Drug Safety In Pregnancy Research Articles

Management of Pregnant Women with Atrial Septal Defect and Pulmonary Hypertension: A Case Report

Background: Pulmonary Hypertension (PH) is a condition where there is an increase in Pulmonary Vascular Resistance (PVR) and an increase in the mean Pulmonary Arterial Pressure (mPAP) to more than 20 mmHg. PH can occur in someone with Congenital Heart Disease (CHD). PH conditions can aggravate pregnancy in women with CHD. Women with PH are recommended not to undergo pregnancy. However, it is possible for women with CHD with PH conditions to undergo pregnancy. In these conditions, optimizing PH therapy is essential so that pregnant women with PH do not experience a worsening of the condition and can carry out their pregnancy well until delivery. Case presentation: A 38-year-old female patient with a history of Atrial Septal Defect-Pulmonary Hypertension came for common control to the cardiac clinic with the pregnancy condition of her 4th child, who was just discovered when she was six months pregnant. Since giving birth to her third child, the patient began complaining of being quickly tired when doing activities accompanied by swollen legs that disappeared with rest. The patient went to a cardiologist for an echocardiography examination and was diagnosed with Atrial Septal Defect (ASD)-Pulmonary Hypertension (PH). Since then, the patient has been routinely treated by a cardiologist with Pulmonary Hypertension drugs, including Phospodiesterase5 (PDE5) inhibitors (Sildenafil) and Prostacyclin Analogue (Dorner). The patient had done Transesophageal Echocardiography (TEE) with the results of ASD secundum suitable for closure by the device. Patients with Right Heart Catheterization (RHC) results, ASD secundum with PH High Flow High Resistance reactive to Vasoreactivity Test. Since the patient was found to be pregnant, the patient continued to use Sildenafil and discontinued the use of Dorner. The patient then continued treatment in a multidisciplinary team. Conclusion: Management of pregnant women with CHD and PH is essential because the condition of PH itself further aggravates the condition of pregnancy. Medical management for PH in pregnant women follows the guidelines for the safety of drugs in pregnancy so that the choice of therapy is crucially related to the goal of treatment to control the PH condition in the patient but still pay attention to safety in pregnancy conditions. Keyword: Congenital Heart Disease, Phosphodiesterase-5 (PDE-5)- Inhibitor, Prostacyclin Analogue, Pulmonary Hypertension.

Dermatologic Drug Safety in Pregnancy

In 2014, the US FDA removed the Pregnancy Category Drug lettering system and enacted the “Pregnancy and Lactation Label Ruling.” This ruling required drug products to contain contact information for drug-specific exposure pregnancy registries, narrative-style sections summarizing the known effect of pregnancy, lactation counseling data, and data describing risks for females and males of reproductive potential. This new ruling has added more dialogue and discussion to the patient-provider decision-making process and equires clinicians to provide more individualized counseling based on the current medical literature. This article summarizes the recent evidence for the safety of the most common dermatological therapies for pregnant and lactating women.

Increasing use of newer antiseizure medication during pregnancy: An observational study with special focus on lacosamide

IntroductionEpilepsy is a common neurological disease requiring long-term therapy also during pregnancy. Most studies on pregnancy outcomes in women with epilepsy are based on antiseizure medication (ASM) in monotherapy. However, about 20–30% of epilepsy patients require polytherapy and newer ASMs are an option, when seizure control is not achieved with first line ASMs. MethodsObservational study evaluating the use of newer ASMs with marketing authorization since 2005 reported to the Embryotox Center of Clinical Teratology and Drug Safety in Pregnancy between 2004 and 2019. In addition, course and outcome of lacosamide exposed pregnancies were analysed. ResultsOur study confirms the increasing use of newer ASMs also in pregnant women. This is especially true for lacosamide, eslicarbazepine and brivaracetam with rising numbers of exposed pregnancies soon after marketing authorization. Analysis of 55 prospectively and 10 retrospectively ascertained lacosamide exposed pregnancies does not indicate increased risks of major birth defects or spontaneous abortion. However, bradycardia observed in 3 neonates might be related to prenatal lacosamide exposure. ConclusionAvailable data do not support the assumption of lacosamide being a major teratogen. The increasing use of newer ASMs during pregnancy underscores the need for more studies to guide preconception counselling, especially for lacosamide, eslicarbazepine and brivaracetam.

