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BackgroundOpioid agonist therapy is strongly recommended for pregnant persons with opioid use disorder. Buprenorphine may be associated with more favorable neonatal and maternal outcomes than methadone, but existing data are limited.MethodsWe conducted a cohort study involving pregnant persons who were enrolled in public insurance programs in the United States during the period from 2000 through 2018 in which we examined outcomes among those who received buprenorphine as compared with those who received methadone. Exposure to the two medications was assessed in early pregnancy (through gestational week 19), late pregnancy (gestational week 20 through the day before delivery), and the 30 days before delivery. Risk ratios for neonatal and maternal outcomes were adjusted for confounders with the use of propensity-score overlap weights.ResultsThe data source for the study consisted of 2,548,372 pregnancies that ended in live births. In early pregnancy, 10,704 pregnant persons were exposed to buprenorphine and 4387 to methadone. In late pregnancy, 11,272 were exposed to buprenorphine and 5056 to methadone (9976 and 4597, respectively, in the 30 days before delivery). Neonatal abstinence syndrome occurred in 52.0% of the infants who were exposed to buprenorphine in the 30 days before delivery as compared with 69.2% of those exposed to methadone (adjusted relative risk, 0.73; 95% confidence interval [CI], 0.71 to 0.75). Preterm birth occurred in 14.4% of infants exposed to buprenorphine in early pregnancy and in 24.9% of those exposed to methadone (adjusted relative risk, 0.58; 95% CI, 0.53 to 0.62); small size for gestational age in 12.1% and 15.3%, respectively (adjusted relative risk, 0.72; 95% CI, 0.66 to 0.80); and low birth weight in 8.3% and 14.9% (adjusted relative risk, 0.56; 95% CI, 0.50 to 0.63). Delivery by cesarean section occurred in 33.6% of pregnant persons exposed to buprenorphine in early pregnancy and 33.1% of those exposed to methadone (adjusted relative risk, 1.02; 95% CI, 0.97 to 1.08), and severe maternal complications developed in 3.3% and 3.5%, respectively (adjusted relative risk, 0.91; 95% CI, 0.74 to 1.13). Results of exposure in late pregnancy were consistent with results of exposure in early pregnancy.ConclusionsThe use of buprenorphine in pregnancy was associated with a lower risk of adverse neonatal outcomes than methadone use; however, the risk of adverse maternal outcomes was similar among persons who received buprenorphine and those who received methadone. (Funded by the National Institute on Drug Abuse.).

There is a dearth of safety data on maternal outcomes after perinatal medication exposure. Data-mining for unexpected adverse event occurrence in existing datasets is a potentially useful approach. One method, the Poisson tree-based scan statistic (TBSS), assumes that the expected outcome counts, based on incidence of outcomes in the control group, are estimated without error. This assumption may be difficult to satisfy with a small control group. Our simulation study evaluated the effect of imprecise incidence proportions from the control group on TBSS' ability to identify maternal outcomes in pregnancy research. We simulated base case analyses with "true" expected incidence proportions and compared these with imprecise incidence proportions derived from sparse control samples. We varied parameters that have an impact on type I error and statistical power (exposure group size, outcome's incidence proportion, and effect size). We found that imprecise incidence proportions generated by a small control group resulted in inaccurate alerting, inflation of type I error, and removal of very rare outcomes for TBSS analysis due to "zero" background counts. Ideally, the control size should be at least several times larger than the exposure size to limit the number of false positive alerts and retain statistical power for true alerts. This article is part of a Special Collection on Pharmacoepidemiology. [ABSTRACT FROM AUTHOR]

