Development and validation of claims-based algorithms for estimating gestational age of spontaneous abortion and termination.

To study the risk of spontaneous abortion (SAB) or termination using healthcare utilization databases, algorithms to estimate the gestational age (GA) are needed. Using Medicaid data, we developed a hierarchical algorithm to classify pregnancy outcomes. We identified the subset of potential SAB and termination cases, and abstracted the GA from linked electronic medical records (gold standard). We developed three approaches: (1) assign median GA for SAB and termination cases in the US; (2) draw a random GA from the population distributions; (3) estimate GA based on regression models. Algorithm performance was assessed based on the proportion of pregnancies with estimated GA within 1-4 weeks of the gold standard, the mean squared error (MSE) and the R-squared. Approach 1 and Approach 3 had similar performance, though approach 3 using random forest models with variables selected via the Boruta algorithm had better MSE and R-squared. For SAB, 58.0% of pregnancies were correctly classified within 2 weeks of the gold standard (MSE: 8.7, R-squared: 0.09). For termination, the proportions were 66.3% (MSE: 11.7; R-squared: 0.35). SABs and terminations can be studied in healthcare utilization data with careful implementation of validated algorithms though higher level of GA misclassification is expected compared to live births.

Development and Validation of Algorithms to Estimate Live Birth Gestational Age in Medicaid Analytic eXtract Data.

BACKGROUND: While healthcare utilization data are useful for postmarketing surveillance of drug safety in pregnancy, the start of pregnancy and gestational age at birth are often incompletely recorded or missing. Our objective was to develop and validate a claims-based live birth gestational age algorithm. METHODS: Using the Medicaid Analytic eXtract (MAX) linked to birth certificates in three states, we developed four candidate algorithms based on: preterm codes; preterm or postterm codes; timing of prenatal care; and prediction models - using conventional regression and machine-learning approaches with a broad range of prespecified and empirically selected predictors. We assessed algorithm performance based on mean squared error (MSE) and proportion of pregnancies with estimated gestational age within 1 and 2 weeks of the gold standard, defined as the clinical or obstetric estimate of gestation on the birth certificate. We validated the best-performing algorithms against medical records in a nationwide sample. We quantified misclassification of select drug exposure scenarios due to estimated gestational age as positive predictive value (PPV), sensitivity, and specificity. RESULTS: Among 114,117 eligible pregnancies, the random forest model with all predictors emerged as the best performing algorithm: MSE 1.5; 84.8% within 1 week and 96.3% within 2 weeks, with similar performance in the nationwide validation cohort. For all exposure scenarios, PPVs were >93.8%, sensitivities >94.3%, and specificities >99.4%. CONCLUSIONS: We developed a highly accurate algorithm for estimating gestational age among live births in the nationwide MAX data, further supporting the value of these data for drug safety surveillance in pregnancy. See video abstract at, http://links.lww.com/EDE/B989 .

Validation of claims-based algorithms to identify non-live birth outcomes.

PURPOSE: Perinatal epidemiology studies using healthcare utilization databases are often restricted to live births, largely due to the lack of established algorithms to identify non-live births. The study objective was to develop and validate claims-based algorithms for the ascertainment of non-live births. METHODS: Using the Mass General Brigham Research Patient Data Registry 2000-2014, we assembled a cohort of women enrolled in Medicaid with a non-live birth. Based on ≥1 inpatient or ≥2 outpatient diagnosis/procedure codes, we identified and randomly sampled 100 potential stillbirth, spontaneous abortion, and termination cases each. For the secondary definitions, we excluded cases with codes for other pregnancy outcomes within ±5 days of the outcome of interest and relaxed the definitions for spontaneous abortion and termination by allowing cases with one outpatient diagnosis only. Cases were adjudicated based on medical chart review. We estimated the positive predictive value (PPV) for each outcome. RESULTS: The PPV was 71.0% (95% CI, 61.1-79.6) for stillbirth; 79.0% (69.7-86.5) for spontaneous abortion, and 93.0% (86.1-97.1) for termination. When excluding cases with adjacent codes for other pregnancy outcomes and further relaxing the definition, the PPV increased to 80.6% (69.5-88.9) for stillbirth, 86.6% (80.5-91.3) for spontaneous abortion and 94.9% (91.1-97.4) for termination. The PPV for the composite outcome using the relaxed definition was 94.4% (92.3-96.1). CONCLUSIONS: Our findings suggest non-live birth outcomes can be identified in a valid manner in epidemiological studies based on healthcare utilization databases.

