Background: Our goal was to develop an approach that can systematically identify potential associations between medication prescribed in pregnancy and spontaneous preterm birth (sPTB) by mining large administrative "claims" databases containing hundreds of medications. One such association that we illustrate emerged with antiviral medications used for herpes treatment.
Methods: IBM MarketScan® databases (2007-2016) were used. A pregnancy cohort was established using International Classification of Diseases (ICD-9/10) codes. Multiple hypothesis testing and the Benjamini-Hochberg procedure that limited false discovery rate at 5% revealed, among 863 medications, five that showed odds ratios (ORs) <1. The statistically strongest was an association between antivirals and sPTB that we illustrate as a real example of our approach, specifically for treatment of genital herpes (GH). Three groups of women were identified based on diagnosis of GH and treatment during the first 36 weeks of pregnancy: (a) GH without treatment; (b) GH treated with antivirals; (c) no GH or treatment.
Results: We identified 2,538,255 deliveries. 0.98% women had a diagnosis of GH. Among them, 60.0% received antiviral treatment. Women with treated GH had OR < 1, (OR [95% CI] = 0.91 [0.85, 0.98]). In contrast, women with untreated GH had a small increased risk of sPTB (OR [95% CI] =1.22 [1.14, 1.32]).
Conclusions: Data-driven approaches can effectively generate new hypotheses on associations between medications and sPTB. This analysis led us to examine the association with GH treatment. While unknown confounders may impact these findings, our results indicate that women with untreated GH have a modest increased risk of sPTB.
Keywords: administrative claims databases; data mining; genital herpes; multiple hypothesis testing; preterm birth.
© 2019 Wiley Periodicals, Inc.