Administrative Claims Data Versus Augmented Pregnancy Data for the Study of Pharmaceutical Treatments in Pregnancy

Characterizing Fit-for-Purpose Real-World Data: An Assessment of a Mother-Infant Linkage in the Japan Medical Data Center Claims Database

Purpose

Observational postapproval safety studies are needed to inform medication safety during pregnancy. Real-world databases can be valuable for supporting such research, but fitness for regulatory purpose must first be vetted. Here, we demonstrate a fit-for-purpose assessment of the Japan Medical Data Center (JMDC) claims database for pregnancy safety regulatory decision-making.

Patients and Methods

The Duke-Margolis framework considers a database's fitness for regulatory purpose based on relevancy (capacity to answer the research question based on variable availability and a sufficiently sized, representative population) and quality (ability to validly answer the research question based on data completeness and accuracy). To assess these considerations, we examined descriptive characteristics of infants and pregnancies among females ages 12-55 years in the JMDC between January 2005 and March 2022.

Results

For relevancy, we determined that critical data fields (maternal medications, infant major congenital malformations, covariates) are available. Family identification codes permitted linkage of 385,295 total mother-infant pairs, 57% of which were continuously enrolled during pregnancy. The prevalence of specific congenital malformation subcategories and maternal medical conditions were representative of the general population, but preterm births were below expectations (3.6% versus 5.6%) in this population. For quality, our methods are expected to accurately identify the complete set of mothers and infants with a shared health insurance plan. However, validity of gestational age information was limited given the high proportion (60%) of missing live birth delivery codes coupled with suppression of infant birth dates and inaccessibility of disease codes with gestational week information.

Conclusion

The JMDC may be well suited for descriptive studies of pregnant people in Japan (eg, comorbidities, medication usage). More work is needed to identify a method to assign pregnancy onset and delivery dates so that in utero medication exposure windows can be defined more precisely as needed for many regulatory postapproval pregnancy safety studies.

Patients with autoimmune skin diseases are at increased risk of adverse pregnancy outcomes

BACKGROUND

Increased rates of adverse pregnancy outcomes have been reported in association with rheumatologic diseases such as systemic lupus erythematosus, rheumatoid arthritis, dermatomyositis. However, little is known about pregnancy outcomes in patients with autoimmune skin diseases.

OBJECTIVE

This study aimed to determine the frequency of adverse pregnancy outcomes in patients with autoimmune skin diseases. We hypothesized that similar to rheumatic diseases, the rate of adverse pregnancy outcomes in patients with autoimmune skin diseases would be higher than the general population.

STUDY DESIGN

This is a case control study using the TriNetX US Collaborative Network, which is a database of electronic medical records of >95 million patients seen at 57 healthcare organizations in the United States. All pregnant women between the ages of 15 and 44 years who were seen at a healthcare organization between January 1, 2016 and December 31, 2021 were included. Participants with autoimmune skin disease were matched to healthy controls and controls with systemic rheumatologic conditions (systemic lupus erythematosus or rheumatoid arthritis). For both the autoimmune skin disease and healthy control groups, those with systemic rheumatologic condition or hidradenitis suppurativa were excluded. The primary outcomes were adverse pregnancy outcomes defined as spontaneous abortion, gestational hypertension, preeclampsia or eclampsia, gestational diabetes mellitus, intrauterine growth restriction, preterm premature rupture of membranes, preterm birth, and stillbirth. Patients with autoimmune skin diseases and controls were 1:1 propensity score-matched by age, race, ethnicity, comorbidities, obesity, and substance use. For each outcome, odds ratio with a 95% confidence interval was calculated.

RESULTS

A total of 2788 patients with autoimmune skin diseases were matched to 2788 healthy controls. Patients with autoimmune skin diseases were at a higher risk of spontaneous abortions than controls (odds ratio, 1.54; 95% confidence interval, 1.36-1.75; P<.001). Compared with patients with systemic lupus erythematosus, patients with autoimmune skin diseases were at lower risk of having infants with intrauterine growth restriction (odds ratio, 0.59; 95% confidence interval, 0.4-0.87; P=.01), preterm birth (odds ratio, 0.68; 95% confidence interval, 0.47-0.98; P=.04), and stillbirth (odds ratio, 0.50; 95% confidence interval, 0.25-0.97; P=.04). The differences in adverse pregnancy outcomes between patients with autoimmune skin diseases and those with rheumatoid arthritis were not statistically significant.

CONCLUSION

Patients with autoimmune skin diseases are at a higher risk of spontaneous abortions than patients without autoimmune skin diseases. When analyzed by each autoimmune skin disease, patients with cutaneous lupus erythematosus or vitiligo remained at increased risk of spontaneous abortions compared with patients without autoimmune skin diseases. Patients with autoimmune skin diseases have similar risks of adverse pregnancy outcomes as patients with rheumatoid arthritis, but lower risks than patients with systemic lupus erythematosus.

Identifying pregnancy episodes and estimating the last menstrual period using an administrative database in Korea: an application to patients with systemic lupus erythematosus

OBJECTIVES

This study developed an algorithm for identifying pregnancy episodes and estimating the last menstrual period (LMP) in an administrative claims database and applied it to investigate the use of pregnancy-incompatible immunosuppressants among pregnant women with systemic lupus erythematosus (SLE).

METHODS

An algorithm was developed and applied to a nationwide claims database in Korea. Pregnancy episodes were identified using a hierarchy of pregnancy outcomes and clinically plausible periods for subsequent episodes. The LMP was estimated using preterm delivery, sonography, and abortion procedure codes. Otherwise, outcome-specific estimates were applied, assigning a fixed gestational age to the corresponding pregnancy outcome. The algorithm was used to examine the prevalence of pregnancies and utilization of pregnancy-incompatible immunosuppressants (cyclophosphamide [CYC]/mycophenolate mofetil [MMF]/methotrexate [MTX]) and non-steroidal anti-inflammatory drugs (NSAIDs) during pregnancy in SLE patients.

