Bayesian Mediation Analysis for Neonatal Neurodevelopmental Outcomes in Pregnancy with Opioid Exposure
Bayesian Mediation Analysis for Neonatal Neurodevelopmental Outcomes in Pregnancy with Opioid Exposure
批准号:
10176650
负责人:
Xuerong Wen
金额:
$25.67万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-02-01 至 2022-01-31
关键词:
6 year oldAlcoholsAnimalsAnxietyAttention deficit hyperactivity disorderAwardBayesian MethodBayesian ModelingBehavioralBirth CertificatesChildChild DevelopmentChildhoodClassificationClinicalCognitiveCongenital AbnormalityDataData AnalysesData SetData SourcesDetectionDevelopmentDevelopmental Delay DisordersEducational AssessmentEducational StatusEnsureExposure toFetal safetyFundingGoalsHealthIncidenceInfant HealthKnowledgeLinkLogistic RegressionsLow Birth Weight InfantMarkov chain Monte Carlo methodologyMaternal ExposureMediatingMediationMediator of activation proteinMedicalMental DepressionMethodsMinorModelingMothersNeonatalNeonatal Abstinence SyndromeNeurologistNewborn InfantOpioidOutcomeOutcome StudyPain managementParentsPathway interactionsPerformancePerinatalPerinatal CarePerinatal ExposurePharmaceutical PreparationsPregnancyPregnant WomenPublic HealthRecordsResearchResearch DesignResearch PersonnelResourcesRiskRoleSafetySample SizeSamplingSignal TransductionSocial SciencesStatistical Data InterpretationStatistical ModelsStructural ModelsTestingTimeUnited StatesWorkadverse outcomeadverse pregnancy outcomeautism spectrum disorderbaseclinically relevantepidemiology studyexperiencefetalfetal opioid exposureflexibilityfollow-upimprovedin uterointerestkindergartenmalformationmaternal opioid usemedication safetymultilevel analysisneonatal outcomeneurobehavioralneurodevelopmentneuron apoptosisobstetric outcomesoffspringopioid exposureopioid overdoseopioid useopioid use in pregnancyoverdose deathprenatal exposureprescription opioidresponsesafety studyscreeningskillsstatisticsthird gradetool
中文摘要
联系PD/PI:温雪蓉
英文摘要
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
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DOI:
10.1007/s40264-021-01080-0
发表时间:
2021-08
期刊:
Drug safety
影响因子:
4.2
作者:
[Wen X, Lawal OD, Belviso N, Matson KL, Wang S, Quilliam BJ, Meador KJ]
通讯作者:
Meador KJ
DOI:
10.1002/pst.2225
发表时间:
2022-11
期刊:
PHARMACEUTICAL STATISTICS
影响因子:
1.5
作者:
[Wang, Shuang, Puggioni, Gavino, Wen, Xuerong]
通讯作者:
Wen, Xuerong
DOI:
10.1001/jamanetworkopen.2021.5708
发表时间:
2021-04-01
期刊:
JAMA network open
影响因子:
13.8
作者:
[Wen X, Belviso N, Murray E, Lewkowitz AK, Ward KE, Meador KJ]
通讯作者:
Meador KJ
DOI:
10.1007/s40264-021-01115-6
发表时间:
2021-12
期刊:
Drug safety
影响因子:
4.2
作者:
[Wen X, Wang S, Lewkowitz AK, Ward KE, Brousseau EC, Meador KJ]
通讯作者:
Meador KJ
海外基金