Utilization of drugs with pregnancy exposure registries during pregnancy

Drug exposure during pregnancy in primary care: an algorithm and observational study from SIDIAP database, Catalunya, Spain

OBJECTIVES

To develop an algorithm to identify pregnancy episodes in women at childbearing age using SIDIAP (Information System for the Improvement of Research in Primary Care) data (Catalunya, Spain).To describe drugs dispensed during gestation.

DESIGN

Construction of an algorithm to identify all pregnancy episodes occurred from January 2011 to June 2020 in women aged 12-50. The variables used to create the algorithm include first day of last menstrual period, reasons for pregnancy termination and diagnoses registered in the primary healthcare records. Population-based cohort study including the pregnancy episodes identified by the algorithm.

SETTING

Catalonia, Spain.

PARTICIPANTS

All women aged 12-50 with at least one pregnancy episode occurred during January 2011-June 2020.

INTERVENTIONS

No interventions performed.

PRIMARY AND SECONDARY OUTCOME MEASURES

Identification of pregnancy episodes through an algorithm and description of drug exposure.

RESULTS

We identified 327 865 pregnancy episodes in 250 910 people with a mean age of 31.3 years. During the study period, 83.4% of the episodes were exposed to at least one drug. The most frequent groups dispensed were iron preparations (48% of pregnancy episodes), iodine therapy (40.2%), analgesics and antipyretics (28%), penicillins (19.8%), vitamin B12 plus folic acid (19.7%) and non-steroidal anti-inflammatory drugs (NSAIDs, 15.1%). The supplements were more frequently dispensed at least twice, and the drugs for acute conditions were mainly dispensed only once during the pregnancy episode.

CONCLUSIONS

We developed an algorithm to automatically identify the pregnancy periods in SIDIAP.We described prescription drugs used during pregnancy. The most used ones were supplements, analgesics, NSAID or antibiotics.SIDIAP might be an efficient database to study drug safety during pregnancy and the consequences of drug use in the offspring.

TRIAL REGISTRATION NUMBER

EUPAS37675.

The US Food and Drug Administration Sentinel System: a national resource for a learning health system

The US Food and Drug Administration (FDA) created the Sentinel System in response to a requirement in the FDA Amendments Act of 2007 that the agency establish a system for monitoring risks associated with drug and biologic products using data from disparate sources. The Sentinel System has completed hundreds of analyses, including many that have directly informed regulatory decisions. The Sentinel System also was designed to support a national infrastructure for a learning health system. Sentinel governance and guiding principles were designed to facilitate Sentinel's role as a national resource. The Sentinel System infrastructure now supports multiple non-FDA projects for stakeholders ranging from regulated industry to other federal agencies, international regulators, and academics. The Sentinel System is a working example of a learning health system that is expanding with the potential to create a global learning health system that can support medical product safety assessments and other research.

Fingolimod, teriflunomide and cladribine for the treatment of multiple sclerosis in women of childbearing age: description of drug utilization and exposed pregnancies in Germany

BACKGROUND

Authorizations of fingolimod, teriflunomide and cladribine were accompanied by risk minimization measures concerning their teratogenic potential. Real-world data on their use are scarce. We aimed to assess trends in the use of fingolimod, teriflunomide and cladribine among women of childbearing age, estimate the number of pregnancies occurring under treatment and explore the occurrence of malformations in newborns exposed during early pregnancy in Germany.

METHODS

Using the German Pharmacoepidemiological Research Database (GePaRD, claims data from ∼20% of the German population), we determined annual age-standardized prevalences of fingolimod, teriflunomide and cladribine use from their authorization until 2019 among women aged 13-49 years (cross-sectional analyses). In longitudinal analyses, we estimated the number of exposed pregnancies by assessing whether there was an overlap between the exposure windows assigned to dispensations and the onset of pregnancy or a dispensation in the first eight weeks of pregnancy. For live births, a mother-baby linkage was performed. All available data of children with in-utero exposure and malformation codes in the first year of life were reviewed to verify the occurrence of congenital malformations.

RESULTS

For fingolimod, the age-standardized prevalence of use per 1,000 females increased from 0.14 in 2011 to 0.46 in 2019; for teriflunomide, from 0.06 in 2013 to 0.28 in 2019; for cladribine, from 0.01 in 2017 to 0.07 in 2019. The proportion of users aged ≤40 years was 60% for fingolimod, 45% for teriflunomide and 65% for cladribine. We identified 136 pregnancies exposed to fingolimod, 50 to teriflunomide and one to cladribine. For fingolimod and teriflunomide, respectively, 72% and 62% of exposed pregnancies ended in a live birth. Mother-newborn linkage was successful in 64 (fingolimod) and 20 (teriflunomide) live-born children. Among these, there were six with relevant malformations (mainly heart defects) for fingolimod and two for teriflunomide.

CONCLUSION

Use of fingolimod, teriflunomide and cladribine among women of childbearing age has substantially increased in Germany. A high proportion of users was in age groups in which pregnancies typically occur. Despite risk minimization measures, early pregnancy exposure to these drugs was observed.