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 2 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 2 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.

Prevalence of prescription opioid use during pregnancy in eight US health plans during 2001-2014.

PURPOSE: To estimate prevalence of prescription opioid use during pregnancy in eight US health plans during 2001-2014. METHODS: We conducted a cohort study of singleton live birth deliveries. Maternal characteristics were ascertained from health plan and/or birth certificate data and opioids dispensed during pregnancy from health plan pharmacy records. Prevalence of prescription opioid use during pregnancy was calculated for any use, cumulative days of use, and number of dispensings. RESULTS: We examined prevalence of prescription opioid use during pregnancy in each health plan. Tennessee Medicaid had appreciably greater prevalence of use compared to the seven other health plans. Thus, results for the two groups were reported separately. In the seven health plans (n = 587 093 deliveries), prevalence of use during pregnancy was relatively stable at 9%-11% throughout 2001-2014. In Tennessee Medicaid (n = 256 724 deliveries), prevalence increased from 29% in 2001 to a peak of 36%-37% in 2004-2010, and then declined to 28% in 2014. Use for ≥30 days during pregnancy was stable at 1% in the seven health plans and increased from 2% to 7% in Tennessee Medicaid during 2001-2014. Receipt of ≥5 opioid dispensings during pregnancy increased in the seven health plans (0.3%-0.6%) and Tennessee Medicaid (3%-5%) during 2001-2014. CONCLUSION: During 2001-2014, prescription opioid use during pregnancy was more common in Tennessee Medicaid (peak prevalence in late 2000s) compared to the seven health plans (relatively stable prevalence). Although a small percentage of women had opioid use during pregnancy for ≥30 days or ≥ 5 dispensings, they represent thousands of women during 2001-2014.

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.

A quantitative bias analysis of the confounding effects due to smoking on the association between fluoroquinolones and risk of aortic aneurysm.

PURPOSE: Epidemiologic studies consistently report an increased risk of aortic aneurysm (AA) among users of fluoroquinolones (FQ), but confounding by smoking could explain all or some of the observed risk. Therefore, to better elucidate the potential causal impact of FQ on AA, we quantitatively evaluated the potential confounding effect of smoking on this observed association. METHODS: We conducted a series of quantitative bias analyses using three previously published approaches: the E-value approach, the rule-out approach, and the array approach. We additionally conducted a numerical comparison between the rule-out approach and the E-value approach. RESULTS: For an apparent relative risk of 2, the E-value is 3.41, suggesting that smoking needs to be associated with both FQ and AA with a minimal magnitude of 3.41 to explain away the observed twofold FQ-AA association. The array approach found that the prevalence of smoking among FQ users would need to be at least 2.9 times higher (43%) than the nonusers (15%), assuming smoking increases the risk of AA by 7.6-fold. A numerical comparison demonstrated that the results from the rule-out approach are similar to that of the E-value approach when there is a lack of prior data on bias parameters. CONCLUSIONS: Using three different approaches, we demonstrate that the strengths of association between smoking and both FQ and AA need to be unusually strong to fully account for the twofold increased risk between FQ and AA. Therefore, it is unlikely that smoking alone would explain away the association reported in the epidemiologic studies.

Validity of diagnosis and procedure codes for identifying neural tube defects in infants.

