Targeted Learning with an Undersmoothed Lasso Propensity Score Model for Large-Scale Covariate Adjustment in Healthcare Database Studies.

Lasso regression is widely used for large-scale propensity score (PS) estimation in healthcare database studies. In these settings, previous work has shown that undersmoothing (overfitting) Lasso PS models can improve confounding control, but it can also cause problems of non-overlap in covariate distributions. It remains unclear how to select the degree of undersmoothing when fitting large-scale Lasso PS models to improve confounding control while avoiding issues that can result from reduced covariate overlap. Here, we used simulations to evaluate the performance of using collaborative-controlled targeted learning to data-adaptively select the degree of undersmoothing when fitting large-scale PS models within both singly and doubly robust frameworks to reduce bias in causal estimators. Simulations showed that collaborative learning can data-adaptively select the degree of undersmoothing to reduce bias in estimated treatment effects. Results further showed that when fitting undersmoothed Lasso PS-models, the use of cross-fitting was important for avoiding non-overlap in covariate distributions and reducing bias in causal estimates.

Validity of inpatient electronic health record-based measures of oxygen-related therapy in the United States: Lessons applicable for studying COVID-19 endpoints.

INTRODUCTION: During the COVID-19 pandemic, inpatient electronic health records (EHRs) have been used to conduct public health surveillance and assess treatments and outcomes. Invasive mechanical ventilation (MV) and supplemental oxygen (O2) use are markers of severe illness in hospitalized COVID-19 patients. In a large US system (n = 142 hospitals), we assessed documentation of MV and O2 use during COVID-19 hospitalization in administrative data versus nursing documentation. METHODS: We identified 319 553 adult hospitalizations with a COVID-19 diagnosis, February 2020-October 2022, and extracted coded, administrative data for MV or O2. Separately, we developed classification rules for MV or O2 supplementation from semi-structured nursing documentation. We assessed MV and O2 supplementation in administrative data versus nursing documentation and calculated ordinal endpoints of decreasing COVID-19 disease severity. Nursing documentation was considered the gold standard in sensitivity and positive predictive value (PPV) analyses. RESULTS: In nursing documentation, the prevalence of MV and O2 supplementation among COVID-19 hospitalizations was 14% and 75%, respectively. The sensitivity of administrative data was 83% for MV and 41% for O2, with both PPVs above 91%. Concordance between sources was 97% for MV (κ = 0.85), and 54% for O2 (κ = 0.21). For ordinal endpoints, administrative data accurately identified intensive care and MV but underestimated hospitalizations with O2 requirements (42% vs. 18%). CONCLUSIONS: In comparison to nursing documentation, administrative data under-ascertained O2 supplementation but accurately estimated severe endpoints such as MV. Nursing documentation improved ascertainment of O2 among COVID-19 hospitalizations and can capture oxygen requirements in adults hospitalized with COVID-19 or other respiratory illnesses.

Switching patterns of immediate-release forms of generic mixed amphetamine salts products among privately and publicly insured individuals aged 15-64 years in the United States, 2013-2019.

PURPOSE: Immediate-release forms of generic mixed amphetamine salts (MAS) have been the subject of passive surveillance reports signaling lack of effectiveness. We examined switching patterns that might suggest whether long-term users of specific MAS are more likely to switch away or switch back after use of the MAS of interest in the FDA's Sentinel Distributed Database. METHODS: We required at least 60-day continuous supply of selected MAS grouped by Abbreviated New Drug Application (ANDA) to describe patterns of switching away from and to generics approved under the ANDAs of interest among individuals ages 15-64 years with attention deficit hyperactivity disorder or narcolepsy during 2013-2019. RESULTS: We observed the greatest number of treatment episodes for ANDA 040422 (n = 525 771), followed by ANDA 202424 (n = 181 693), ANDA 040439 (n = 62 363), ANDA 040440 (n = 21 143), and ANDA 040480 (n = 8792). Of those with switches away from their original ANDA, episodes initiated on generic products under ANDA 040422 (48.6%) and ANDA 202424 (43.0%) were most likely to switch back, while those initiated on generic product under ANDA 040480 were least likely (24.1%). Of those episodes with switches to a generic under an ANDA of interest, about one-third (range 27.1% to 37.0%) switched back to the same product. These switches back had a median time to switch of about 30 days. CONCLUSIONS: These descriptive analyses, although subject to limitations, did not suggest increased switching away or switching back after use of the generics of interest. Continued post-marketing surveillance is warranted.