Investigating drug safety in pregnancy based on the German Pharmacoepidemiological Research Database (GePaRD): A proof-of-concept analysis on the association between valproate and spina bifida.

Large health-care databases are increasingly used for research on drug utilization and safety in pregnancy. For the German Pharmacoepidemiological Research Database (GePaRD), covering ~20% of the German population, algorithms have been developed to identify pregnancies, to estimate their date of onset and to link mothers to their babies. Using this methodology, we aimed to conduct a proof-of-concept analysis on the known association between valproate (VPA) exposure in early pregnancy and spina bifida in the exposed child. We identified all pregnancies in GePaRD between 2006 and 2016 in women aged 12 to 50 years. To each VPA dispensation of these women, an exposure period was assigned, based on the dispensation date and the number of defined daily doses in the dispensed package. A pregnancy was classified as exposed to VPA in the critical time window if this exposure period overlapped with the first 55 days of pregnancy. Risk ratios were calculated for spina bifida in live births and induced abortions comparing VPA-exposed ones to all pregnancies. Overall, we identified 1 271 384 pregnancies fulfilling the inclusion criteria. Of these, 668 pregnancies (0.053%) were classified as exposed to VPA in the critical time window regarding spina bifida. An induced abortion accompanied by a diagnosis of spina bifida was observed in one of the VPA-exposed pregnancies (0.15%) and in 154 of all pregnancies (0.012%), yielding a risk ratio of 12.4 (95% confidence interval [CI]: 1.7-88.2). Out of 775 875 pregnancies ending in a live birth, 366 (0.047%) were classified as VPA exposed. A diagnosis of spina bifida was coded in 3 of 366 VPA-exposed live births (0.82%) and in 260 of all live births (0.03%), yielding a relative risk of 24.5 (95% CI: 7.9-76.0). Our proof-of-concept analysis based on GePaRD showed a strong association between intrauterine exposure to VPA and occurrence of spina bifida. The results are plausible and consistent with the literature, supporting the suitability of GePaRD and the developed algorithms to conduct studies on drug safety in pregnancy.

Monitoring Drug Safety in Pregnancy with Scan Statistics: A Comparison of Two Study Designs.

Traditional surveillance of adverse infant outcomes following maternal medication exposures relies on pregnancy exposure registries, which are often underpowered. We characterize the statistical power of TreeScan, a data mining tool, to identify potential signals in the setting of perinatal medication exposures and infant outcomes. We used empirical data to inform background incidence of major congenital malformations and other birth conditions. Statistical power was calculated using two probability models compatible with TreeScan, Bernoulli and Poisson, while varying the sample size, magnitude of the risk increase, and incidence of a specified outcome. We also simulated larger referent to exposure matching ratios when using the Bernoulli model in the setting of fixed N:1 propensity score matching. Finally, we assessed the impact of outcome misclassification on power. The Poisson model demonstrated greater power to detect signals than the Bernoulli model across all scenarios and suggested a sample size of 4,000 exposed pregnancies is needed to detect a twofold increase in risk of a common outcome (approximately 8 per 1,000) with 85% power. Increasing the fixed matching ratio with the Bernoulli model did not reliably increase power. An outcome definition with high sensitivity is expected to have somewhat greater power to detect signals than an outcome definition with high positive predictive value. Use of the Poisson model with an outcome definition that prioritizes sensitivity may be optimal for signal detection. TreeScan is a viable method for surveillance of adverse infant outcomes following maternal medication use.

Medication history-wide association studies for pharmacovigilance of pregnant patients