PURPOSE: The use of validated criteria to identify birth defects in electronic healthcare databases can avoid the cost and time-intensive efforts required to conduct chart reviews to confirm outcomes. This study evaluated the validity of various case-finding methodologies to identify neural tube defects (NTDs) in infants using an electronic healthcare database. METHODS: This analysis used data generated from a study whose primary aim was to evaluate the association between first-trimester maternal prescription opioid use and NTDs. The study was conducted within the Medication Exposure in Pregnancy Risk Evaluation Program. A broad approach was used to identify potential NTDs including diagnosis and procedure codes from inpatient and outpatient settings, death certificates and birth defect flags in birth certificates. Potential NTD cases were chart abstracted and confirmed by clinical experts. Positive predictive values (PPVs) and 95% confidence intervals (95% CI) are reported. RESULTS: The cohort included 113 168 singleton live-born infants: 55 960 infants with opioid exposure in pregnancy and 57 208 infants unexposed in pregnancy. Seventy-three potential NTD cases were available for the validation analysis. The overall PPV was 41% using all diagnosis and procedure codes plus birth certificates. Restricting approaches to codes recorded in the infants' medical record or to birth certificate flags increased the PPVs (72% and 80%, respectively) but missed a substantial proportion of confirmed NTDs. CONCLUSIONS: Codes in electronic healthcare data did not accurately identify confirmed NTDs. These results indicate that chart review with adjudication of outcomes is important when conducting observational studies of NTDs using electronic healthcare data.

Misclassification in Assessment of First Trimester In-utero Exposure to Drugs Used Proximally to Conception: the Example of Letrozole Utilization for Infertility Treatment.

Letrozole is an aromatase inhibitor that has an unapproved use for ovulation induction with infertility. Because of the proximity of this use to conception, we selected letrozole to study the effect of 3 different methods for identifying the pregnancy start date and their impact on exposure misclassification. Using electronic health data from the US Sentinel database (2001-2015), we identified live-birth pregnancies conceived through in-vitro fertilization or intrauterine insemination. The pregnancy start was calculated using 1) a validated algorithm to estimate the last menstrual period (LMP), 2) LMP + 14 days (i.e., conception estimate), and 3) the fertility-procedure date. We identified 47,628 live-births after intrauterine insemination (n = 24,962) and in-vitro fertilization (n = 22,666), in which 2,458 (5.3%) mothers received letrozole. The algorithm-based conception estimate occurred within 14 days of the fertility procedure for 78.3% of pregnancies. Defining pregnancy start as LMP (45.7/1,000 pregnancies) or LMP + 14 days (12.7/1,000 pregnancies) overestimated letrozole exposure during pregnancy by 8.4-fold and 2.3-fold, respectively, compared with defining it at the date of the fertility procedure (5.5/1,000 pregnancies). While most studies of drug utilization in pregnancy use LMP as the conventional pregnancy start, this introduced substantial exposure misclassification in the example of letrozole. LMP + 14 days was less biased. Researchers should carefully consider the impact of the method for identifying the pregnancy start date on the potential for exposure misclassification.

Incidence of Heart Failure and Cardiomyopathy Following Initiation of Medications for Attention-Deficit/Hyperactivity Disorder: A Descriptive Study.