Evaluating Confounding Control in Estimations of Influenza Antiviral Effectiveness in Electronic Health Plan Data.

Observational studies of oseltamivir use and influenza complications could suffer from residual confounding. Using negative control risk periods and a negative control outcome, we examined confounding control in a health-insurance-claims-based study of oseltamivir and influenza complications (pneumonia, all-cause hospitalization, and dispensing of an antibiotic). Within the Food and Drug Administration's Sentinel System, we identified individuals aged ≥18 years who initiated oseltamivir use on the influenza diagnosis date versus those who did not, during 3 influenza seasons (2014-2017). We evaluated primary outcomes within the following 1-30 days (the primary risk period) and 61-90 days (the negative control period) and nonvertebral fractures (the negative control outcome) within days 1-30. We estimated propensity-score-matched risk ratios (RRs) per season. During the 2014-2015 influenza season, oseltamivir use was associated with a reduction in the risk of pneumonia (RR = 0.72, 95% confidence interval (CI): 0.70, 0.75) and all-cause hospitalization (RR = 0.54, 95% CI: 0.53, 0.55) in days 1-30. During days 61-90, estimates were near-null for pneumonia (RR = 1.04, 95% CI: 0.95, 1.15) and hospitalization (RR = 0.94, 95% CI: 0.91, 0.98) but slightly increased for antibiotic dispensing (RR = 1.14, 95% CI: 1.08, 1.21). The RR for fractures was near-null (RR = 1.09, 95% CI: 0.99, 1.20). Estimates for the 2016-2017 influenza season were comparable, while the 2015-2016 season had conflicting results. Our study suggests minimal residual confounding for specific outcomes, but results differed by season.

Validation of diagnosis codes to identify hospitalized COVID-19 patients in health care claims data.

PURPOSE: Health plan claims may provide complete longitudinal data for timely, real-world population-level COVID-19 assessment. However, these data often lack laboratory results, the standard for COVID-19 diagnosis. METHODS: We assessed the validity of ICD-10-CM diagnosis codes for identifying patients hospitalized with COVID-19 in U.S. claims databases, compared to linked laboratory results, among six Food and Drug Administration Sentinel System data partners (two large national insurers, four integrated delivery systems) from February 20-October 17, 2020. We identified patients hospitalized with COVID-19 according to five ICD-10-CM diagnosis code-based algorithms, which included combinations of codes U07.1, B97.29, general coronavirus codes, and diagnosis codes for severe symptoms. We calculated the positive predictive value (PPV) and sensitivity of each algorithm relative to laboratory test results. We stratified results by data source type and across three time periods: February 20-March 31 (Time A), April 1-30 (Time B), May 1-October 17 (Time C). RESULTS: The five algorithms identified between 34 806 and 47 293 patients across the study periods; 23% with known laboratory results contributed to PPV calculations. PPVs were high and similar across algorithms. PPV of U07.1 alone was stable around 93% for integrated delivery systems, but declined over time from 93% to 70% among national insurers. Overall PPV of U07.1 across all data partners was 94.1% (95% CI, 92.3%-95.5%) in Time A and 81.2% (95% CI, 80.1%-82.2%) in Time C. Sensitivity was consistent across algorithms and over time, at 94.9% (95% CI, 94.2%-95.5%). CONCLUSION: Our results support the use of code U07.1 to identify hospitalized COVID-19 patients in U.S. claims data.

Association of COVID-19 vs Influenza With Risk of Arterial and Venous Thrombotic Events Among Hospitalized Patients.