BackgroundSystematic exclusion of pregnant people from interventional clinical trials has created a public health emergency for millions of patients through a dearth of robust safety data for common drugs.MethodsWe harnessed an enterprise collection of 2.8 M electronic health records (EHRs) from routine care, leveraging data linkages between mothers and their babies to detect drug safety signals in this population at full scale. Our mixed-methods signal detection approach stimulates new hypotheses for post-marketing surveillance agnostically of both drugs and diseases—by identifying 1,054 drugs historically prescribed to pregnant patients; developing a quantitative, medication history-wide association study; and integrating a qualitative evidence synthesis platform using expert clinician review for integration of biomedical specificity—to test the effects of maternal exposure to diverse drugs on the incidence of neurodevelopmental defects in their children.ResultsWe replicated known teratogenic risks and existing knowledge on drug structure-related teratogenicity; we also highlight 5 common drug classes for which we believe this work warrants updated assessment of their safety.ConclusionHere, we present roots of an agile framework to guide enhanced medication regulations, as well as the ontological and analytical limitations that currently restrict the integration of real-world data into drug safety management during pregnancy. This research is not a replacement for inclusion of pregnant people in prospective clinical studies, but it presents a tractable team science approach to evaluating the utility of EHRs for new regulatory review programs—towards improving the delicate equipoise of accuracy and ethics in assessing drug safety in pregnancy.

Using Twitter Data for Cohort Studies of Drug Safety in Pregnancy: Proof-of-concept With β-Blockers.

BackgroundDespite the fact that medication is taken during more than 90% of pregnancies, the fetal risk for most medications is unknown, and the majority of medications have no data regarding safety in pregnancy.ObjectiveUsing β-blockers as a proof-of-concept, the primary objective of this study was to assess the utility of Twitter data for a cohort study design—in particular, whether we could identify (1) Twitter users who have posted tweets reporting that they took medication during pregnancy and (2) their associated pregnancy outcomes.MethodsWe searched for mentions of β-blockers in 2.75 billion tweets posted by 415,690 users who announced their pregnancy on Twitter. We manually reviewed the matching tweets to first determine if the user actually took the β-blocker mentioned in the tweet. Then, to help determine if the β-blocker was taken during pregnancy, we used the time stamp of the tweet reporting intake and drew upon an automated natural language processing (NLP) tool that estimates the date of the user’s prenatal time period. For users who posted tweets indicating that they took or may have taken the β-blocker during pregnancy, we drew upon additional NLP tools to help identify tweets that report their pregnancy outcomes. Adverse pregnancy outcomes included miscarriage, stillbirth, birth defects, preterm birth (<37 weeks gestation), low birth weight (<5 pounds and 8 ounces at delivery), and neonatal intensive care unit (NICU) admission. Normal pregnancy outcomes included gestational age ≥37 weeks and birth weight ≥5 pounds and 8 ounces.ResultsWe retrieved 5114 tweets, posted by 2339 users, that mention a β-blocker, and manually identified 2332 (45.6%) tweets, posted by 1195 (51.1%) of the users, that self-report taking the β-blocker. We were able to estimate the date of the prenatal time period for 356 pregnancies among 334 (27.9%) of these 1195 users. Among these 356 pregnancies, we identified 257 (72.2%) during which the β-blocker was or may have been taken. We manually verified an adverse pregnancy outcome—preterm birth, NICU admission, low birth weight, birth defects, or miscarriage—for 38 (14.8%) of these 257 pregnancies. We manually verified a gestational age ≥37 weeks for 198 (90.4%) and a birth weight ≥5 pounds and 8 ounces for 50 (22.8%) of the 219 pregnancies for which we did not identify an adverse pregnancy outcome.ConclusionsOur ability to detect pregnancy outcomes for Twitter users who posted tweets reporting that they took or may have taken a β-blocker during pregnancy suggests that Twitter can be a complementary resource for cohort studies of drug safety in pregnancy.

Can non-responding mask or mimic drug effects on pregnancy outcome? Evaluation of case characteristics based on the national Embryotox cohort

Women and their health care provider (HCP) often seek advice for drug safety in pregnancy at Teratology Information Services (TIS). In turn, TIS ask for details of drug exposure and pregnancy outcome. These data constitute a valuable basis for research on prenatal drug risks in many countries. Non-response to follow-up questionnaires, however, may cause biased study results. To assess the potential of non-response bias, this study based on the German Embryotox cohort compares maternal and HCP characteristics of responders and non-responders. Change in loss of follow-up rates over time is investigated using logistic regression. From 2010 until the end of 2020, 48,410 pregnant women and/or their HCP consented to participation in follow-up. Of these, 25.0 % did not return follow-up questionnaires. Loss rates were similar for patients and HCP but increased over time. Participants from semi-dense populated areas had a smaller loss rate (20.4 %) than those from rural (28.4 %) or urban areas (25.6 %). Responding women were older than non-responders, had a lower BMI, a more positive attitude towards pregnancy, a higher educational level, a lower number of previous pregnancies, smoked less, and indicated alcohol consumption more but social drugs less often. Non-response bias cannot be ruled out in studies based on observational data on drug use in pregnancy as those collected by TIS. However, differences between the complete and lost-to follow-up cohort do not suggest a particularly high or low risk profile for one of the cohorts that might substantially confound study results or even mask or mimic potential drug toxicity.