RESULTS

The pregnancy outcomes identified in SLE patients included live births (67%), stillbirths (2%), and abortions (31%). The LMP was mostly estimated with outcome-specific estimates for full-term births (92.3%) and using sonography procedure codes (54.7%) and preterm delivery diagnosis codes (37.9%) for preterm births. The use of CYC/MMF/MTX decreased from 7.6% during preconception to 0.2% at the end of pregnancy. CYC/MMF/MTX use was observed in 3.6% of women within 3 months preconception and 2.5% during 0-7 weeks of pregnancy.

CONCLUSIONS

This study presents the first pregnancy algorithm using a Korean administrative claims database. Although further validation is necessary, this study provides a foundation for evaluating the safety of medications during pregnancy using secondary databases in Korea, especially for rare diseases.

Development and evaluation of an algorithm to link mothers and infants in two US commercial healthcare claims databases for pharmacoepidemiology research

BACKGROUND

Administrative healthcare claims databases are used in drug safety research but are limited for investigating the impacts of prenatal exposures on neonatal and pediatric outcomes without mother-infant pair identification. Further, existing algorithms are not transportable across data sources. We developed a transportable mother-infant linkage algorithm and evaluated it in two, large US commercially insured populations.

METHODS

We used two US commercial health insurance claims databases during the years 2000 to 2021. Mother-infant links were constructed where persons of female sex 12-55 years of age with a pregnancy episode ending in live birth were associated with a person who was 0 years of age at database entry, who shared a common insurance plan ID, had overlapping insurance coverage time, and whose date of birth was within ± 60-days of the mother's pregnancy episode live birth date. We compared the characteristics of linked vs. non-linked mothers and infants to assess similarity.

RESULTS

The algorithm linked 3,477,960 mothers to 4,160,284 infants in the two databases. Linked mothers and linked infants comprised 73.6% of all mothers and 49.1% of all infants, respectively. 94.9% of linked infants' dates of birth were within ± 30-days of the associated mother's pregnancy episode end dates. Characteristics were largely similar in linked vs. non-linked mothers and infants. Differences included that linked mothers were older, had longer pregnancy episodes, and had greater post-pregnancy observation time than mothers with live births who were not linked. Linked infants had less observation time and greater healthcare utilization than non-linked infants.

CONCLUSIONS

We developed a mother-infant linkage algorithm and applied it to two US commercial healthcare claims databases that achieved a high linkage proportion and demonstrated that linked and non-linked mother and infant cohorts were similar. Transparent, reusable algorithms applied to large databases enable large-scale research on exposures during pregnancy and pediatric outcomes with relevance to drug safety. These features suggest studies using this algorithm can produce valid and generalizable evidence to inform clinical, policy, and regulatory decisions.

Validation of case definition algorithms for the ascertainment of congenital anomalies

BACKGROUND

Congenital anomalies (CA) are one of the leading causes of infant mortality and long-term disability. Many jurisdictions rely on health administrative data to monitor these conditions. Case definition algorithms can be used to monitor CA; however, validation of these algorithms is needed to understand the strengths and limitations of the data. This study aimed to validate case definition algorithms used in a CA surveillance system in British Columbia (BC), Canada.

METHODS

A cohort of births between March 2000 and April 2002 in BC was linked to the Health Status Registry (HSR) and the BC Congenital Anomalies Surveillance System (BCCASS) to identify cases and non-cases of specific anomalies within each surveillance system. Measures of algorithm performance were calculated for each CA using the HSR as the reference standard. Agreement between both databases was calculated using kappa coefficient. The modified Standards for Reporting Diagnostic Accuracy guidelines were used to enhance the quality of the study.

RESULTS

Measures of algorithm performance varied by condition. Positive predictive value (PPV) ranged between approximately 73%-100%. Sensitivity was lower than PPV for most conditions. Internal congenital anomalies or conditions not easily identifiable at birth had the lowest sensitivity. Specificity and negative predictive value exceeded 99% for all algorithms.

CONCLUSION

Case definition algorithms may be used to monitor CA at the population level. Accuracy of algorithms is higher for conditions that are easily identified at birth. Jurisdictions with similar administrative data may benefit from using validated case definitions for CA surveillance as this facilitates cross-jurisdictional comparison.

Development and Validation of ICD-10-CM-based Algorithms for Date of Last Menstrual Period, Pregnancy Outcomes, and Infant Outcomes

INTRODUCTION AND OBJECTIVE

Validation studies of algorithms for pregnancy outcomes based on International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes are important for conducting drug safety research using administrative claims databases. To facilitate the conduct of pregnancy safety studies, this exploratory study aimed to develop and validate ICD-10-CM-based claims algorithms for date of last menstrual period (LMP) and pregnancy outcomes using medical records.

METHODS

Using a mother-infant-linked claims database, the study included women with a pregnancy between 2016-2017 and their infants. Claims-based algorithms for LMP date utilized codes for gestational age (Z3A codes). The primary outcomes were major congenital malformations (MCMs) and spontaneous abortion; additional secondary outcomes were also evaluated. Each pregnancy outcome was identified using a claims-based simple algorithm, defined as presence of ≥ 1 claim for the outcome. Positive predictive values (PPV) and 95% confidence intervals (CI) were calculated.

RESULTS

Overall, 586 medical records were sought and 365 (62.3%) were adjudicated, including 125 records each for MCMs and spontaneous abortion. Last menstrual period date was validated among maternal charts procured for pregnancy outcomes and fewer charts were adjudicated for the secondary outcomes. The median difference in days between LMP date based on Z3A codes and adjudicated LMP date was 4.0 (interquartile range: 2.0-10.0). The PPV of the simple algorithm for spontaneous abortion was 84.7% (95% CI 78.3, 91.2). The PPV for the MCM algorithm was < 70%. The algorithms for the secondary outcomes pre-eclampsia, premature delivery, and low birthweight performed well, with PPVs > 70%.