Importance: The incidence of arterial thromboembolism and venous thromboembolism in persons with COVID-19 remains unclear. Objective: To measure the 90-day risk of arterial thromboembolism and venous thromboembolism in patients hospitalized with COVID-19 before or during COVID-19 vaccine availability vs patients hospitalized with influenza. Design, Setting, and Participants: Retrospective cohort study of 41 443 patients hospitalized with COVID-19 before vaccine availability (April-November 2020), 44 194 patients hospitalized with COVID-19 during vaccine availability (December 2020-May 2021), and 8269 patients hospitalized with influenza (October 2018-April 2019) in the US Food and Drug Administration Sentinel System (data from 2 national health insurers and 4 regional integrated health systems). Exposures: COVID-19 or influenza (identified by hospital diagnosis or nucleic acid test). Main Outcomes and Measures: Hospital diagnosis of arterial thromboembolism (acute myocardial infarction or ischemic stroke) and venous thromboembolism (deep vein thrombosis or pulmonary embolism) within 90 days. Outcomes were ascertained through July 2019 for patients with influenza and through August 2021 for patients with COVID-19. Propensity scores with fine stratification were developed to account for differences between the influenza and COVID-19 cohorts. Weighted Cox regression was used to estimate the adjusted hazard ratios (HRs) for outcomes during each COVID-19 vaccine availability period vs the influenza period. Results: A total of 85 637 patients with COVID-19 (mean age, 72 [SD, 13.0] years; 50.5% were male) and 8269 with influenza (mean age, 72 [SD, 13.3] years; 45.0% were male) were included. The 90-day absolute risk of arterial thromboembolism was 14.4% (95% CI, 13.6%-15.2%) in patients with influenza vs 15.8% (95% CI, 15.5%-16.2%) in patients with COVID-19 before vaccine availability (risk difference, 1.4% [95% CI, 1.0%-2.3%]) and 16.3% (95% CI, 16.0%-16.6%) in patients with COVID-19 during vaccine availability (risk difference, 1.9% [95% CI, 1.1%-2.7%]). Compared with patients with influenza, the risk of arterial thromboembolism was not significantly higher among patients with COVID-19 before vaccine availability (adjusted HR, 1.04 [95% CI, 0.97-1.11]) or during vaccine availability (adjusted HR, 1.07 [95% CI, 1.00-1.14]). The 90-day absolute risk of venous thromboembolism was 5.3% (95% CI, 4.9%-5.8%) in patients with influenza vs 9.5% (95% CI, 9.2%-9.7%) in patients with COVID-19 before vaccine availability (risk difference, 4.1% [95% CI, 3.6%-4.7%]) and 10.9% (95% CI, 10.6%-11.1%) in patients with COVID-19 during vaccine availability (risk difference, 5.5% [95% CI, 5.0%-6.1%]). Compared with patients with influenza, the risk of venous thromboembolism was significantly higher among patients with COVID-19 before vaccine availability (adjusted HR, 1.60 [95% CI, 1.43-1.79]) and during vaccine availability (adjusted HR, 1.89 [95% CI, 1.68-2.12]). Conclusions and Relevance: Based on data from a US public health surveillance system, hospitalization with COVID-19 before and during vaccine availability, vs hospitalization with influenza in 2018-2019, was significantly associated with a higher risk of venous thromboembolism within 90 days, but there was no significant difference in the risk of arterial thromboembolism within 90 days.

Validation of an electronic algorithm for Hodgkin and non-Hodgkin lymphoma in ICD-10-CM.

PURPOSE: Lymphoma is a health outcome of interest for drug safety studies. Studies using administrative claims data require the accurate identification of lymphoma cases. We developed and validated an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify lymphoma in healthcare claims data. METHODS: We developed a three-component algorithm to identify patients aged ≥15 years who were newly diagnosed with Hodgkin (HL) or non-Hodgkin (NHL) lymphoma from January 2016 through July 2018 among members of four Data Partners within the FDA's Sentinel System. The algorithm identified potential cases as patients with ≥2 ICD-10-CM lymphoma diagnosis codes on different dates within 183 days; ≥1 procedure code for a diagnostic procedure (e.g., biopsy, flow cytometry) and ≥1 procedure code for a relevant imaging study within 90 days of the first lymphoma diagnosis code. Cases identified by the algorithm were adjudicated via chart review and a positive predictive value (PPV) was calculated. RESULTS: We identified 8723 potential lymphoma cases via the algorithm and randomly sampled 213 for validation. We retrieved 138 charts (65%) and adjudicated 134 (63%). The overall PPV was 77% (95% confidence interval: 69%-84%). Most cases also had subtype information available, with 88% of cases identified as NHL and 11% as HL. CONCLUSIONS: Seventy-seven percent of lymphoma cases identified by an algorithm based on ICD-10-CM diagnosis and procedure codes and applied to claims data were true cases. This novel algorithm represents an efficient, cost-effective way to target an important health outcome of interest for large-scale drug safety and public health surveillance studies.