PURPOSE/BACKGROUND: Stimulant abuse is associated with cardiomyopathy, but cardiomyopathy rates with therapeutic use of stimulants for attention-deficit/hyperactivity disorder (ADHD) are poorly characterized. Labels for methylphenidate, amphetamine, and atomoxetine caution against use in patients with cardiovascular disease. We sought to assess the incidence of new-onset heart failure or cardiomyopathy among initiators of these medications. METHODS/PROCEDURES: Using the Sentinel distributed database, we analyzed new-onset heart failure or cardiomyopathy among initiators of selected ADHD medications (amphetamine products including lisdexamfetamine, methylphenidate, and atomoxetine), by duration of use (0-90, 91-180, 181-270, 271-365, 366-730, and 731-1095 days) and age group (<22, 22-44, 45-64, and ≥65 years). FINDINGS/RESULTS: In our sample of 2,012,948 initiators of ADHD medications, 44.6% were female, and 54.1% were younger than 22 years. Heart failure/cardiomyopathy rates in the age groups younger than 22 and 22 to 44 years old were less than 50 per 10,000 person-years, without clear trends by duration of use. The highest rates occurred soon after treatment initiation in the age group 65 years or older, with 1 case per 10.5 person-years of follow-up, or 950 cases per 10,000 person-years, for days 0-90. IMPLICATIONS/CONCLUSIONS: Heart failure/cardiomyopathy rates were not higher over 3 years of ADHD medication use compared with shorter-term treatment. In older age groups, lower rates later in treatment could reflect depletion of patients predisposed to the outcome if they develop it soon after starting treatment.

Utilization of drugs with pregnancy exposure registries during pregnancy.

PURPOSE: To describe the utilization of drugs with pregnancy exposure registries by trimester during pregnancy, in comparison with matched nonpregnant episodes and a pre-pregnancy period. METHODS: We identified live-born deliveries from women aged 10 to 54 years and matched the pregnancies 1:1 with nonpregnant episodes from a comparator cohort not delivering live-born infants, using data from 2001 to 2013 in the Sentinel Distributed Database. We evaluated the utilization of 34 drugs with pregnancy exposure registries, comparing utilization during pregnancy to the matched nonpregnant episodes, and to the 90 days before pregnancy. RESULTS: We identified 1 895 597 pregnancies ending in live births in 1 598 697 women and 1 895 597 matched nonpregnant episodes in 1 582 581 women. We observed a lower prevalence of use for most drugs during pregnancy compared with the matched nonpregnant episodes, and the 90-day pre-pregnancy period. The median (interquartile range) prevalence ratio of use, at any time during pregnancy, for all products was 0.2 (0.1-0.3) comparing pregnant to nonpregnant episodes. Overall, there was a decrease in drug utilization by trimester; from 2.6% in the 90 days preceding pregnancy to 2.1% in the first trimester, 1.1% in the second trimester, and 0.9% in the third trimester. CONCLUSIONS: Among drugs with pregnancy exposure registries, use was less during pregnancy compared with before pregnancy and to the matched nonpregnant episodes. The lower utilization during pregnancy suggests that women may be avoiding these drugs to minimize potentially harmful exposure during pregnancy. This lower utilization may increase the challenges of further studying the safety of these drugs using pregnancy exposure registries.

Overall and cause-specific mortality in the Sentinel system: A power analysis.

PURPOSE: Mortality data within the Sentinel Death Tables remain generally uncharacterized. Assessment of mortality data within Sentinel will help inform its utility for medical product safety studies. METHODS: To determine if Sentinel contains sufficient all-cause and cause-specific mortality events to power postmarketing safety studies. We calculated crude rates of all-cause mortality and suicide and proportional mortality from suicide from 2004 to 2012 in seven Sentinel data partners. Results were stratified by data partner, sex, age group, and calendar year and compared with national estimates from Centers for Disease Control and Prevention Wide-ranging ONline Data for Epidemiologic Research. We performed sample size estimations for all-cause mortality and 10 leading causes of death. RESULTS: We observed 479 694 deaths, including 5811 suicides, during 68 million person-years of follow-up. Pooled mean death and suicide rates in the data partners were 710 and 8.6 per 100 000 person-years, respectively (vs 810 and 11.8 nationally). The mean proportional mortality from suicide among the data partners was 1.2%, compared with 1.5% nationally. National trends of decreasing overall mortality and increasing proportional mortality for suicide were reflected within Sentinel. We estimated that detecting hazard ratios of 1.25 and 3 would require 16 442 and 460 exposed patients, respectively, for overall mortality, and 1.3 million and 37 411, respectively, for suicide. CONCLUSIONS: This was the first study to investigate mortality data in the Sentinel death tables. We found that all-cause mortality appeared well powered for use as a safety outcome and cause-specific mortality outcomes may be adequately powered in certain circumstances. Further investigation into the quality of the Sentinel death data is needed.