A Bayesian latent class model for predicting gestational age in health administrative data.

Health administrative data are oftentimes of limited use in epidemiological study on drug safety in pregnancy, due to lacking information on gestational age at birth (GAB). Although several studies have proposed algorithms to estimate GAB using claims database, failing to incorporate the unique distributional shape of GAB, can introduce bias in estimates and subsequent modeling. Hence, we develop a Bayesian latent class model to predict GAB. The model employs a mixture of Gaussian distributions with linear covariates within each class. This approach allows modeling heterogeneity in the population by identifying latent subgroups and estimating class-specific regression coefficients. We fit this model in a Bayesian framework conducting posterior computation with Markov Chain Monte Carlo methods. The method is illustrated with a dataset of 10,043 Rhode Island Medicaid mother-child pairs. We found that the three-class and six-class mixture specifications maximized prediction accuracy. Based on our results, Medicaid women were partitioned into three classes, featured by extreme preterm or preterm birth, preterm or" early" term birth, and" late" term birth. Obstetrical complications appeared to pose a significant influence on class-membership. Altogether, compared to traditional linear models our approach shows an advantage in predictive accuracy, because of superior flexibility in modeling a skewed response and population heterogeneity.

Liver injury associated with drug intake during pregnancy.

Drug use during pregnancy is not common. Drug-induced liver injury (DILI) is a potential complication that is rare but can adversely affect both the mother and the fetus. Although many drugs can directly cause hepatotoxicity, idiosyncratic liver injury is common in pregnancy. Underreporting of adverse drug reactions, lack of adequate literature regarding drug safety in pregnancy, and the inherent difficulty in diagnosing DILI during pregnancy make the management of this condition challenging. This review attempts to describe the existing literature regarding DILI in pregnancy, which is mainly in the form of case reports; several studies have looked at the safety of antithyroid drugs, antiretroviral drugs, and paracetamol, which have an indication for use in pregnancy; the relevant data from these studies with regard to DILI has been presented. In addition, the review describes the diagnosis of DILI, grading the disease severity, assessment of causality linking the drug to the adverse event, regulatory guidelines for evaluating the potential of drugs to cause liver injury, efforts to ensure better participation of women in clinical trials and studies in pregnant women population in particular, and the challenges involved in generating adequate research evidence. The establishment of DILI registries in various countries is an encouraging development; however, there is a need for promoting active, spontaneous reporting of adverse events during pregnancy to ensure rapid generation of evidence regarding the safety of a drug in pregnant women.

Medication use among pregnant women at a secondary health institution: utilisation patterns and predictors of quantity.

Despite the lack of adequate studies on the safety of drugs in pregnancy, surprisingly, available evidence shows that pregnant women still take large number of drugs. The study aim was to determine drug utilization pattern and predictors of number of medications used by pregnant women. This was a cross-sectional survey of 369 pregnant women attending a secondary health facility. Data were collected using interviewer-administered questionnaire. Descriptive and inferential statistics using the Chi-Square test were carried out with level of significance set at p<0.05. Three hundred and sixty-nine women were interviewed. Their mean age was 27.7 years (SD± 4.78) and the mean number of pregnancies was 2.46 (SD± 1.34). On average, 2.62 medications were taken, with the lowest being 1 and the highest being 12 different medications during the course of pregnancy. Those who were on more than 2 medications were more likely to be older than 30 years, had lower education and with history of associated medical conditions. All participants were on one form of supplements or the other, nearly half had used antimalarials, 12.8%, 5.8% 2.4% were on antibiotics, anti-hypertensive and anti-retroviral medications respectively. All the medications prescribed were from category A, B, C, N, and none from category D and X. Varieties of medications were used during the course of pregnancy among this population, however, most of these drugs were still within safety profile.