Understanding utilization patterns of biologics and biosimilars in the United States to support postmarketing studies of safety and effectiveness.

PURPOSE: To describe utilization of filgrastim and infliximab, the first two products with biosimilars approved in the United States. METHODS: We identified use of filgrastim (reference, tbo-filgrastim, and filgrastim-sndz) and infliximab (reference, infliximab-dyyb, and infliximab-abda) in the Sentinel Distributed Database using Healthcare Common Procedure Coding System (HCPCS) codes and National Drug Codes (NDCs) from January 2015 to August 2018. We calculated the proportion of use by code type and assessed uptake over time. We compared baseline patient characteristics and treatment indications. Among patients with >1 exposure episode, we characterized gaps between episodes. RESULTS: Use was identified primarily via HCPCS codes (filgrastim: 86.4%-97.7%; infliximab: 87.8%-100%) although some was identified via NDCs (filgrastim: 2.2%-13.5%; infliximab: <0.1%-6.5%). Filgrastim reference product use declined from 89.4% in January 2015 to 30.3% in June 2018, with corresponding increases in filgrastim-sndz (0% to 49.3%) and tbo-filgrastim (10.6% to 20.4%). Infliximab biosimilar uptake was low (9.7% in June 2018). We identified 94 846 filgrastim reference product, 27 143 tbo-filgrastim, and 38 264 filgrastim-sndz users. For infliximab, we identified 125 412 reference product, 1034 infliximab-dyyb, 49 infliximab-abda, and 4855 undetermined biosimilar users. Patients receiving filgrastim products were largely similar, but differences in age, sex, and indication were observed across infliximab product users. The median exposure episode gap ranged from 1 to 3 days for filgrastim and 48 to 50 days for infliximab. CONCLUSION: Use of biosimilar filgrastim has increased in the United States, but infliximab biosimilar use remains low. Data on identification of biosimilars in claims data and observed gaps between exposure episodes can be used to support drug safety studies of biosimilars.

Comparative effectiveness of generic and brand-name medication use: A database study of US health insurance claims.