CONCLUSIONS

The ICD-10-CM claims-based algorithm for spontaneous abortion performed well and may be used in pregnancy studies. Further algorithm refinement for MCMs is needed. The algorithms for LMP date and the secondary outcomes would benefit from additional validation in a larger sample.

Prenatal cannabis use disorder and infant hospitalization and death in the first year of life

OBJECTIVE

To determine whether maternal cannabis use disorder is associated with infant hospitalization or death in the first year of life.

METHODS

We queried an administrative birth cohort derived from the hospital discharge database maintained by the California Office of Statewide Health Planning and Development and linked with vital statistics files. We included singleton, live-birth deliveries between 2011 and 2018. Pregnancies with cannabis use disorder were classified from International Classification of Disease codes. Outcomes included infant emergency department visits and hospital admissions identified from health records, and infant deaths identified from death records. Models were adjusted for sociodemographic variables, psychiatric comorbidities and other substance use disorders.

RESULTS

There were 34,544 births (1.0 %) with a cannabis use disorder diagnosis in pregnancy, with increasing prevalence over the study period. The incidence of infant death in the first year of life was greater among those with a maternal cannabis use disorder diagnosis than those without (1.0 % vs 0.4 %; adjusted risk ratio 1.4 95 % CI: 1.2-1.6). When examining specific causes of death, the increased risk estimates were attributable to perinatal conditions and sudden unexpected infant death. After adjustment, there was no increased risk of infant hospitalizations or emergency department visits.

CONCLUSIONS

These findings warrant further investigation into the underlying mechanisms of maternal prenatal CUD on infant outcomes, and add to a rapidly expanding body of literature supporting the need for effective treatment options for pregnant individuals with cannabis use disorders.

Associations Between Late-Onset Preeclampsia and the Use of Calcium-Based Antacids and Proton Pump Inhibitors During Pregnancy: A Prospective Cohort Study

Purpose

Preeclampsia is a leading cause of maternal morbidity and mortality. Calcium-based antacids and proton pump inhibitors (PPIs) are commonly used during pregnancy to treat symptoms of gastroesophageal reflux disease. Both have been hypothesized to reduce the risk of preeclampsia. We determined associations of calcium-based antacid and PPI use during pregnancy with late-onset preeclampsia (≥34 weeks of gestation), taking into account dosage and timing of use.

Patients and Methods

We included 9058 pregnant women participating in the PRIDE Study (2012–2019) or The Dutch Pregnancy Drug Register (2014–2019), two prospective cohorts in The Netherlands. Data were collected through web-based questionnaires and obstetric records. We estimated risk ratios (RRs) for late-onset preeclampsia for any use and trajectories of calcium-based antacid and PPI use before gestational day 238, and hazard ratios (HRs) for time-varying exposures after gestational day 237.

Results

Late-onset preeclampsia was diagnosed in 2.6% of pregnancies. Any use of calcium-based antacids (RR 1.2 [95% CI 0.9–1.6]) or PPIs (RR 1.4 [95% CI 0.8–2.4]) before gestational day 238 was not associated with late-onset preeclampsia. Use of low-dose calcium-based antacids in gestational weeks 0–16 (<1 g/day; RR 1.8 [95% CI 1.1–2.9]) and any use of PPIs in gestational weeks 17–33 (RR 1.6 [95% CI 1.0–2.8]) seemed to increase risks of late-onset preeclampsia. We did not observe associations between late-onset preeclampsia and use of calcium-based antacids (HR 1.0 [95% CI 0.6–1.5]) and PPIs (HR 1.4 [95% CI 0.7–2.9]) after gestational day 237.

Conclusion

In this prospective cohort study, use of calcium-based antacids and PPIs during pregnancy was not found to reduce the risk of late-onset preeclampsia.

Cohort profile: the Western Cape Pregnancy Exposure Registry (WCPER)

PURPOSE

The Western Cape Pregnancy Exposure Registry (PER) was established at two public sector healthcare sentinel sites in the Western Cape province, South Africa, to provide ongoing surveillance of drug exposures in pregnancy and associations with pregnancy outcomes.

PARTICIPANTS

Established in 2016, all women attending their first antenatal visit at primary care obstetric facilities were enrolled and followed to pregnancy outcome regardless of the site (ie, primary, secondary, tertiary facility). Routine operational obstetric and medical data are digitised from the clinical stationery at the healthcare facilities. Data collection has been integrated into existing services and information platforms and supports routine operations. The PER is situated within the Provincial Health Data Centre, an information exchange that harmonises and consolidates all health-related electronic data in the province. Data are contributed via linkage across a unique identifier. This relationship limits the missing data in the PER, allows validation and avoids misclassification in the population-level data set.

FINDINGS TO DATE

Approximately 5000 and 3500 pregnant women enter the data set annually at the urban and rural sites, respectively. As of August 2021, >30 000 pregnancies have been recorded and outcomes have been determined for 93%. Analysis of key obstetric and neonatal health indicators derived from the PER are consistent with the aggregate data in the District Health Information System.

FUTURE PLANS

This represents significant infrastructure, able to address clinical and epidemiological concerns in a low/middle-income setting.

Identification of pregnancies and infants within a United States commercial healthcare administrative claims database

PURPOSE

Health care insurance claims databases are becoming a more common data source for studies of medication safety during pregnancy. While pregnancies have historically been identified in such databases by pregnancy outcomes, International Classification of Diseases, 10^th revision Clinical Modification (ICD-10-CM) Z3A codes denoting weeks of gestation provide more granular information on pregnancies and pregnancy periods (i.e. start and end dates). The purpose of this study was to develop a process that uses Z3A codes to identify pregnancies, pregnancy periods, and links infants within a commercial health insurance claims database.