A systematic review of pregnancy exposure registries: examination of protocol-specified pregnancy outcomes, target sample size, and comparator selection.

PURPOSE: Our study sought to systematically evaluate protocol-specified study methodology in prospective pregnancy exposure registries including pre-specified pregnancy outcomes, power calculations for sample size, and comparator group selection. METHODS: U.S. pregnancy exposure registries designed to evaluate safety of drugs or biologics were identified from www.clinicaltrials.gov, the FDA's Office of Women's Health website, and the FDA's list of postmarketing studies. Protocols or similar documentation were obtained. RESULTS: We identified 35 U.S. registries for drugs or biologic use during pregnancy. All registries assessed risk for overall major congenital malformations. Pre-specified target enrollment was stated for 18 (51%) registries, and ranged from 150 to 500 exposed pregnancies (median 300). Thirty-two (91%) registries identified at least one comparison group, but only nine (26%) planned to use an internal comparator. The most common external comparator group (n = 24, 69%) was the Metropolitan Atlanta Congenital Defects Program (MACDP). CONCLUSIONS: No registries were designed to have sufficient power to assess specific malformations, despite the plausibility that most teratogens cause specific defects. Only half of the registries included a power analysis. Despite their common use, external comparators, including MACDP, have important limitations. In the absence of randomized controlled trial data in pregnant women, pregnancy registries remain an important tool as part of a comprehensive pregnancy surveillance program; however, pregnancy registries alone may not be sufficient to obtain adequate data regarding risks of specific malformations. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Antiemetic use among pregnant women in the United States: the escalating use of ondansetron.

PURPOSE: To examine ondansetron use in pregnancy in the context of other antiemetic use among a large insured United States population of women delivering live births. METHODS: We assessed ondansetron and other antiemetic use among pregnant women delivering live births between 2001 and 2015 in 15 data partners contributing data to the Mini-Sentinel Distributed Database. We identified live birth pregnancies using a validated algorithm, and all forms of ondansetron and other available antiemetics were identified using National Drug Codes or procedure codes. We assessed the prevalence of antiemetic use by trimester, calendar year, and formulation. RESULTS: In over 2.3 million pregnancies, the prevalence of ondansetron, promethazine, metoclopramide, or doxylamine/pyridoxine use anytime in pregnancy was 15.2, 10.3, 4.0, and 0.4%, respectively. Ondansetron use increased from <1% of pregnancies in 2001 to 22.2% in 2014, with much of the increase attributable to oral ondansetron beginning in 2006. Promethazine and metoclopramide use increased modestly between 2001 (13.8%, 3.2%) and 2006 (16.0%, 6.0%) but decreased annually through 2014 (8.0%, 3.2%). Doxylamine/pyridoxine, approved for management of nausea and vomiting in pregnancy in 2013, was used in 1.8% of pregnancies in 2014. For all antiemetics, use was highest in the first trimester. CONCLUSIONS: We observed a marked increase in ondansetron use by study year, prescribed to nearly one-quarter of insured pregnant women in 2014, occurring in conjunction with decreased use of promethazine and metoclopramide. Given the widespread use of ondansetron in pregnancy, data establishing product efficacy and methodologically rigorous evaluation of post-marketing safety are needed. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Development of a mother-child database for drug exposure and adverse event detection in the Military Health System.