BACKGROUND: To the extent that outcomes are mediated through negative perceptions of generics (the nocebo effect), observational studies comparing brand-name and generic drugs are susceptible to bias favoring the brand-name drugs. We used authorized generic (AG) products, which are identical in composition and appearance to brand-name products but are marketed as generics, as a control group to address this bias in an evaluation aiming to compare the effectiveness of generic versus brand medications. METHODS AND FINDINGS: For commercial health insurance enrollees from the US, administrative claims data were derived from 2 databases: (1) Optum Clinformatics Data Mart (years: 2004-2013) and (2) Truven MarketScan (years: 2003-2015). For a total of 8 drug products, the following groups were compared using a cohort study design: (1) patients switching from brand-name products to AGs versus generics, and patients initiating treatment with AGs versus generics, where AG use proxied brand-name use, addressing negative perception bias, and (2) patients initiating generic versus brand-name products (bias-prone direct comparison) and patients initiating AG versus brand-name products (negative control). Using Cox proportional hazards regression after 1:1 propensity-score matching, we compared a composite cardiovascular endpoint (for amlodipine, amlodipine-benazepril, and quinapril), non-vertebral fracture (for alendronate and calcitonin), psychiatric hospitalization rate (for sertraline and escitalopram), and insulin initiation (for glipizide) between the groups. Inverse variance meta-analytic methods were used to pool adjusted hazard ratios (HRs) for each comparison between the 2 databases. Across 8 products, 2,264,774 matched pairs of patients were included in the comparisons of AGs versus generics. A majority (12 out of 16) of the clinical endpoint estimates showed similar outcomes between AGs and generics. Among the other 4 estimates that did have significantly different outcomes, 3 suggested improved outcomes with generics and 1 favored AGs (patients switching from amlodipine brand-name: HR [95% CI] 0.92 [0.88-0.97]). The comparison between generic and brand-name initiators involved 1,313,161 matched pairs, and no differences in outcomes were noted for alendronate, calcitonin, glipizide, or quinapril. We observed a lower risk of the composite cardiovascular endpoint with generics versus brand-name products for amlodipine and amlodipine-benazepril (HR [95% CI]: 0.91 [0.84-0.99] and 0.84 [0.76-0.94], respectively). For escitalopram and sertraline, we observed higher rates of psychiatric hospitalizations with generics (HR [95% CI]: 1.05 [1.01-1.10] and 1.07 [1.01-1.14], respectively). The negative control comparisons also indicated potentially higher rates of similar magnitude with AG compared to brand-name initiation for escitalopram and sertraline (HR [95% CI]: 1.06 [0.98-1.13] and 1.11 [1.05-1.18], respectively), suggesting that the differences observed between brand and generic users in these outcomes are likely explained by either residual confounding or generic perception bias. Limitations of this study include potential residual confounding due to the unavailability of certain clinical parameters in administrative claims data and the inability to evaluate surrogate outcomes, such as immediate changes in blood pressure, upon switching from brand products to generics. CONCLUSIONS: In this study, we observed that use of generics was associated with comparable clinical outcomes to use of brand-name products. These results could help in promoting educational interventions aimed at increasing patient and provider confidence in the ability of generic medicines to manage chronic diseases.

A Survey of Patients' Perceptions of Pill Appearance and Responses to Changes in Appearance for Four Chronic Disease Medications.

BACKGROUND: Generic versions of a drug can vary in appearance, which can impact adherence. OBJECTIVE: To assess the preferences, perceptions, and responses of patients who experienced a change in the appearance of a generic medication. DESIGN: Cross-sectional survey of patients from a large commercial health plan. PARTICIPANTS: Adults receiving generic versions of lisinopril, fluoxetine, lamotrigine, or simvastatin who experienced a change in the color or shape of their pills between March 2014 and November 2015. MAIN MEASURES: Likert-scale responses to questions concerning perceptions of generic drug safety and effectiveness, reliance on and preferences for pill appearance, and responses to pill appearance changes. Multivariable logistic regression-modeled predictors of seeking advice and adjusting use following a pill appearance change. KEY RESULTS: Of 814 respondents (response rate = 41%), 72% relied on pill appearance to ensure they took the correct medication. A similar percentage wanted their pills to remain the same color (72%), shape (71%), and size (75%) upon refill, but 58% would not have paid a $1 premium on a $5 co-pay to ensure such consistency. Most respondents (86%) wanted their pharmacists to notify them about pill appearance changes, but only 37% recalled such notification; 21% thought they received the wrong medication, and 8% adjusted medication use. Younger respondents (18-33 vs. 50-57 years) were more likely to seek advice (odds ratio [OR] = 1.91; 95% confidence interval [CI],1.02-3.59), and respondents with lower household income (< $30,000 vs. > $100,000) were more likely to adjust medication use (OR = 3.40; 95% CI,1.09-10.67). CONCLUSIONS: Requiring uniform pill appearance may help increase adherence but presents challenges. Standardized pharmacy notification and education policies may be a more feasible short-term solution.

Provider and Patient Determinants of Generic Levothyroxine Prescribing: An Electronic Health Records-Based Study.