Warning of Immortal Time Bias When Studying Drug Safety in Pregnancy: Application to Late Use of Antibiotics and Preterm Delivery.

This study aimed to illustrate and account for immortal time bias in pregnancy observational investigations, using the relationship between late use of antibiotics and risk of preterm birth as an example. We conducted a population-based cohort study including 549,082 deliveries between 2007 and 2017 in Lombardy, Italy. We evaluated the risk of preterm births, low birth weight, small for gestational age, and low Apgar score associated with antibiotic dispensing during the third trimester of pregnancy. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CI) of the outcomes, considering the use of antibiotics as time-fixed (with biased classification of exposure person-time) and time-varying (with proper classification of exposure person-time) exposure. There were 23,638 (4.3%) premature deliveries. There was no association between time-fixed exposure to antibiotics and preterm delivery (adjusted HR 0.96; 95% CI 0.92 to 1.01) but an increased risk of preterm birth when time-varying exposure to antibiotics was considered (1.27; 1.21 to 1.34). The same trend was found for low birth weight and low Apgar score. Immortal time bias is a common and sneaky trap in observational studies involving exposure in late pregnancy. This bias could be easily avoided with suitable design and analysis.

Estimating the Beginning of Pregnancy in German Claims Data: Development of an Algorithm With a Focus on the Expected Delivery Date.

Background: Estimating the beginning of pregnancy is crucial when studying drug safety in pregnancy, but important information in this regard, such as the last menstrual period (LMP), is generally not recorded in claims databases. The beginning of pregnancy is therefore usually estimated by subtracting a median length of pregnancy from the date of birth. Due to the variability in pregnancy lengths, this might result in non-negligible errors. German claims data may offer the possibility to estimate the beginning of pregnancy more precisely based on the expected delivery date (EDD) which can be coded once or more often during a pregnancy.Purpose: To estimate the beginning of pregnancy in German claims data focusing on the potential of the expected delivery date (EDD).Methods: We included data of all pregnancies in women aged 12–50 years ending in a live birth between 2006 and 2015 identified in the German Pharmacoepidemiological Research Database (GePaRD). We assessed the number of coded EDDs per pregnancy and the concordance if ≥ 2 EDDs were coded. We estimated the beginning of pregnancy by subtracting 280 days from the EDD or the most frequent EDD (in case of discordant EDDs). To examine plausibility, we determined the distribution of pregnancy lengths and assessed whether the gestational age at which prenatal examinations were coded was plausible. For pregnancies without EDD, the beginning was estimated by subtracting the respective observed median lengths of pregnancy for preterm births, term births, and births after due date from the actual dates of birth.Results: In 82.4% of pregnancies, at least one EDD was available (thereof 6.1% with only one EDD and 80.9% with ≥ 2 EDDs that were all concordant). The maximal difference between discordant EDDs was in median 5 days (interquartile range: 3–7 days). Based on the EDD, the median length of pregnancy was 276 days for term births and in 84.7% of pregnancies the second antibody screening test was performed in the recommended interval ± 2 weeks. In pregnancies without EDD the respective proportion was 84.9%.Conclusions: By using the EDD, the beginning of pregnancy can plausibly be estimated in German claims data.

Validation of algorithms to identify adverse perinatal outcomes in the Medicaid Analytic Extract database.

The Medicaid Analytic eXtract (MAX) is a health care utilization database from publicly insured individuals that has been used for studies of drug safety in pregnancy. Claims-based algorithms for defining many important maternal and neonatal outcomes have not been validated. To validate claims-based algorithms for identifying selected pregnancy outcomes in MAX using hospital medical records. The medical records of mothers who delivered between 2000 and 2010 within a single large healthcare system were linked to their claims in MAX. Claims-based algorithms for placental abruption, preeclampsia, postpartum hemorrhage, small for gestational age, and noncardiac congenital malformation were defined. Fifty randomly sampled cases for each outcome identified using these algorithms were selected, and their medical records were independently reviewed by two physicians to confirm the presence of the diagnosis of interest; disagreements were resolved by a third physician reviewer. Positive predictive values (PPVs) and 95% confidence intervals (CIs) of the claims-based algorithms were calculated using medical records as the gold standard. The linked cohort included 10,899 live-birth pregnancies. The PPV was 92% (95% CI, 82%-97%) for placental abruption, 82% (95% CI, 70%-91%) for preeclampsia, 74% (95% CI, 61%-85%) for postpartum hemorrhage, 92% (95% CI, 82%-97%) for small for gestational age, and 86% (95% CI, 74%-94%) for noncardiac congenital malformation. Across the perinatal outcomes considered, PPVs ranged between 74% and 92%. These PPVs can inform bias analyses that correct for outcome misclassification.