PURPOSE: The aim of this study was to develop a mother-child linked database consisting of all eligible active duty military personnel, retirees, and their dependents in order to conduct medication-related analyses to improve the safety and quality of care in the Military Health System (MHS). METHODS: Eligible women of reproductive age with at least one pregnancy-related encounter between January 2005 and December 2013 receiving care in the MHS were included in the study population. Building on previously published algorithms, we used pregnancy-related diagnostic and procedure codes, parameterized temporal constraints, and data elements unique to the MHS to identify pregnancies ending in live births, stillbirth, spontaneous abortion, or ectopic pregnancy. Pregnancies ending in live births were matched to presumptive offspring using birth dates and family-based sponsorship identification. Antidepressant and antiepileptic use during pregnancy was evaluated using electronic pharmacy data. RESULTS: Algorithms identified 755,232 women who experienced 1,099,648 complete pregnancies with both pregnancy care encounter and pregnancy outcome. Of the 924,320 live birth pregnancies, 827,753 (90.0%) were matched to offspring. Algorithms also identified 5,663 stillbirths, 11,358 ectopic pregnancies, and 169,665 spontaneous abortions. Among the matched singleton live birth pregnancies, 7.1% of mothers were dispensed an antidepressant at any point during pregnancy, usually a selective serotonin reuptake inhibitor, (75.3%), whereas 1.3% of mothers were dispensed an antiepileptic drug.

Considerations for practical use of tree-based scan statistics for signal detection using electronic healthcare data: a case study with insulin glargine.

BACKGROUND: Hypothesis-free signal detection (HFSD) methods such as tree-based scan statistics (TBSS) applied to longitudinal electronic healthcare data (EHD) are increasingly used in safety monitoring. However, challenges may arise in interpreting HFSD results alongside results from disproportionality analysis of spontaneous reporting. RESEARCH DESIGN AND METHODS: Using the anti-diabetes drug insulin glargine (Lantus®) we apply two different tree-based scan designs using TreeScan™ software on retrospective EHD and compare the results to one another as well as to results from a disproportionality analysis using SRD. RESULTS: The self-controlled tree temporal scan method produced the larger number of alerts relative to propensity-score matched approach; however, far fewer alerts were observed when analyses were limited to EHD in inpatient/emergency room settings only. Very few reference adverse events were observed using TBSS methods on EHD relative to disproportionality methods in SRD. CONCLUSION: Differences in detected alerts between TBSS methods and between TBSS and disproportionality analysis of SRD are likely attributable to differences in data, comparator, and study design. Our results suggest that HFDS methods like TBSS applied to EHD may complement more traditional approaches such as disproportionality analysis of SRD to provide a more complete picture of product safety in the post-approval setting.

Acetaminophen overdose in the Military Health System.

PURPOSE: We report the annual trend, distribution, and determinants of acetaminophen overdose using data from the Military Health System. We also assess the proportion of individuals with an acetaminophen overdose who received a prescription for any acetaminophen-containing medication prior to their event. METHODS: Diagnostic International Classification of Diseases, 9th revision (ICD-9) codes from inpatient medical encounters were used to identify patients with acetaminophen overdose. We used Poisson regression to estimate adjusted prevalence ratios (aPRs) for associations between selected socio-demographic characteristics and acetaminophen overdose. Pharmacy records for individuals with an acetaminophen overdose were obtained to evaluate the proportion who received a prescription for any acetaminophen-containing medication prior to their overdose. RESULTS: Annual age-adjusted and sex-adjusted prevalence of acetaminophen overdose increased by 38.5% from 2004 to 2008. Acetaminophen overdose was significantly more common in female subjects than in male subjects (aPR = 3.24, 95%CI = 2.97-3.55). Individuals aged 15-17 and 18-24 also were significantly more likely to have an overdose compared with those aged 45-64 (aPR = 6.06, 95%CI = 5.25-7.00 and aPR = 4.58, 95%CI = 4.01-5.23, respectively). Among active duty service members, acetaminophen overdose was six times more common in junior enlisted service members than in officers (aPR = 6.06, 95%CI = 3.90-9.40). The proportion of individuals with an inpatient overdose who had any prescription for an acetaminophen-containing medication in the 365, 30, and 7 days before the overdose was 53.3%, 23.7%, and 16.3%, respectively. CONCLUSIONS: Identification of at-risk populations will aid the military in ongoing efforts to decrease medication misuse. Findings suggest a potential need for improved labeling of over-the-counter medications and medication safety education efforts for unintentional acetaminophen overdose and continued efforts to identify individuals at risk for intentional overdose. Published 2012. This article is a US Government work and is in the public domain in the USA.

