Our objective was to estimate the association between methadone and neonatal abstinence syndrome compared with buprenorphine using a probabilistic bias analysis to account for unmeasured confounding by severity of addiction.
We used a cohort of live-born infants exposed in utero to methadone or buprenorphine for maternal opioid maintenance therapy at Magee-Womens Hospital in Pittsburgh, PA from 2013–2015 (n=716). We determined exposure and outcome status using pharmacy billing claims. We used log-binomial regression models to assess association of treatment with neonatal abstinence syndrome after adjusting for parity, maternal race, age, delivery year, employment, hepatitis c, smoking, marital, and insurance status. We implemented probabilistic bias analysis, informed by an internal validation study, to assess the impact of unmeasured confounding by severity of addiction.
Infants exposed to methadone in utero were more likely to experience neonatal abstinence syndrome compared with those exposed to buprenorphine [RR: 1.3, 95% CI: 1.2, 1.5]. After adjustment, infants exposed to methadone were more likely (adjusted RR 1.3, 95% CI: 1.1, 1.5) than infants exposed to buprenorphine to have the syndrome. In the validation cohort (n=200), severe addiction was more common in methadone- versus buprenorphine-exposed deliveries (77% vs. 32%). However, adjustment for severe addiction in the bias analysis only slightly attenuated the association (RR 1.2, 95% CI: 1.0, 1.4), supporting conventional analysis.
Methadone is associated with increased risk of neonatal abstinence syndrome compared with buprenorphine in infants exposed in utero. This association is subject to minimal bias due to unmeasured confounding by severity of addiction.
Conflicts of Interest: The authors report no conflicts of interest
Sources of Funding: This work was supported, in part, by Grant # HD047905 from the NICHD and Obstetric-Fetal Pharmacology Research Center. Lara S. Lemon is also a Ruth Kirschstein T-32 grant recipient. Robert W. Platt holds the Albert Boehringer I Chair at McGill University, and a Chercheur-national (National Scholar) award from the Fonds de Recherche du Québec – Santé.
The statistical code is available from Dr. Lemon upon request; authors must obtain permission from our Institutional Review Board to analyze the data directly.
Acknowledgement: Neggin Mokhtari, MD & Allison Serra, MD
* Correspondence: Lara S. Lemon, PhD, PharmD, Department of Clinical Analytics, UPMC , Suite 9030 , Forbes Tower, 3600 Forbes Avenue, Pittsburgh, PA 15213, firstname.lastname@example.org, 412/802-6910 (voice)
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