BACKGROUND: Despite the availability of generic levothyroxine products for more than a decade, uptake of these products is poor. OBJECTIVE: We sought to evaluate determinants of generic prescribing of levothyroxine. METHODS: In a cross-sectional analysis of electronic health records data between 2010 and 2013, we identified adult patients with a levothyroxine prescription from a primary-care physician (PCP) or endocrinologist. We used mixed-effect logistic regression models with random intercepts for prescribing provider to examine predictors of generic levothyroxine prescribing. Models include patient, prescription, and provider fixed-effect covariates. Odds ratios (ORs) and 95% CIs were generated. Between-provider random variation was quantified by the intraclass correlation coefficient (ICC). RESULTS: Study patients (n = 63 838) were clustered among 941 prescribing providers within 25 ambulatory care clinics. The overall prevalence of generic prescribing of levothyroxine was 73%. In the multivariable mixed-effect model, patients were significantly less likely to receive generic levothyroxine from an endocrinologist than a PCP (OR = 0.43; 95% CI = 0.33-0.55; P < 0.001). Women were less likely to receive generic levothyroxine than men from endocrinologists (OR = 0.68; 95% CI = 0.59-0.78; P < 0.001) but not from PCPs. Between-provider variation in generic prescribing was 18.3% in the absence of fixed-effect covariates and could be explained marginally by patient, prescription, and provider factors (ICC = 15.9%). CONCLUSIONS: Generic levothyroxine prescribing differed by PCPs and endocrinologists. Residual variation in generic prescribing, after accounting for measurable factors, indicates the need for provider interventions or patient education aimed at improving levothyroxine generic uptake.

Switch-backs associated with generic drugs approved using product-specific determinations of therapeutic equivalence.

PURPOSE: US Food and Drug Administration approval for generic drugs relies on demonstrating pharmaceutical equivalence and bioequivalence; however, some drug products have unique attributes that necessitate product-specific approval pathways. We evaluated rates of patients' switching back to brand-name versions from generic versions of four drugs approved via such approaches. METHODS: We used data from Optum LifeSciences Research Database to identify patients using a brand-name version of a study drug (acarbose tablets, salmon calcitonin nasal spray, enoxaparin sodium injection, and venlafaxine extended release tablets) or a control drug. We followed patients to identify switching to generic versions and then followed those who switched to identify whether they switched back to brand-name versions. We calculated switch and switch-back rates and used Kaplan-Meier and log-rank tests to compare rates between study and control drugs. RESULTS: Our cohort included 201 959 eligible patients. Brand-to-generic switch rates ranged from 66 to 106 switches per 100 person-years for study drugs and 80 to 110 for control drugs. Rates of switch-back to brand-name versions ranged from 5 to 37 among study drugs and 3 to 53 among control drugs. Switch-back rates were higher for venlafaxine vs. sertraline (p < 0.01) and calcitonin vs. alendronate (p = 0.01). Switch-back rates were lower for venlafaxine vs. paroxetine (p < 0.01) and acarbose vs. nateglinide (p < 0.01). Rates were similar for acarbose vs. glimepiride (p = 0.97) and for enoxaparin vs. fondiparinux (p = 0.11). CONCLUSION: As compared to control drugs, patients were not more likely to systematically switch back from generic to brand-name versions of the four study drugs. Copyright © 2016 John Wiley & Sons, Ltd.

A Systematic Review of the Benefits and Risks of Anticoagulation Following Traumatic Brain Injury.

OBJECTIVE: To synthesize the existing literature on benefits and risks of anticoagulant use after traumatic brain injury (TBI). DESIGN: Systematic review. A literature search was performed in MEDLINE, International Pharmaceutical Abstracts, Health Star, and CINAHL (Cumulative Index to Nursing and Allied Health Literature) on October 11, 2012, and updated on September 2, 2013, using terms related to TBI and anticoagulants. MAIN MEASURES: Human studies evaluating the effects of post-TBI anticoagulation on venous thromboembolism, hemorrhage, mortality, or coagulation parameters with original analyses were eligible for the review. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline was followed throughout the conduct of the review. RESULTS: Thirty-nine eligible studies were identified from the literature, of which 23 studies with complete information on post-TBI anticoagulant use and patient outcomes were summarized in this review. Meta-analysis was unwarranted because of varying methodological design and quality of the studies. Twenty-one studies focused on the effects of pharmacological thromboprophylaxis (PTP) post-TBI on venous thromboembolism and/or progression of intracranial hemorrhage, whereas 2 randomized controlled trials analyzed coagulation parameters as the result of anticoagulation. CONCLUSION: Pharmacological thromboprophylaxis appears to be safe among TBI patients with stabilized hemorrhagic patterns. More evidence is needed regarding effectiveness of PTP in preventing venous thromboembolism as well as preferred agent, dose, and timing for PTP.