Key Points: Question: Does prenatal exposure to the combination of buprenorphine and naloxone compared with buprenorphine alone increase the risk of adverse neonatal and maternal outcomes? Findings: This observational study noted similar and, in some instances, more favorable neonatal and maternal outcomes for pregnancies exposed to buprenorphine combined with naloxone compared with buprenorphine alone. Meaning: The findings demonstrate comparative safety for the combination of buprenorphine with naloxone for the outcomes considered, supporting both formulations as reasonable options for treating opioid use disorder during pregnancy. Importance: Buprenorphine combined with naloxone is commonly used to treat opioid use disorders outside of pregnancy. In pregnancy, buprenorphine alone is generally recommended because of limited perinatal safety data on the combination product. Objective: To compare perinatal outcomes following prenatal exposure to buprenorphine with naloxone vs buprenorphine alone. Design, Settings, and Participants: Population-based cohort study using health care utilization data from Medicaid-insured beneficiaries in the US from 2000 to 2018. The cohort was restricted to pregnant individuals linked to their liveborn infants, with maternal Medicaid enrollment from 3 months before pregnancy to 1 month after delivery and infant enrollment for the first 3 months after birth, unless they died sooner. Exposure: Use of buprenorphine with naloxone vs buprenorphine alone during the first trimester based on outpatient dispensings. Main Outcomes and Measures: Outcomes included major congenital malformations, low birth weight, neonatal abstinence syndrome, neonatal intensive care unit admission, preterm birth, respiratory symptoms, small for gestational age, cesarean delivery, and maternal morbidity. Confounder-adjusted risk ratios were calculated using propensity score overlap weights. Results: This study identified 3369 pregnant individuals exposed to buprenorphine with naloxone during the first trimester (mean [SD] age, 28.8 [4.6] years) and 5326 exposed to buprenorphine alone or who switched from the combination to buprenorphine alone by the end of the first trimester (mean [SD] age, 28.3 [4.5] years). When comparing buprenorphine combined with naloxone with buprenorphine alone, a lower risk for neonatal abstinence syndrome (absolute risk, 37.4% vs 55.8%; weighted relative risk, 0.77 [95% CI, 0.70-0.84]) and a modestly lower risk for neonatal intensive care unit admission (absolute risk, 30.6% vs 34.9%; weighted relative risk, 0.91 [95% CI, 0.85-0.98]) and small for gestational age (absolute risk, 10.0% vs 12.4%; weighted relative risk, 0.86 [95% CI, 0.75-0.98]) was observed. For maternal morbidity, the comparative rates were 2.6% vs 2.9%, respectively, and the weighted relative risk was 0.90 (95% CI, 0.68-1.19). No differences were observed with respect to major congenital malformations overall, low birth weight, preterm birth, respiratory symptoms, or cesarean delivery. Results were consistent across sensitivity analyses. Conclusions and Relevance: There were similar and, in some instances, more favorable neonatal and maternal outcomes for pregnancies exposed to buprenorphine combined with naloxone compared with buprenorphine alone. For the outcomes assessed, compared with buprenorphine alone, buprenorphine with naloxone during pregnancy appears to be a safe treatment option. This supports the view that both formulations are reasonable options for the treatment of opioid use disorder in pregnancy, affirming flexibility in collaborative treatment decision-making. This population-based cohort study uses health care utilization data for pregnant individuals with opioid use disorder to compare neonatal and maternal outcomes following prenatal exposure to buprenorphine combined with naloxone vs buprenorphine alone. [ABSTRACT FROM AUTHOR]

Epidemiologists spend a great deal of time on confounding in our teaching, in our methods development, and in our assessment of study results. This may give the impression that uncontrolled confounding is the biggest problem observational epidemiology faces, when in fact, other sources of bias such as selection bias, measurement error, missing data, and misalignment of zero time may often (especially if they are all present in a single study) lead to a stronger deviation from the truth. Compared with the amount of time we spend teaching how to address confounding in data analysis, we spend relatively little time teaching methods for simulating confounding (and other sources of bias) to learn their impact and develop plans to mitigate or quantify the bias. Here we review the accompanying paper by Desai et al (Am J Epidemiol. 2024;193(11):1600-1608), which uses simulation methods to quantify the impact of an unmeasured confounder when it is completely missing or when a proxy of the confounder is measured. We discuss how we can use simulations of sources of bias to ensure that we generate better and more valid study estimates, and we discuss the importance of simulating realistic datasets with plausible bias structures to guide data collection. This article is part of a Special Collection on Pharmacoepidemiology. [ABSTRACT FROM AUTHOR]

Purpose: The US Food and Drug Administration established the Sentinel System to monitor the safety of medical products. A component of this system includes parameterizable analytic tools to identify mother‐infant pairs and evaluate infant outcomes to enable the routine monitoring of the utilization and safety of drugs used in pregnancy. We assessed the feasibility of using the data and tools in the Sentinel System by assessing a known association between topiramate use during pregnancy and oral clefts in the infant. Methods: We identified mother‐infant pairs using the mother‐infant linkage table from six data partners contributing to the Sentinel Distributed Database from January 1, 2000, to September 30, 2015. We compared mother‐infant pairs with first‐trimester exposure to topiramate to mother‐infant pairs that were topiramate‐unexposed or lamotrigine‐exposed and used a validated algorithm to identify oral clefts in the infant. We estimated adjusted risk ratios through propensity score stratification. Results: There were 2007 topiramate‐exposed and 1 066 086 unexposed mother‐infant pairs in the main comparison. In the active‐comparator analysis, there were 1996 topiramate‐exposed and 2859 lamotrigine‐exposed mother‐infant pairs. After propensity score stratification, the odds ratio for oral clefts was 2.92 (95% CI: 1.43, 5.93) comparing the topiramate‐exposed to unexposed groups and 2.72 (95% CI: 0.75, 9.93) comparing the topiramate‐exposed to lamotrigine‐exposed groups. Conclusions: We found an increased risk of oral clefts after topiramate exposure in the first trimester in the Sentinel database. These results are similar to prior published observational study results and demonstrate the ability of Sentinel's data and analytic tools to assess medical product safety in cohorts of mother‐infant pairs in a timely manner. [ABSTRACT FROM AUTHOR]