Development and evaluation of standardized pregnancy identification and trimester distribution algorithms in U.S. IBM MarketScan® Commercial and Medicaid data

OBJECTIVES

Creation of new algorithms to identify pregnancies in automated health care claims databases is of public health importance, as it allows us to learn more about medication use and safety in a vulnerable population. Previous algorithms were largely created using international classification of disease codes, but despite the U.S. code transition in 2015, few algorithms are available with the latest ICD-10-CM codes.

METHODS

Using U.S. IBM MarketScan® Commercial Claims and Encounters and Multi-State Medicaid databases for women aged 10-64 years during 2014 and 2016, two pregnancy algorithms (ICD-9-CM and ICD-10-CM) were created using expert clinical review. The algorithms were evaluated by assessing the distribution of pregnancy outcomes (live birth and pregnancy losses) within each time-based cohort and the ability of the algorithms to identify select medication use during pregnancy. Medication exposure, demographics, comorbidities, and pregnancy outcomes were compared to published literature estimates for the two time periods.

RESULTS

For the IBM MarketScan® Commercial database, the algorithms identified 687,228 pregnancies in 2014 and 444,293 in 2016. In the IBM MarketScan® Medicaid database, 389,132 pregnancies in 2014 and 406,418 in 2016 were identified. Percentages of most pregnancy outcomes identified using the algorithms were similar to national data sources; however, percentages of preterm births and pregnancy losses were not comparable. Most medication use estimates from the algorithms were similar to or higher than published estimates.

CONCLUSIONS

By incorporating the latest ICD-10-CM codes, the new algorithms provide more complete estimates of medication use during pregnancy than algorithms using the outdated codes.

Use of a mobile app to capture supplemental health information during pregnancy: Implications for clinical research

PURPOSE

Mobile applications ("apps") may be efficient tools for improving the quality of clinical research among pregnant women, but evidence is sparse. We assess the feasibility and generalizability of a mobile app for capturing supplemental data during pregnancy.

METHODS

In 2017, we conducted a pilot study of the FDA MyStudies mobile app within a pregnant population identified through Kaiser Permanente Washington (KPWA), an integrated healthcare delivery system. We ascertained health conditions, medications, and substance use through app-based questionnaires. In a post-hoc analysis, we utilized electronic health records (EHR) to summarize sociodemographic and health characteristics of pilot participants and, for comparison, a pregnant population identified using similar methods.

RESULTS

Six percent (64/1070) of contacted women enrolled in the pilot study. Nearly half (23/53) reported taking medication for headaches and one-fourth for constipation (13/53) and nausea (12/53) each. Few instances (2/92) of over-the-counter medication use were identified in electronic dispensing records. One-quarter to one-third of participants with depression and anxiety/panic, respectively, reported recently discontinuing medications for these conditions. Eighty-eight percent of pilot participants reported White race (95%CI: 81-95%), versus 67% of the comparison population (N = 2065). More pilot participants filled ≥1 prescription for antianxiety medication (22% [95%CI: 13-35%]) and antidepressants (19% [95%CI 10-31%]) pre-pregnancy than the comparison population (10 and 9%, respectively).

CONCLUSIONS

Mobile apps may be a feasible tool for capturing health data not routinely available in EHR. Pregnant women willing to use a mobile app for research may differ from the general pregnant population, but confirmation is needed.

Validation of an ICD-10-based algorithm to identify stillbirth in the Sentinel System

PURPOSE

To develop and validate an International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify cases of stillbirth using electronic healthcare data.

METHODS

We conducted a retrospective study using claims data from three Data Partners (healthcare systems and insurers) in the Sentinel Distributed Database. Algorithms were developed using ICD-10-CM diagnosis codes to identify potential stillbirths among females aged 12-55 years between July 2016 and June 2018. A random sample of medical charts (N = 169) was identified for chart abstraction and adjudication. Two physician adjudicators reviewed potential cases to determine whether a stillbirth event was definite/probable, the date of the event, and the gestational age at delivery. Positive predictive values (PPVs) were calculated for the algorithms. Among confirmed cases, agreement between the claims data and medical charts was determined for the outcome date and gestational age at stillbirth.

RESULTS

Of the 110 potential cases identified, adjudicators determined that 54 were stillbirth events. Criteria for the algorithm with the highest PPV (82.5%; 95% CI, 70.9%-91.0%) included the presence of a diagnosis code indicating gestational age ≥20 weeks and occurrence of either >1 stillbirth-related code or no other pregnancy outcome code (i.e., livebirth, spontaneous abortion, induced abortion) recorded on the index date. We found ≥90% agreement within 7 days between the claims data and medical charts for both the outcome date and gestational age at stillbirth.

CONCLUSIONS

Our results suggest that electronic healthcare data may be useful for signal detection of medical product exposures potentially associated with stillbirth.