Risk of Arterial and Venous Thrombotic Events Among Patients with COVID-19: A Multi-National Collaboration of Regulatory Agencies from Canada, Europe, and United States.

Purpose: Few studies have examined how the absolute risk of thromboembolism with COVID-19 has evolved over time across different countries. Researchers from the European Medicines Agency, Health Canada, and the United States (US) Food and Drug Administration established a collaboration to evaluate the absolute risk of arterial (ATE) and venous thromboembolism (VTE) in the 90 days after diagnosis of COVID-19 in the ambulatory (eg, outpatient, emergency department, nursing facility) setting from seven countries across North America (Canada, US) and Europe (England, Germany, Italy, Netherlands, and Spain) within periods before and during COVID-19 vaccine availability. Patients and Methods: We conducted cohort studies of patients initially diagnosed with COVID-19 in the ambulatory setting from the seven specified countries. Patients were followed for 90 days after COVID-19 diagnosis. The primary outcomes were ATE and VTE over 90 days from diagnosis date. We measured country-level estimates of 90-day absolute risk (with 95% confidence intervals) of ATE and VTE. Results: The seven cohorts included 1,061,565 patients initially diagnosed with COVID-19 in the ambulatory setting before COVID-19 vaccines were available (through November 2020). The 90-day absolute risk of ATE during this period ranged from 0.11% (0.09-0.13%) in Canada to 1.01% (0.97-1.05%) in the US, and the 90-day absolute risk of VTE ranged from 0.23% (0.21-0.26%) in Canada to 0.84% (0.80-0.89%) in England. The seven cohorts included 3,544,062 patients with COVID-19 during vaccine availability (beginning December 2020). The 90-day absolute risk of ATE during this period ranged from 0.06% (0.06-0.07%) in England to 1.04% (1.01-1.06%) in the US, and the 90-day absolute risk of VTE ranged from 0.25% (0.24-0.26%) in England to 1.02% (0.99-1.04%) in the US. Conclusion: There was heterogeneity by country in 90-day absolute risk of ATE and VTE after ambulatory COVID-19 diagnosis both before and during COVID-19 vaccine availability.

Six Years of the US Food and Drug Administration's Postmarket Active Risk Identification and Analysis System in the Sentinel Initiative: Implications for Real World Evidence Generation.

Congress mandated the creation of a postmarket Active Risk Identification and Analysis (ARIA) system containing data on 100 million individuals for monitoring risks associated with drug and biologic products using data from disparate sources to complement the US Food and Drug Administration's (FDA's) existing postmarket capabilities. We report on the first 6 years of ARIA utilization in the Sentinel System (2016-2021). The FDA has used the ARIA system to evaluate 133 safety concerns; 54 of these evaluations have closed with regulatory determinations, whereas the rest remain in progress. If the ARIA system and the FDA's Adverse Event Reporting System are deemed insufficient to address a safety concern, then the FDA may issue a postmarket requirement to a product's manufacturer. One hundred ninety-seven ARIA insufficiency determinations have been made. The most common situation for which ARIA was found to be insufficient is the evaluation of adverse pregnancy and fetal outcomes following in utero drug exposure, followed by neoplasms and death. ARIA was most likely to be sufficient for thromboembolic events, which have high positive predictive value in claims data alone and do not require supplemental clinical data. The lessons learned from this experience illustrate the continued challenges using administrative claims data, especially to define novel clinical outcomes. This analysis can help to identify where more granular clinical data are needed to fill gaps to improve the use of real-world data for drug safety analyses and provide insights into what is needed to efficiently generate high-quality real-world evidence for efficacy.

Treatment and care received by children hospitalized with COVID-19 in a large hospital network in the United States, February 2020 to September 2021.