The emerging role of real-world data in advanced breast cancer therapy: Recommendations for collaborative decision-making.

Among stakeholders and decision-makers in advanced breast cancer, the demand for insights from real-world data (RWD) is increasing. Although RWD can be used to support decisions throughout different stages of a breast cancer drug's life cycle, barriers exist to its use and acceptance. We propose a collaborative approach to generating and using RWD that is meaningful to multiple stakeholders, and encourage frameworks toward international guidelines to help standardize RWD methodologies to achieve more efficient use of RWD insights.

Use of oral contraceptives in pregnancy and major structural birth defects in offspring.

BACKGROUND: Oral contraceptives (OCs) are the most commonly used reversible contraceptive method among US women. Although the majority of previous studies have reported no association between OC use during pregnancy and birth defects, some studies have reported increased occurrence of neural tube defects, limb reduction defects, and urinary tract anomalies. METHODS: We assessed OC use among mothers who participated in the multisite, case-control, National Birth Defects Prevention Study. Mothers of 9986 infants with 32 types of birth defects and 4000 infants without birth defects were included. RESULTS: Maternal OC use during the first 3 months of pregnancy was associated with an increased odds ratio for 2 of 32 birth defects: hypoplastic left heart syndrome (adjusted odds ratio = 2.3 [95% confidence interval = 1.3-4.3) and gastroschisis (1.8 [1.3-2.7]). CONCLUSION: Previous reports of associations between OC use and specific types of anomalies were not corroborated. Given that associations were assessed for 32 types of birth defects, our findings of 2 increased associations between OC use and gastroschisis and hypoplastic left heart syndrome should be interpreted as hypotheses until they can be evaluated further. Overall, our findings are consistent with the majority of previous studies that found women who use OCs during early pregnancy have no increased risk for most types of major congenital malformations.

Antipsychotic Use and Stroke: A Retrospective Comparative Study in a Non-Elderly Population.

OBJECTIVE: To evaluate stroke risk among users of typical antipsychotics compared to users of atypical antipsychotics in a non-elderly and non-demented US population. METHODS: New users of antipsychotics aged 18-64 years without dementia were identified via electronic health care data from 13 health plans participating in the Sentinel System from January 2001 to September 2015. The risk of hospitalized stroke events, identified via ICD-9-CM diagnostic criteria, was compared between typical and atypical antipsychotic users using 1:1 matching on propensity score. Adjusted hazard ratios (HRs) and 95% CIs during the entire follow-up period and during 1- to 15-day and 16- to 90-day risk windows were estimated. The risk associated with haloperidol use was estimated separately. RESULTS: A total of 45,495 typical antipsychotic users were matched 1:1 to atypical antipsychotic users. While unmatched HRs suggest an increased stroke risk among typical antipsychotic users compared to atypical antipsychotic users, no increased risk was observed after matching during the entire follow-up period (HR = 0.87; 95% CI, 0.54-1.41), the 1- to 15-day risk window (HR = 1.16; 95% CI, 0.41-3.32), or the 16- to 90-day risk window (HR = 0.52; 95% CI, 0.20-1.36). The adjusted HR for haloperidol was 1.31 (95% CI, 0.54-3.21). CONCLUSION: These findings were not suggestive of an increased stroke risk in typical antipsychotic users compared to atypical antipsychotic users in a non-elderly and non-demented population.