Medications used disproportionately during pregnancy: Priorities for research on the risks and benefits of medications when used during pregnancy

PURPOSE

To identify medications used disproportionately more or less among pregnant women relative to women of childbearing age.

METHODS

Medication use among pregnant women in New South Wales, Australia was identified using linked perinatal and pharmaceutical dispensing data from 2006 to 2012. Medication use in women of childbearing age (including pregnant women) was identified using pharmaceutical dispensing data for a 10% random sample of the Australian population. Pregnant social security beneficiaries (n = 111 612) were age-matched (1:3) to female social security beneficiaries in the 10% sample. For each medication, the risk it was dispensed during pregnancy relative to being dispensed during an equivalent time period among matched controls was computed. Medications were mapped to Australian pregnancy risk categories.

RESULTS

Of the 181 included medications, 35 were statistically significantly more commonly dispensed to pregnant women than control women. Of these, 23 are categorised as posing no increased risk to the foetus. Among medications suspected of causing harm or having insufficient safety data, the strongest associations were observed for hydralazine, ondansetron, dalteparin sodium and ranitidine. Use was less likely during pregnancy than control periods for 127 medications, with the strongest associations observed for hormonal contraceptives and progestogens.

CONCLUSIONS

Most medications found to be used disproportionately more by pregnant women are indicated for pregnancy-related problems. A large number of medications were used disproportionately less among pregnant women, where avoidance of some of these medications may pose a greater risk of harm. For many other medications avoided during pregnancy, current data are insufficient to inform this risk-benefit assessment.

Antipsychotic drug use in pregnancy: A multinational study from ten countries

AIM

To compare the prevalence and trends of antipsychotic drug use during pregnancy between countries across four continents.

METHODS

Individually linked health data in Denmark (2000-2012), Finland (2005-2014), Iceland (2004-2017), Norway (2005-2015), Sweden (2006-2015), Germany (2006-2015), Australia (New South Wales, 2004-2012), Hong Kong (2001-2015), UK (2006-2016), and the US (Medicaid, 2000-2013, and IBM MarketScan, 2012-2015) were used. Using a uniformed approach, we estimated the prevalence of antipsychotic use as the proportion of pregnancies where a woman filled at least one antipsychotic prescription within three months before pregnancy until birth. For the Nordic countries, data were meta-analyzed to investigate maternal characteristics associated with the use of antipsychotics.

RESULTS

We included 8,394,343 pregnancies. Typical antipsychotic use was highest in the UK (4.4%) whereas atypical antipsychotic use was highest in the US Medicaid (1.5%). Atypical antipsychotic use increased over time in most populations, reaching 2% in Australia (2012) and US Medicaid (2013). In most countries, prochlorperazine was the most commonly used typical antipsychotic and quetiapine the most commonly used atypical antipsychotic. Use of antipsychotics decreased across the trimesters of pregnancy in all populations except Finland. Antipsychotic use was elevated among smokers and those with parity ≥4 in the Nordic countries.

CONCLUSION

Antipsychotic use during pregnancy varied considerably between populations, partly explained by varying use of the typical antipsychotic prochlorperazine, which is often used for nausea and vomiting in early pregnancy. Increasing usage of atypical antipsychotics among pregnant women reflects the pattern that was previously reported for the general population.

Pharmacoepidemiologic Evaluation of Birth Defects from Health-Related Postings in Social Media During Pregnancy

Introduction

Adverse effects of medications taken during pregnancy are traditionally studied through post-marketing pregnancy registries, which have limitations. Social media data may be an alternative data source for pregnancy surveillance studies.

Objective

The objective of this study was to assess the feasibility of using social media data as an alternative source for pregnancy surveillance for regulatory decision making.

Methods

We created an automated method to identify Twitter accounts of pregnant women. We identified 196 pregnant women with a mention of a birth defect in relation to their baby and 196 without a mention of a birth defect in relation to their baby. We extracted information on pregnancy and maternal demographics, medication intake and timing, and birth defects.

Results

Although often incomplete, we extracted data for the majority of the pregnancies. Among women that reported birth defects, 35% reported taking one or more medications during pregnancy compared with 17% of controls. After accounting for age, race, and place of residence, a higher medication intake was observed in women who reported birth defects. The rate of birth defects in the pregnancy cohort was lower (0.44%) compared with the rate in the general population (3%).

Conclusions

Twitter data capture information on medication intake and birth defects; however, the information obtained cannot replace pregnancy registries at this time. Development of improved methods to automatically extract and annotate social media data may increase their value to support regulatory decision making regarding pregnancy outcomes in women using medications during their pregnancies.

Use of Therapeutics in Pregnancy and Lactation

This theme issue of Pharmaceutical Research is dedicated to drug research and therapy in pregnant and breastfeeding woman. Enthusiasm for studying drug safety and toxicity in these patients (and in their children) has risen over the past decade. Yet, the accumulation of data is slow. A combined effort of industry, regulators, academia and clinicians can promote the treatment of these populations, as discussed in detail in this issue.