辅助生殖后出生的技术 (ART) 或非 IVF 生育治疗 (NIFT)。这些治疗通常需要大量的社会力量以及资源和时间的个人投资，但关于长期健康或治疗后出生的儿童的发育结果。事实上，大多数现有文献都围绕出生或婴儿期发生的事件，对以后生活的事件的发现有限且混杂。这个有限文献还反映了主要的方法学挑战，包括（i）没有足够的后续时间来评估青春期过后和成年期的医疗状况的发展； (ii) 许多潜在的混杂因素，包括需要治疗的最初原因（不孕不育），以及获得和使用治疗的变化，例如，按收入或教育程度划分的差别待遇； (iii) 使用不解决问题的分析方法偏倚的相关来源，或依赖不明确的假设来评估治疗效果。两者都解决了需要更多证据并减轻方法论问题，我们建议比较以下风险与使用多种基于人口的全国富人的不同生育治疗相关的结果数据集与现代因果推理方法相结合。我们的目标是检查生育力的影响针对两种结果的治疗（按不孕类型分层）：1）临床事件； 2）教育事件。我们将在 1980 年至 2020 年期间对近 400,000 名接受生育治疗后出生的儿童进行四个研究人口（丹麦、荷兰、瑞典和马萨诸塞州）。在这些人群中，我们有关于我们的成果和潜在联合创始人的全面、个人层面的信息，例如不孕不育的类型，治疗、教育、收入和临床特征。我们将进行预测分析和因果分析，以便告知临床医生和潜在父母，让他们首先考虑使用生育治疗，然后进行选择可用的治疗方法。我们的统计方法涵盖一系列从传统方法开始的方法生存和重复测量分析，以及最近开发的因果分析技术观察数据，例如逆概率加权。我们还将探索使用替代方法工具变量和 g 公式。简而言之，这项研究提供了评估长期效果的最佳机会生育治疗后出生的孩子的结果，随访时间最长，范围最广人口统计、临床和治疗特征，以及最先进的分析方法的使用。