Combining adverse pregnancy and perinatal outcomes for women exposed to antiepileptic drugs during pregnancy, using a latent trait model

Xuerong Wen,Joseph A Delaney,Rich Segal,Jeffrey Roth,Abraham Hartzema,Kimford J Meador,Xuefeng Liu,Robert Egerman,Babette Brumback

doi:10.1186/s12884-016-1190-7

Abstract

BackgroundApplication of latent variable models in medical research are becoming increasingly popular. A latent trait model is developed to combine rare birth defect outcomes in an index of infant morbidity.MethodsThis study employed four statewide, retrospective 10-year data sources (1999 to 2009). The study cohort consisted of all female Florida Medicaid enrollees who delivered a live singleton infant during study period. Drug exposure was defined as any exposure to Antiepileptic drugs (AEDs) during pregnancy. Mothers with no AED exposure served as the AED unexposed group for comparison. Four adverse outcomes, birth defect (BD), abnormal condition of new born (ACNB), low birth weight (LBW), and pregnancy and obstetrical complication (PCOC), were examined and combined using a latent trait model to generate an overall severity index. Unidimentionality, local independence, internal homogeneity, and construct validity were evaluated for the combined outcome.ResultsThe study cohort consisted of 3183 mother-infant pairs in total AED group, 226 in the valproate only subgroup, and 43,956 in the AED unexposed group. Compared to AED unexposed group, the rate of BD was higher in both the total AED group (12.8% vs. 10.5%, P < .0001), and the valproate only subgroup (19.6% vs. 10.5%, P < .0001). The combined outcome was significantly correlated with the length of hospital stay during delivery in both the total AED group (Rho = 0.24, P < .0001) and the valproate only subgroup (Rho = 0.16, P = .01). The mean score for the combined outcome in the total AED group was significantly higher (2.04 ± 0.02 vs. 1.88 ± 0.01, P < .0001) than AED unexposed group, whereas the valproate only subgroup was not.ConclusionsLatent trait modeling can be an effective tool for combining adverse pregnancy and perinatal outcomes to assess prenatal exposure to AED, but evaluation of the selected components is essential to ensure the validity of the combined outcome.

Highlights

Application of latent variable models in medical research are becoming increasingly popular
Component outcomes We investigated four adverse pregnancy and infant outcomes: birth defect (BD), abnormal condition of new born (ACNB), low birth weight (LBW), and pregnancy and obstetrical complication (PCOC) from multiple data sources
After applying all inclusion and exclusion criteria, the final study cohort consisted of 3183 mother-infant pairs in the Antiepileptic Drugs (AED) exposure group, 226 mother-infant pairs in the valproate exposure subgroup, and 43,956 motherinfant pairs in the AED unexposed group

Summary

Introduction

Application of latent variable models in medical research are becoming increasingly popular. A latent variable model in a latent trait setting was developed for this study to combine individual BD outcomes and generate an infant morbidity index [11]. This model combines four infant morbidity outcomes and generates a continuous index representing the infant’s propensity for morbidity [11]. Application of this model to combine rare adverse pregnancy and perinatal outcomes in drug safety studies may increase statistical power and improve efficiency of studies investigating low prevalence sequelae

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