Contact PD/PI: Wen, Xuerong ABSTRACT Mediation analysis is useful to quantify the direct and indirect relationship among maternal opioid exposure during pregnancy, short-term adverse neonatal outcomes, and long-term neurodevelopmental outcomes in children. There are different approaches to estimate mediation models, and Bayesian methods offer some advantages compared to their frequentist counterparts: possibility of including prior information, computational feasibility when a multilevel model structure is needed, and more flexibility in analyzing data with smaller sample sizes. In conducting the originally funded project (1R15HD097588), we have observed significant effects for pregnancy opioid exposure on multiple short-term congenital malformations and long-term neurodevelopmental outcomes in children. However, it is unclear whether the observed effects are direct or indirect, and whether the effect of maternal opioid usage on neonatal development remains significant after adjusting for mediation factors. The limited data sources restrain our knowledge and creates a formidable research opportunity. In this project, we will investigate mediation effects of maternal opioid use on multiple short- and long-term adverse pregnancy outcomes for children. Two linked datasets will be used to examine different outcomes, provide a long follow-up time, and validate the estimation of pregnancy window. Our findings from the originally awarded project have shown that prescription opioid use in pregnant women is associated with increased risk of congenital malformations and neonatal neurodevelopmental outcomes. It is necessary to further adjust for the mediation factors and determine the direct effects of opioid exposure during pregnancy. The focus of this project is to study the relationship between perinatal opioid exposure and adverse health outcomes in children. We hypothesize that prescription opioid use during pregnancy directly poses risks on long-term development of children, and that optimized pain management in pregnant women improves long-term health outcomes for children.
Specific Aim 1 : To identify the mediation factors that are on the causal pathway of maternal exposure to prescription opioids and neonatal neurodevelopmental outcomes. The goal of this aim is to identify the mediators that are significantly associated with maternal opioid exposure and also strongly correlated with child long-term neurodevelopmental outcomes. First, we will fit a multivariable logistic regression model to assess the association between short-term adverse neonatal outcomes and in-utero opioid exposure after adjusting for baseline potential confounding factors. Second, parametric and non-parametric correlations will be assessed for long-term neurodevelopmental outcomes and short-term adverse neonatal outcomes that are significantly related to in-utero opioid exposure. Third, a mediating risk scores will be calculated based on all selected mediators.
Specific Aim 2 : To formulate and estimate a Bayesian mediation model for the long-term neonatal neurodevelopmental outcome First, we will formulate a Bayesian mediation analysis model. The specification of a Bayesian mediation model requires the prior distribution elicitation for the unknown parameters, using information from previous studies when available, and a sampling distribution for the response or mediation variable. The choice of default priors allows for comparison with frequentist methods. Second, Markov Chain Monte Carlo methods (MCMC) will be applied to estimate Bayesian models. Posterior distributions will be obtained for all the parameters of interest, in particular for the effect of maternal opioid exposure during pregnancy. Posterior distribution analysis allows for the extraction of summary statistics of interest, posterior means, medians, and credible intervals. Robustness of results will be assessed for different prior distribution choices. Outcome: This work will significantly impact the field of opioid safety in pregnancy by accurately quantifying the association between perinatal exposure to prescription opioids with long term neurodevelopment and educational status in children. Project Summary/Abstract
The rapid increase in the incidence of opioid-related overdoses and deaths has become a major public health threat in the United States. Understanding how opioid exposure during pregnancy impacts infant health will improve drug safety and help us to better control opioid use during pregnancy. We introduce Bayesian Mediation Analysis to drug safety studies to help determine the role of perinatal opioid exposures on neonatal development and provide evidences for improved perinatal care.
