Initiation of Atenolol versus Methyldopa During Pregnancy and the Risk of Intrauterine Growth Restriction/small for Gestational Age

Friday, August 26, 2022

2:30 PM – 2:45 PM CEST

Location: C1M2

Publication Number: 65

Background: Beta blockers are commonly used in pregnancy to treat hypertensive disorders. However, atenolol use has been associated with intrauterine growth restriction/small for gestational age (IUGR/SGA) in the literature, which is included in the product label. It is possible that the observed association is due to confounding.

Objectives: Our study objective was therefore to estimate the effect of atenolol initiation in pregnancy on IUGR/SGA, using an active comparator design with bias analyses.

Methods: We used a mother-infant linked cohort in the Medicaid Analytic eXtract 2000-2014, including mothers 12-55 years continuously enrolled from 3 months before pregnancy start to 1 month after delivery, and infants enrolled for ≥3 months after birth.
Atenolol (exposure) and methyldopa (comparator) initiators were defined as mothers whose first antihypertensive prescription in pregnancy was for atenolol or methyldopa, with no antihypertensive use from 3 months before pregnancy start until that first prescription (index date). IUGR/SGA was defined via a validated algorithm (PPV: 0.92, 95% CI: 0.82, 0.97) between delivery and 30 days thereafter. We estimated absolute risks, and relative risks (RR) with 95% CIs using a generalized linear model. A propensity score (PS) was estimated based on demographics, indications, obstetrical/comorbid conditions, other medications, and healthcare utilization markers assessed from 90 days before pregnancy start until the index date. Exposure groups were matched 1:1 based on the index date ±14 days and the PS using a caliper of 0.05. In sensitivity analyses, we required ≥ 2 fills to define exposure. We used probabilistic bias analysis to assess the impact of outcome misclassification, and the rule-out approach to assess the impact of unmeasured confounders (e.g., obesity and tobacco use).

Results: We identified 1,115 atenolol and 9,311 methyldopa initiators. The absolute risk of IUGR/SGA was 5.1% in the atenolol group and 4.2% in the methyldopa group, corresponding to a crude RR of 1.22 (95% CI: 0.93 — 1.60). After matching (N= 849 per group), the RR was 1.24 (95% CI: 0.79 — 1.95). Requiring 2 fills resulted in a stronger adjusted RR of 1.67 (95% CI: 0.83 — 3.35). Accounting for outcome misclassification showed a slightly higher bias-adjusted result (RR = 1.34; 95% CI: 0.77 — 2.43). Strong unmeasured confounders would be required to fully explain the observed point estimate.

Conclusions: A 24% increase in risk of IUGR/SGA was observed with atenolol exposure compared to methyldopa exposure, though this effect was estimated imprecisely, and the confidence interval includes the null. Based on sensitivity analyses and the upper limit of the 95% CI, a two- to three-fold increase in risk cannot be excluded.

Presenting Author(s)

BB

Brian Bateman

BWH Div of Pharmacoepidemiology and Pharmacoeconomics
Concord, Massachusetts, United States

Slides

Co-Author(s)

Yanmin Zhu, MS, PhD

Instructor in Medicine
Brigham and Women's Hospital/Harvard Medical School
Boston, Massachusetts, United States
Krista F. Huybrechts, MS, PhD, FISPE

Brigham and Women's Hospital, Harvard Medical School
Boston, Massachusetts, United States
Sonia Hernandez-Diaz, MD, MPH, FISPE

Professor of Epidemiology
Harvard School of Public Health
Boston, Massachusetts, United States
LT

Lockwood Taylor

Division of Epidemiology, Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, United States Food and Drug Administration
Austin, Texas, United States
RO

Rita Ouellet-Hellstrom

Division of Epidemiology, Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, United States Food and Drug Administration, United States
YM

Yong Ma

Lead Mathematical Statistician
Office of Biostatistics, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, United States
YQ

Yandong Qiang, MD, PhD

US Food and Drug Administration
Silver Spring, Maryland, United States
Jenny Sun

Pfizer, Inc. Worldwide Medical and Safety
New York, New York, United States
Loreen Straub, MD MS

Research Fellow
Brigham and Women's Hospital/Harvard Medical School
Cambridge, Massachusetts, United States
Elizabeth A. Suarez

BWH Div of Pharmacoepidemiology and Pharmacoeconomics
Boston, Massachusetts, United States
SV

Seanna Vine

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA, United States
WH

Wei Hua, MSc, MHS, MD, PhD

Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, United States