Drug Safety in Pregnancy: Review of Study Approaches Requested by Regulatory Agencies

We reviewed postauthorization pregnancy safety studies requested by regulatory agencies to explore which study approaches have been typically requested and to what extent these have changed over time. The most common study approach requested by the US Food and Drug Administration (FDA) is pregnancy exposure registries (observational cohorts with prospective data collection), per the FDA’s Postmarketing Requirements and Commitments (PMR/PMC) database. Since 2017, this requirement has often been paired with a request for a database study (observational study using preexisting electronic health care data), both approaches assessing pregnancy and fetal outcomes. From studies registered in the European Union electronic Register of Post-Authorisation Studies, we observed a similar number of pregnancy exposure registries and database studies, both approaches also assessing pregnancy and fetal outcomes. In requests for drugs approved since 2014, preference appears to have shifted toward studies using preexisting electronic health care databases from multiple countries. Pregnancy exposure registries have been the most commonly requested study approach on drug safety in pregnancy. Recent regulatory requests and activities denote an increasing interest in other approaches.

Brian Bateman, M.D., Recipient of the 2018 James E. Cottrell, M.D., Presidential Scholar Award

Brian Bateman, M.D., Recipient of the 2018 James E. Cottrell, M.D., Presidential Scholar Award

Drug safety in pregnancy-aparticular challenge

Drug safety in pregnancy is of utmost importance because prenatal exposure to the unborn child may result in side effects with life-long consequences. Data on their risks in pregnancy are scarce for many drugs. Furthermore, there is often uncertainty how to translate risk data into practice.This article aims to identify tools to improve data ascertainment on exposed pregnancies and their outcome. Using the example of the German Embryotox institute, it is demonstrated how to disseminate drug safety knowledge to healthcare professionals and patients for clinical decision-making.Observational data are the most important basis for drug risk assessment in pregnancy. Such data are collected by Embryotox through the risk consultation process. Prospective cohort studies with comparison cohorts allow to estimate relative risks for birth defects, pregnancy loss, and other developmental anomalies. Retrospectively ascertained adverse drug reactions contribute to identification of distinct pattern of congenital anomalies.Drugs in pregnancy counselling require risk characterization dependent on the individual clinical setting: recommendation of treatment of choice (comparative risk assessment between effective drugs), individual risk estimation after (inadvertent) exposure, and assessment of causal relationship in cases of congenital anomalies. Combining counselling and protocols of pregnancy outcome after drug exposure is optimal to cost-efficiently ascertain data of high quality.Using acetaminophen, valproic acid, AT1-receptor blockers and retinoids as examples, recent discussions on drug risks in pregnancy and their clinical implications are presented.

Drug safety in pregnancy: Assessment by FDA Safety Rating system and WHO prescribing Indicators

Drug safety in pregnancy: Assessment by FDA Safety Rating system and WHO prescribing Indicators

Drug Safety in Pregnancy

Drug Safety in Pregnancy

Learning the effects of psychotropic drugs during pregnancy using real-world safety data: a paradigm shift toward modern pharmacovigilance

The growing evidence on psychotropic drug safety in pregnancy has been possible thanks to the increasing availability of real-world data, i.e. data not collected in conventional randomised controlled trials. Use of these data is a key to establish psychotropic drug effects on foetal, child, and maternal health. Despite the inherent limitations and pitfalls of observational data, these can still be informative after a critical appraisal of the collective body of evidence has been done. By valuing real-world safety data, and making these a larger part of the regulatory decision-making process, we move toward a modern pregnancy pharmacovigilance. The recent uptake of real-world safety data by health authorities has set the basis for an important paradigm shift, which is integrating such data into drug labelling. The recent safety assessment of sodium valproate in pregnant and childbearing women is probably one of the first examples of modern pregnancy pharmacovigilance.