METHODS

We identified pregnancies, gestation periods, pregnancy outcomes, and linked infants within the United States (US)-based Optum Research Database (ORD) between 2015 and 2020 via a series of algorithms utilizing diagnosis and procedure codes on claims. The diagnosis and procedure codes included ICD-10-CM codes, Current Procedural Terminology (CPT) codes, and Healthcare Common Procedure Coding System (HCPCS) codes.

RESULTS

We identified 1,030,874 pregnancies among 841,196 women of reproductive age. Of pregnancies with livebirth outcomes, 84% were successfully linked to infants. The prevalence of pregnancy outcomes (livebirth, stillbirth, ectopic, molar, abortion) was similar to national estimates.

CONCLUSIONS

This process provides an opportunity to study drug safety and care patterns during pregnancy and may be replicated in other claims databases containing ICD-10-CM, CPT, and HCPCS codes. Work is underway to validate and refine the various algorithms. This article is protected by copyright. All rights reserved.

Utility of fertility procedures and prenatal tests to estimate gestational age for live-births and stillbirths in electronic health plan databases

PURPOSE

Current algorithms to evaluate gestational age (GA) during pregnancy rely on hospital coding at delivery and are not applicable to non-live births. We developed an algorithm using fertility procedures and fertility tests, without relying on delivery coding, to develop a novel GA algorithm in live-births and stillbirths.

METHODS

Three pregnancy cohorts were identified from 16 health-plans in the Sentinel System: 1) hospital admissions for live-birth, 2) hospital admissions for stillbirth, and 3) medical chart-confirmed stillbirths. Fertility procedures and prenatal tests, recommended within specific GA windows were evaluated for inclusion in our GA algorithm. Our GA algorithm was developed against a validated delivery-based GA algorithm in live-births, implemented within a sample of chart-confirmed stillbirths, and compared to national estimates of GA at stillbirth.

RESULTS

Our algorithm, including fertility procedures and 11 prenatal tests, assigned a GA at delivery to 97.9% of live-births and 92.6% of stillbirths. For live-births (n = 4 701 207), it estimated GA within two weeks of a reference delivery-based GA algorithm in 82.5% of pregnancies, with a mean difference of 3.7 days. In chart-confirmed stillbirths (n = 49), it estimated GA within two weeks of the clinically recorded GA at delivery for 80% of pregnancies, with a mean difference of 11.1 days. Implementation of the algorithm in a cohort of stillbirths (n = 40 484) had an increased percentage of deliveries after 36 weeks compared to national estimates.

CONCLUSIONS

In a population of primarily commercially-insured pregnant women, fertility procedures and prenatal tests can estimate GA with sufficient sensitivity and accuracy for utility in pregnancy studies.

Does race or ethnicity play a role in the origin, pathophysiology, and outcomes of preeclampsia? An expert review of the literature

The burden of preeclampsia, a substantial contributor to perinatal morbidity and mortality, is not born equally across the population. Although the prevalence of preeclampsia has been reported to be 3% to 5%, racial and ethnic minority groups such as non-Hispanic Black women and American Indian or Alaskan Native women are widely reported to be disproportionately affected by preeclampsia. However, studies that add clarity to the causes of the racial and ethnic differences in preeclampsia are limited. Race is a social construct, is often self-assigned, is variable across settings, and fails to account for subgroups. Studies of the genetic structure of human populations continue to find more variations within racial groups than among them. Efforts to examine the role of race and ethnicity in biomedical research should consider these limitations and not use it as a biological construct. Furthermore, the use of race in decision making in clinical settings may worsen the disparity in health outcomes. Most of the existing data on disparities examine the differences between White and non-Hispanic Black women. Fewer studies have enough sample size to evaluate the outcomes in the Asian, American Indian or Alaskan Native, or mixed-race women. Racial differences are noted in the occurrence, presentation, and short-term and long-term outcomes of preeclampsia. Well-established clinical risk factors for preeclampsia such as obesity, diabetes, and chronic hypertension disproportionately affect non-Hispanic Black, American Indian or Alaskan Native, and Hispanic populations. However, with comparable clinical risk factors for preeclampsia among women of different race or ethnic groups, addressing modifiable risk factors has not been found to have the same protective effect for all women. Abnormalities of placental formation and development, immunologic factors, vascular changes, and inflammation have all been identified as contributing to the pathophysiology of preeclampsia. Few studies have examined race and the pathophysiology of preeclampsia. Despite attempts, a genetic basis for the disease has not been identified. A number of genetic variants, including apolipoprotein L1, have been identified as possible risk modifiers. Few studies have examined race and prevention of preeclampsia. Although low-dose aspirin for the prevention of preeclampsia is recommended by the US Preventive Service Task Force, a population-based study found racial and ethnic differences in preeclampsia recurrence after the implementation of low-dose aspirin supplementation. After implementation, recurrent preeclampsia reduced among Hispanic women (76.4% vs 49.6%; P<.001), but there was no difference in the recurrent preeclampsia in non-Hispanic Black women (13.7 vs 18.1; P=.252). Future research incorporating the National Institute on Minority Health and Health Disparities multilevel framework, specifically examining the role of racism on the burden of the disease, may help in the quest for effective strategies to reduce the disproportionate burden of preeclampsia on a minority population. In this model, a multilevel framework provides a more comprehensive approach and takes into account the influence of behavioral factors, environmental factors, and healthcare systems, not just on the individual.

Association of Alcohol Use Diagnostic Codes in Pregnancy and Offspring Conotruncal and Endocardial Cushion Heart Defects

Background

The pathogenesis of congenital heart disease (CHD) remains largely unknown, with only a small percentage explained solely by genetic causes. Modifiable environmental risk factors, such as alcohol, are suggested to play an important role in CHD pathogenesis. We sought to evaluate the association between prenatal alcohol exposure and CHD to gain insight into which components of cardiac development may be most vulnerable to the teratogenic effects of alcohol.