Purpose: It is a priority of the US Food and Drug Administration (FDA) to monitor the safety of medications used during pregnancy. Pregnancy exposure registries and cohort studies utilizing electronic health record data are primary sources of information but are limited by small sample sizes and limited outcome assessment. TreeScan™, a statistical data mining tool, can be applied within the FDA Sentinel System to simultaneously identify multiple potential adverse neonatal and infant outcomes after maternal medication exposure. Methods: We implemented TreeScan using the Sentinel analytic tools in a cohort of linked live birth deliveries and infants nested in the IBM MarketScan® Research Database. As a case study, we compared first trimester fluoroquinolone use and cephalosporin use. We used the Bernoulli and Poisson TreeScan statistics with compatible propensity score‐based study designs for confounding control (matching and stratification) and used multiple propensity score models with various strategies for confounding control to inform best practices. We developed a hierarchical outcome tree including major congenital malformations and outcomes of gestational length and birth weight. Results: A total of 1791 fluoroquinolone‐exposed and 8739 cephalosporin‐exposed mother‐infant pairs were eligible for analysis. Both TreeScan analysis methods resulted in single alerts that were deemed to be due to uncontrolled confounding or otherwise not warranting follow‐up. Conclusions: In this implementation of TreeScan using Sentinel analytic tools, we did not observe any new safety signals for fluoroquinolone use in the first trimester. TreeScan, with tailored or high‐dimensional propensity scores for confounding control, is a valuable tool in addition to current safety surveillance methods for medications used during pregnancy. [ABSTRACT FROM AUTHOR]

Yucatan is a region with a high impact of water contamination since it has a karst type soil favoring contaminants entry into the phreatic level, the only source of freshwater in the area. However, no studies report pesticides in water for human consumption or the risk it represents. The objective of this study was to detect and measure pesticide concentrations in domestic tap water to estimate the risk (carcinogenic and non-carcinogenic) to health. A non-probabilistic sampling was applied of 48 tap water sources, and then pesticide detection with solid-phase extraction gas chromatography coupled to the electron capture and flame photometric detectors allowed the estimation of risk through hazard ratios. The present results suggest that aldrin, heptachlor, and β-BHC residues in domestic tap water from Ticul, Yucatan, pose a risk to children's health, particularly for potential carcinogenic risks. [ABSTRACT FROM AUTHOR]

Purpose: To validate healthcare claim‐based algorithms for neurodevelopmental disorders (NDD) in children using medical records as the reference. Methods: Using a clinical data warehouse of patients receiving outpatient or inpatient care at two hospitals in Boston, we identified children (≤14 years between 2010 and 2014) with at least one of the following NDDs according to claims‐based algorithms: autism spectrum disorder/pervasive developmental disorder (ASD), attention deficit disorder/other hyperkinetic syndromes of childhood (ADHD), learning disability, speech/language disorder, developmental coordination disorder (DCD), intellectual disability, and behavioral disorder. Fifty cases per outcome were randomly sampled and their medical records were independently reviewed by two physicians to adjudicate the outcome presence. Positive predictive values (PPVs) and 95% confidence intervals (CIs) were calculated. Results: PPVs were 94% (95% CI, 83%–99%) for ASD, 88% (76%–95%) for ADHD, 98% (89%–100%) for learning disability, 98% (89%–100%) for speech/language disorder, 82% (69%–91%) for intellectual disability, and 92% (81%–98%) for behavioral disorder. A total of 19 of the 50 algorithm‐based cases of DCD were confirmed as severe coordination disorders with functional impairment, with a PPV of 38% (25%–53%). Among the 31 false‐positive cases of DCD were 7 children with coordination deficits that did not persist throughout childhood, 7 with visual‐motor integration deficits, 12 with coordination issues due to an underlying medical condition and 5 with ADHD and at least one other severe NDD. Conclusions: PPVs were generally high (range: 82%–98%), suggesting that claims‐based algorithms can be used to study NDDs. For DCD, additional criteria are needed to improve the classification of true cases. [ABSTRACT FROM AUTHOR]