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Purpose: To assess the prevalence and potential indications of PDE5 inhibitor use among pregnant and reproductive‐age women in the United States. Methods: We identified women 15 to 50 years with a livebirth from January 2001 through March 2018 in Sentinel Database. We assessed the prevalence of PDE5 inhibitor use prior to and during pregnancy by trimester, identified potential on‐ and off‐label indications using predefined diagnosis codes recorded within 90 days before the estimated last menstrual period through delivery. Separately, we used data from IQVIA's National Prescription Audit and Total Patient Tracker to estimate the dispensed prescriptions for PDE5 inhibitors and the number of patients with PDE5 inhibitor prescriptions. Results: We identified approximately 3.3 million pregnancies during 2001 to 2018, 96 of which had PDE5 inhibitor use during pregnancy. Prevalence of PDE5 inhibitor use was 2.61, 0.62, and 0.62 per 100, 000 live‐born pregnancies during the first, second, or third trimesters, respectively. Among women exposed to a PDE5 inhibitor from 90 days before conception to the end of pregnancy, 25.0%, 31.1%, and 15.5% had a diagnosis code for fetal growth restriction, preeclampsia, and pulmonary arterial hypertension. In IQVIA data, an estimated 223, 000 prescriptions from July 2015 through June 2018 and 58, 000 women received prescriptions for PDE5 inhibitors in 2017, of whom approximately 15, 000 (26%) were aged 15 to 50 years. Conclusion: We found a low prevalence of PDE5 inhibitor use in pregnant and reproductive‐age women. Given the very low prevalence of use and the inconsistency of neonatal mortality data across STRIDER centers, the risk to public health is low at present. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: To replicate the well-established association between angiotensinconverting enzyme inhibitors versus beta blockers and angioedema in the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) era. Methods: We conducted a retrospective, inception cohort study in a large insurance database formatted to the Sentinel Common Data Model. We defined study periods spanning the ICD-9-CM era only, ICD-10-CM era only, and ICD-9-CM and ICD-10-CM era and conducted simple-forward mapping (SFM), simple-backward mapping (SBM), and forward-backward mapping (FBM) referencing the General Equivalence Mappings to translate the outcome (angioedema) and covariates from ICD-9-CM to ICD-10-CM. We performed propensity score (PS)-matched and PSstratified Cox proportional hazards regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: In the ICD-9-CM and ICD-10-CM eras spanning April 1 to September 30 of 2015 and 2016, there were 152 017 and 145 232 angiotensin-converting enzyme inhibitor initiators and 115 073 and 116 652 beta-blocker initiators, respectively. The PS-matched HR was 4.19 (95% CI, 2.82-6.23) in the ICD-9-CM era, 4.37 (2.92-6.52) in the ICD-10-CM era using SFM, and 4.64 (3.05-7.07) in the ICD-10-CM era using SBM and FBM. The PS-matched HRs from the mixed ICD-9-CM and ICD-10-CM eras ranged from 3.91 (2.69-5.68) to 4.35 (3.33-5.70). Conclusion: The adjusted HRs across different diagnostic coding eras and the use of SFM versus SBM and FBM produced numerically different but clinically similar results. Additional investigations as ICD-10-CM data accumulate are warranted. [ABSTRACT FROM AUTHOR]

Purpose: To describe the consistency in the frequency of 5 health outcomes across the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and Tenth Revision, Clinical Modification (ICD-10-CM) eras in the US. Methods: We examined the incidence of 3 acute conditions (acute myocardial infarction [AMI], angioedema, ischemic stroke) and the prevalence of 2 chronic conditions (diabetes, hypertension) during the final 5 years of the ICD-9-CM era (January 2010-September 2015) and the first 15 months of the ICD-10-CM era (October 2015-December 2016) in 13 electronic health care databases in the Sentinel System. For each health outcome reviewed during the ICD-10-CM era, we evaluated 4 definitions, including published algorithms derived from other countries, as well as simple-forward, simple-backward, and forward-backward mapping using the General Equivalence Mappings. For acute conditions, we also compared the incidence between April to December 2014 and April to December 2016. Results: The analyses included data from approximately 172 million health plan members. While the incidence or prevalence of AMI and hypertension performed similarly across the 2 eras, the other 3 outcomes did not demonstrate consistent trends for some or all the ICD-10-CM definitions assessed. Conclusions: When using data from both the ICD-9-CM and ICD-10-CM eras, or when using results from ICD-10-CM data to compare to results from ICD-9-CM data, researchers should test multiple ICD-10-CM outcome definitions as part of sensitivity analysis. Ongoing assessment of the impact of ICD-10-CM transition on identification of health outcomes in US electronic health care databases should occur as more data accrue. [ABSTRACT FROM AUTHOR]