Methods and Results

This was a retrospective analysis of hospital discharge records from the California Office of Statewide Health Planning and Development and linked birth certificate records restricted to singleton, live‐born infants from 2005 to 2017. Of the 5 820 961 births included, 16 953 had an alcohol‐related International Classification of Diseases, Ninth and Tenth Revisions (ICD‐9; ICD‐10) code during pregnancy. Log linear regression was used to calculate risk ratios (RR) for CHD among individuals with an alcohol‐related ICD‐9 and ICD10 code during pregnancy versus those without. Three models were created: (1) unadjusted, (2) adjusted for maternal demographic factors, and (3) adjusted for maternal demographic factors and comorbidities. Maternal alcohol‐related code was associated with an increased risk for CHD in all models (RR, 1.33 to 1.84); conotruncal (RR, 1.62 to 2.11) and endocardial cushion (RR, 2.71 to 3.59) defects were individually associated with elevated risk in all models.

Conclusions

Alcohol‐related diagnostic codes in pregnancy were associated with an increased risk of an offspring with a CHD, with a particular risk for endocardial cushion and conotruncal defects. The mechanistic basis for this phenotypic enrichment requires further investigation.

Longitudinal Methods for Modeling Exposures in Pharmacoepidemiologic Studies in Pregnancy

In many perinatal pharmacoepidemiologic studies, exposure to a medication is classified as "ever exposed" versus "never exposed" within each trimester or even over the entire pregnancy. This approach is often far from real-world exposure patterns, may lead to exposure misclassification, and does not to incorporate important aspects such as dosage, timing of exposure, and treatment duration. Alternative exposure modeling methods can better summarize complex, individual-level medication use trajectories or time-varying exposures from information on medication dosage, gestational timing of use, and frequency of use. We provide an overview of commonly used methods for more refined definitions of real-world exposure to medication use during pregnancy, focusing on the major strengths and limitations of the techniques, including the potential for method-specific biases. Unsupervised clustering methods, including k-means clustering, group-based trajectory models, and hierarchical cluster analysis, are of interest because they enable visual examination of medication use trajectories over time in pregnancy and complex individual-level exposures, as well as providing insight into comedication and drug-switching patterns. Analytical techniques for time-varying exposure methods, such as extended Cox models and Robins' generalized methods, are useful tools when medication exposure is not static during pregnancy. We propose that where appropriate, combining unsupervised clustering techniques with causal modeling approaches may be a powerful approach to understanding medication safety in pregnancy, and this framework can also be applied in other areas of epidemiology.

Vaccine exposure during pregnancy among privately and publicly insured women in the United States, 2016-2018

BACKGROUND

Vaccine use during pregnancy affects maternal and infant health. Many women do not receive vaccines recommended during pregnancy; conversely, inadvertent exposure to vaccines contraindicated or not recommended during pregnancy may occur. We assessed exposure to two recommended vaccines and two vaccines not recommended during pregnancy among privately and Medicaid-insured women in the United States.

METHODS

This study includes a retrospective cohort of pregnancies in women aged 12-55 years resulting in live birth, spontaneous abortion, or stillbirth identified in the IBM® MarketScan® Commercial, Blue Health Intelligence® (BHI®) Commercial, and IBM MarketScan Multi-State Medicaid Databases from August 1, 2016, to December 31, 2018. Gestational age at vaccination was determined using a validated algorithm. We examined vaccines (1) recommended by the Centers for Disease Control and Prevention Advisory Committee on Immunization Practices (ACIP) (tetanus, diphtheria, and acellular pertussis [Tdap]; inactivated influenza) and (2) not recommended (human papillomavirus [HPV]) or contraindicated (measles, mumps, and rubella [MMR]).

RESULTS

We identified 496,771 (MarketScan Commercial), 858,961 (BHI), and 289,573 (MarketScan Medicaid) pregnancies (approximately 75% aged 20-34 years). Across these three databases, 52.1%, 50.3%, and 31.3% of pregnancies, respectively, received Tdap, most often at a gestational age of 28 weeks, and influenza vaccination occurred in 32.1%, 30.8%, and 18.0% of pregnancies, respectively. HPV vaccination occurred in < 0.2% of pregnancies, mostly in the first trimester among women aged 12-19 years, and MMR was administered in < 0.1% of pregnancies. Use of other contraindicated vaccines per ACIP (e.g., varicella, live attenuated influenza) was rare.

CONCLUSION

Maternal vaccination with ACIP-recommended vaccines was suboptimal among privately and Medicaid-insured patients, with lower vaccination coverage among Medicaid-insured pregnancies than their privately insured counterparts. Inadvertent exposure to contraindicated vaccines during pregnancy was rare. This study evaluated only vaccinations reimbursed among insured populations and may have limited generalizability to uninsured populations.

Validating Claims-Based Algorithms Determining Pregnancy Outcomes and Gestational Age Using a Linked Claims-Electronic Medical Record Database

Introduction

Pregnancy outcome identification and precise estimates of gestational age (GA) are critical in drug safety studies of pregnant women. Validated pregnancy outcome algorithms based on the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) have not previously been published.

Methods

We developed algorithms to classify pregnancy outcomes and estimate GA using ICD-10-CM/PCS and service codes on claims in the 2016–2018 IBM^® MarketScan^® Explorys^® Claims-EMR Data Set and compared the results with ob-gyn adjudication of electronic medical records (EMRs). Obstetric services were grouped into episodes using hierarchical and spacing requirements. GA was based on evidence with the highest clinical accuracy. Among pregnancies with obstetric EMRs, 100 full-term live births (FTBs), 100 preterm live births (PTBs), 100 spontaneous abortions (SAs), and 24 stillbirths were selected for review. Physicians adjudicated cases using Global Alignment of Immunization safety Assessment in pregnancy (GAIA) definitions applied to structured EMRs.