We described care received by hospitalized children with COVID-19 or multi-system inflammatory syndrome (MIS-C) prior to the 2021 COVID-19 Omicron variant surge in the US. We identified hospitalized children <18 years of age with a COVID-19 or MIS-C diagnosis (COVID-19 not required), separately, from February 2020-September 2021 (n = 126 hospitals). We described high-risk conditions, inpatient treatments, and complications among these groups. Among 383,083 pediatric hospitalizations, 2,186 had COVID-19 and 395 had MIS-C diagnosis. Less than 1% had both COVID-19 and MIS-C diagnosis (n = 154). Over half were >6 years old (54% COVID-19, 70% MIS-C). High-risk conditions included asthma (14% COVID-19, 11% MIS-C), and obesity (9% COVID-19, 10% MIS-C). Pulmonary complications in children with COVID-19 included viral pneumonia (24%) and acute respiratory failure (11%). In reference to children with COVID-19, those with MIS-C had more hematological disorders (62% vs 34%), sepsis (16% vs 6%), pericarditis (13% vs 2%), myocarditis (8% vs 1%). Few were ventilated or died, but some required oxygen support (38% COVID-19, 45% MIS-C) or intensive care (42% COVID-19, 69% MIS-C). Treatments included: methylprednisolone (34% COVID-19, 75% MIS-C), dexamethasone (25% COVID-19, 15% MIS-C), remdesivir (13% COVID-19, 5% MIS-C). Antibiotics (50% COVID-19, 68% MIS-C) and low-molecular weight heparin (17% COVID-19, 34% MIS-C) were frequently administered. Markers of illness severity among hospitalized children with COVID-19 prior to the 2021 Omicron surge are consistent with previous studies. We report important trends on treatments in hospitalized children with COVID-19 to improve the understanding of real-world treatment patterns in this population.

Risk of admission to hospital with arterial or venous thromboembolism among patients diagnosed in the ambulatory setting with covid-19 compared with influenza: retrospective cohort study.

Objective: To measure the 90 day risk of arterial thromboembolism and venous thromboembolism among patients diagnosed with covid-19 in the ambulatory (ie, outpatient, emergency department, or institutional) setting during periods before and during covid-19 vaccine availability and compare results to patients with ambulatory diagnosed influenza. Design: Retrospective cohort study. Setting: Four integrated health systems and two national health insurers in the US Food and Drug Administration's Sentinel System. Participants: Patients with ambulatory diagnosed covid-19 when vaccines were unavailable in the US (period 1, 1 April-30 November 2020; n=272 065) and when vaccines were available in the US (period 2, 1 December 2020-31 May 2021; n=342 103), and patients with ambulatory diagnosed influenza (1 October 2018-30 April 2019; n=118 618). Main outcome measures: Arterial thromboembolism (hospital diagnosis of acute myocardial infarction or ischemic stroke) and venous thromboembolism (hospital diagnosis of acute deep venous thrombosis or pulmonary embolism) within 90 days after ambulatory covid-19 or influenza diagnosis. We developed propensity scores to account for differences between the cohorts and used weighted Cox regression to estimate adjusted hazard ratios of outcomes with 95% confidence intervals for covid-19 during periods 1 and 2 versus influenza. Results: 90 day absolute risk of arterial thromboembolism with covid-19 was 1.01% (95% confidence interval 0.97% to 1.05%) during period 1, 1.06% (1.03% to 1.10%) during period 2, and with influenza was 0.45% (0.41% to 0.49%). The risk of arterial thromboembolism was higher for patients with covid-19 during period 1 (adjusted hazard ratio 1.53 (95% confidence interval 1.38 to 1.69)) and period 2 (1.69 (1.53 to 1.86)) than for patients with influenza. 90 day absolute risk of venous thromboembolism with covid-19 was 0.73% (0.70% to 0.77%) during period 1, 0.88% (0.84 to 0.91%) during period 2, and with influenza was 0.18% (0.16% to 0.21%). Risk of venous thromboembolism was higher with covid-19 during period 1 (adjusted hazard ratio 2.86 (2.46 to 3.32)) and period 2 (3.56 (3.08 to 4.12)) than with influenza. Conclusions: Patients diagnosed with covid-19 in the ambulatory setting had a higher 90 day risk of admission to hospital with arterial thromboembolism and venous thromboembolism both before and after covid-19 vaccine availability compared with patients with influenza.