Results

The claims-based algorithms identified 34,204 pregnancies, of which 9.9% had obstetric EMRs. Of sampled pregnancies, 92 FTBs, 93 PTBs, 75 SAs, and 24 stillbirths were adjudicated. Among these pregnancies, the percent agreement was 97.8%, 62.4%, 100.0%, and 70.8% for FTBs, PTBs, SAs, and stillbirths, respectively. The percent agreement on GA within 7 and 28 days, respectively, was 85.9% and 100.0% for FTBs, 81.7% and 98.9% for PTBs, 61.3% and 94.7% for SAs, and 66.7% and 79.2% for stillbirths.

Conclusions

The pregnancy outcome algorithms had high agreement with physician adjudication of EMRs and may inform post-market maternal safety surveillance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40264-021-01113-8.

Associations Between Maternal Depression, Antidepressant Use During Pregnancy, and Adverse Pregnancy Outcomes: An Individual Participant Data Meta-analysis

OBJECTIVE

To evaluate the associations of depressive symptoms and antidepressant use during pregnancy with the risks of preterm birth, low birth weight, small for gestational age (SGA), and low Apgar scores.

DATA SOURCES

MEDLINE, EMBASE, ClinicalTrials.gov, and PsycINFO up to June 2016.

METHODS OF STUDY SELECTION

Data were sought from studies examining associations of depression, depressive symptoms, or use of antidepressants during pregnancy with gestational age, birth weight, SGA, or Apgar scores. Authors shared the raw data of their studies for incorporation into this individual participant data meta-analysis.

TABULATION, INTEGRATION, AND RESULTS

We performed one-stage random-effects meta-analyses to estimate odds ratios (ORs) with 95% CIs. The 215 eligible articles resulted in 402,375 women derived from 27 study databases. Increased risks were observed for preterm birth among women with a clinical diagnosis of depression during pregnancy irrespective of antidepressant use (OR 1.6, 95% CI 1.2-2.1) and among women with depression who did not use antidepressants (OR 2.2, 95% CI 1.7-3.0), as well as for low Apgar scores in the former (OR 1.5, 95% CI 1.3-1.7), but not the latter group. Selective serotonin reuptake inhibitor (SSRI) use was associated with preterm birth among women who used antidepressants with or without restriction to women with depressive symptoms or a diagnosis of depression (OR 1.6, 95% CI 1.0-2.5 and OR 1.9, 95% CI 1.2-2.8, respectively), as well as with low Apgar scores among women in the latter group (OR 1.7, 95% CI 1.1-2.8).

CONCLUSION

Depressive symptoms or a clinical diagnosis of depression during pregnancy are associated with preterm birth and low Apgar scores, even without exposure to antidepressants. However, SSRIs may be independently associated with preterm birth and low Apgar scores.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO, CRD42016035711.

Protocol of a prospective and multicentre China Teratology Birth Cohort (CTBC): association of maternal drug exposure during pregnancy with adverse pregnancy outcomes

BACKGROUND

As reported, 27-93 % of pregnant women take at least one drug during pregnancy. However, drug exposure during pregnancy still lacks sufficient foetal safety evidence of human origin. It is urgent to fill the knowledge gap about medication safety during pregnancy for optimization of maternal disease treatment and pregnancy drug consultation.

METHODS AND ANALYSIS

The China Teratology Birth Cohort (CTBC) was established in 2019 and is a hospital-based open-ended prospective cohort study with the aim of assessing drug safety during pregnancy. Pregnant women who set up the pregnancy health records in the first trimester or who seek drug consultation regardless of gestational age in the member hospitals are recruited. Enrolled pregnant women need to be investigated four times, namely, 6-14 and 24-28 weeks of gestational age, before discharge after hospital delivery, and 28-42 days after birth. Maternal medication exposure during pregnancy is the focus of the CTBC. For drugs, information on the type, name, and route of medication; start and end time of medication; single dose; frequency of medication; dosage form; manufacturer; and reason for medication is collected. The adverse pregnancy outcomes collected in the study include birth defects, stillbirth, spontaneous abortion, preterm birth, post-term birth, low birth weight, macrosomia, small for gestational age, large for gestational age and low Apgar score. CTBC uses an electronic questionnaire for data collection and a cloud system for data management. Biological samples are collected if informed consents are obtained. Multi-level logistic regression, mixed-effect negative binomial distribution regression and spline function regression are used to explore the effect of drugs on the occurrence of birth defects.

DISCUSSION

The findings of the study will assist in further understanding the risk of birth defects and other adverse pregnancy outcomes associated with maternal drug exposure and developing the optimal treatment plans and drug counselling for pregnant women.

TRIAL REGISTRATION

This study was approved by the Research Ethics Committee of the West China Second Hospital of Sichuan University and registered at the Chinese Clinical Trial Registry ( http://www.chictr.org.cn/index.aspx , registration number ChiCTR1900022569 ).

Cannabis-related diagnosis in pregnancy and adverse maternal and infant outcomes

BACKGROUND

Cannabis use and cannabis use disorders are increasing in prevalence, including among pregnant women. The objective was to evaluate the association of a cannabis-related diagnosis (CRD) in pregnancy and adverse maternal and infant outcomes.

METHODS

We queried an administrative birth cohort of singleton deliveries in California between 2011-2017 linked to maternal and infant hospital discharge records. We classified pregnancies with CRD from International Classification of Disease codes. We identified nicotine and other substance-related diagnoses (SRD) in the same manner. Outcomes of interest included maternal (hypertensive disorders) and infant (prematurity, small for gestational age, NICU admission, major structural malformations) adverse outcomes.

RESULTS

From 3,067,069 pregnancies resulting in live births, 29,112 (1.0 %) had a CRD. CRD was associated with an increased risk of all outcomes studied; the strongest risks observed were for very preterm birth (aRR 1.4, 95 % CI 1.3, 1.6) and small for gestational age (aRR 1.4, 95 % CI 1.3, 1.4). When analyzed with or without co-exposure diagnoses, CRD alone conferred increased risk for all outcomes compared to no use. The strongest effects were seen for CRD with other SRD (preterm birth aRR 2.3, 95 % CI 2.2, 2.5; very preterm birth aRR 2.6, 95 % CI 2.3, 3.0; gastrointestinal malformations aRR 2.0, 95 % CI 1.6, 2.6). The findings were generally robust to unmeasured confounding and misclassification analyses.

CONCLUSIONS

CRD in pregnancy was associated with increased risk of adverse maternal and infant outcomes. Providing education and effective treatment for women with a CRD during prenatal care may improve maternal and infant health.

Antiemetic Prescription Fills in Pregnancy: A Drug Utilization Study Among 762,437 Pregnancies in Norway

Objective

To determine antiemetic prescription fill patterns during pregnancy in Norway, with special focus on the use of ondansetron and recurrent use in subsequent pregnancies.

Methods

We conducted a population-based registry study based on data from the Medical Birth Registry of Norway linked to the Norwegian Prescription Database for 762,437 pregnancies >12 gestational weeks ending in live or non-live births between 2005 and 2017. Prescription fills of medications used for nausea and vomiting of pregnancy were summarized in treatment pathways to determine drug utilization patterns. Logistic regression analyses were used to estimate associations between maternal and pregnancy characteristics and antiemetic prescription fills.

Results

The prescription fill rate for antiemetic medication during pregnancy was 7.6%. However, prescription fill rates were 35.5% in the second pregnancy after filling an antiemetic prescription in the first pregnancy and 53.5% for women who filled antiemetic prescriptions in the previous 2 pregnancies. Among pregnancies with antiemetic prescription fills, 62.2% were dispensed metoclopramide, 28.2% meclizine, and 17.2% promethazine. First-line treatment started with monotherapy in 97.4% of these pregnancies, which was the only treatment received in 78.7%. Prescriptions for ondansetron were filled in 0.3% of pregnancies, with 76.9% being initially filled in the first trimester. Ondansetron as first-line prescription medication and/or use in the first trimester was associated with proxies for more severe nausea and vomiting of pregnancy, including a diagnosis of hyperemesis gravidarum, multiple gestations, a higher obstetric comorbidity index, and concomitant use of medication for gastroesophageal reflux disease and nervous system medications. Women who filled an antiemetic prescription in their first pregnancy were less likely to have subsequent pregnancies than women who did not fill an antiemetic prescription in their first pregnancy (OR 0.93, 95% CI 0.90–0.96).

Conclusion

Complex patterns of antiemetic prescription fills in pregnancy may mirror the challenge of optimal management of nausea and vomiting of pregnancy in clinical practice, especially for women with severe symptoms.

Fertility treatment and oral contraceptive discontinuation for identification of pregnancy planning in routinely collected health data - an application to analgesic and antibiotic utilisation

BACKGROUND

Women with unplanned pregnancies use folic acid less frequently, and more often use potentially teratogenic medications in the first trimester. Yet most studies based on routinely collected data lack information on pregnancy planning. Further, only pregnancies proceeding beyond a certain gestational age appear in routinely collected data, creating the possibility for collider-stratification bias. If pregnancy intention could be identified, pregnancies could be ascertained earlier. This study aimed to investigate fertility treatment and discontinuation of oral contraception (OC) as proxies for pregnancy planning by describing variations in patterns of prescription fills for antibiotics and analgesics during the peri-pregnancy period by these proxies of pregnancy intention.

METHODS

Fertility treatment with clomiphene and discontinuation of OC were identified in the Norwegian Prescription Database (NorPD) and linked with data from the Medical Birth Registry of Norway for the years 2006 to 2017. Filled prescriptions for antibiotics and analgesics from NorPD were displayed for women on fertility treatment, women who discontinued OC before pregnancy, and women who discontinued during pregnancy.

RESULTS

Of 172,585 included pregnancies, fertility treatment was identified in 19,449, and OC discontinuation before or during pregnancy in 153,136. Women who discontinued OC during pregnancy were less likely to use preconception folic acid (25.4%) than women who discontinued before pregnancy (32.9%), and women on fertility treatment (51.0%). Proportions of first trimester prescription fills were 4.9% (analgesics) and 12.8% (antibiotics) for women who discontinued OC during pregnancy, compared to 4.0 and 11.4% in women who discontinued OC before pregnancy, and 4.7 and 11.0% in women on fertility treatment.

CONCLUSIONS

There were no substantial differences in patterns of prescription fills for analgesics and antibiotics before or during pregnancy by fertility treatment and OC discontinuation. This suggests that there were few differences in medication use between women with planned and unplanned pregnancies, or that fertility treatment and timing of OC discontinuation from routinely collected health data cannot stand alone in the identification of unplanned pregnancies. A narrower definition of OC discontinuation during pregnancy seemed to be a better proxy, but this should be confirmed in other studies.

Ondansetron use in early pregnancy and the risk of late pregnancy outcomes

BACKGROUND

The effects of ondansetron, used off-label to treat nausea and vomiting during pregnancy, on common pregnancy complications are understudied. Modest effects of a commonly used drug could result in adverse events for large numbers of pregnant women. Therefore, our objective was to compare the risk of stillbirth, preterm birth, gestational hypertensive disorders, small for gestational age, and differences in birth weight between women prescribed ondansetron and women prescribed alternative antiemetics in early pregnancy.

METHODS

A cohort of pregnant women receiving a prescription for ondansetron or comparator antiemetics (metoclopramide or promethazine) during the first 20 weeks of pregnancy was identified using electronic health record data from a health care system in North Carolina, USA. Confounding by multiple covariates was controlled using stabilized inverse probability of treatment weights. Weighted hazard ratios (HR) and 95% confidence intervals (CI) accounted for competing events.

RESULTS

We identified 2677 eligible pregnancies with antiemetic orders, 66% for ondansetron. The small number of stillbirths (n = 15) resulted in an imprecise estimate of the association with ondansetron (HR = 1.60; 95%CI 0.51, 4.97). No association was observed for preterm birth (HR = 0.90; 95%CI 0.67, 1.20) or gestational hypertensive disorders (HR = 0.87; 95%CI 0.68, 1.12). We observed an association with small for gestational age (HR = 1.37; 95%CI 0.98, 1.90), however mean birth weight among term births was similar between groups.

CONCLUSIONS

Our results do not suggest that ondansetron increases the risk of preterm birth or gestational hypertensive disorders. The weak association observed between ondansetron use and small for gestational age warrants further investigation.

Safe Expectations: Current State and Future Directions for Medication Safety in Pregnancy Research

Medication use in pregnancy is common, but information about the safety of most medications in pregnant women or their infants is limited. In the absence of data from randomized clinical trials to guide decisions made by regulators, clinicians, and patients, we often have to rely on well-designed observational studies to generate valid evidence about the benefits and risks of medications in pregnancy. Spontaneous reporting, primary case-control and cohort studies, pregnancy exposure registries, and electronic health data have been used extensively for studying medication safety in pregnancy. This article discusses these data sources, their strengths and limitations, and possible strategies and approaches to mitigating limitations when planning studies or interpreting findings from the literature. Strategies discussed include combining data sources across institutional or national borders, developing and using more sophisticated study designs, and taking advantage of existing analytic methods for more complex data structures, such as time-varying exposure or unmeasured confounding. Finally, we make recommendations for study designs that aid in better risk-related communication.

Aim and Design of pREGnant, the Dutch Pregnancy Drug Register

Information on the safety of medication use during pregnancy and breastfeeding is scarce, yet use of medication among pregnant and breastfeeding women is widespread. The pREGnant, the Dutch Pregnancy Drug Register, was set up to obtain insight into medication use among pregnant and breastfeeding women and potential effects on maternal and fetal/infant health. The systematically documented, good quality data on medication use during pregnancy and lactation in pREGnant will be used in signal detection, epidemiologic studies and counseling of healthcare providers and patients. The register has a prospective cohort design. The population is derived from pregnant women throughout the Netherlands. Data collection started in April 2014 and enrollment of women is continuous and is characterized by a relative high proportion of women born in the Netherlands with a high education compared with the general Dutch pregnant population. Data on current pregnancy, obstetric history, maternal lifestyle, health and medication use, delivery, and infant health are collected through web-based questionnaires completed by the participating women (three times during pregnancy and three times during the infant’s first year of life). If permission is given, the self-reported data can be complemented with information retrieved from Perined, the perinatal registry of the Netherlands, and from obstetric and medical records, and/or pharmacy records. Here, we provide detailed information on the design of the pREGnant, the Dutch Pregnancy Drug Register, as well as descriptive information on characteristics of the participants so far. Currently, steps are being taken to implement the register on a large scale in the Netherlands.

Assessment of medication use during pregnancy by Web-based questionnaires, pharmacy records and serum screening

OBJECTIVE

To compare assessment of early pregnancy medication exposure using three methods of data collection.

METHODS

Serum samples were obtained from 752 women participating in the PRegnancy and Infant DEvelopment (PRIDE) Study before gestational week 17. For 52 women using medication at the date of blood sampling according to Web-based questionnaires or pharmacy records, we analysed serum samples using untargeted liquid chromatography time-of-flight spectrometry.

RESULTS

Medication was detected in 18 serum samples (35%). Medications taken orally for chronic conditions reported in the questionnaire were detected in serum and vice versa. Pharmacy records did not identify additional exposed women, but missed exposure in 5 women mainly due to unavailability. We observed substantial discordance between the three methods for inhaled medication, dermatological preparations, and medications for short-term use, which went often undetected in serum.

CONCLUSIONS

It remains challenging to assess medication use in large-scale studies as no 'gold standard' is currently available.

Estimating Effects of Dynamic Treatment Strategies in Pharmacoepidemiologic Studies with Time-varying Confounding: A Primer

PURPOSE OF REVIEW

Pharmacoepidemiologists are often interested in estimating the effects of dynamic treatment strategies, where treatments are modified based on patients' evolving characteristics. For such problems, appropriate control of both baseline and time-varying confounders is critical. Conventional methods that control confounding by including time-varying treatments and confounders in an outcome regression model may not have a causal interpretation, even when all baseline and time-varying confounders are measured. This problem occurs when time-varying confounders are, themselves, affected by past treatment. We review alternative analytic approaches that can produce valid inferences in the presence of such confounding. We focus on the parametric g-formula and inverse probability weighting of marginal structural models, two examples of Robins' g-methods.

RECENT FINDINGS

Unlike standard outcome regression methods, the parametric g-formula and inverse probability weighting of marginal structural models can estimate the effects of dynamic treatment strategies and appropriately control for measured time-varying confounders affected by prior treatment. Few applications of g-methods exist in the pharmacoepidemiology literature, primarily due to the common use of administrative claims data, which typically lack detailed measurements of time-varying information, and the limited availability of or familiarity with tools to help perform the relatively complex analysis. These barriers may be overcome with the increasing availability of data sources containing more detailed time-varying information and more accessible learning tools and software.

SUMMARY

With appropriate data and study design, g-methods can improve our ability to make causal inferences on dynamic treatment strategies from observational data in pharmacoepidemiology.

Making fair comparisons in pregnancy medication safety studies: An overview of advanced methods for confounding control

Understanding the safety of medication use during pregnancy relies on observational studies: However, confounding in observational studies poses a threat to the validity of estimates obtained from observational data. Newer methods, such as marginal structural models and propensity calibration, have emerged to deal with complex confounding problems, but these methods have seen limited uptake in the pregnancy medication literature. In this article, we provide an overview of newer advanced methods for confounding control and show how these methods are relevant for pregnancy medication safety studies.