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.

Validation of Acute Pancreatitis Among Adults in an Integrated Healthcare System.

Background: Acute pancreatitis is a serious gastrointestinal disease that is an important target for drug safety surveillance. Little is known about the accuracy of ICD-10 codes for acute pancreatitis in the United States, or their performance in specific clinical settings. We conducted a validation study to assess the accuracy of acute pancreatitis ICD-10 diagnosis codes in inpatient, emergency department (ED), and outpatient settings.

New-Onset Cancer Cases in FDA's Sentinel System: A Large Distributed System of US Electronic Healthcare Data.

Background: Evaluations of cancer etiology and safety and effectiveness of cancer treatments are predicated on large numbers of patients with sufficient baseline and follow-up data. To assess feasibility of FDA's Sentinel System's electronic healthcare data for surveillance of malignancy onset and examination of product safety, this study examined patterns of enrollment surrounding new-onset cancers.

Methods: Using a retrospective cohort of patients based on administrative claims, we identified incident events of 19 cancers among 292.

Validity of ICD-10-CM diagnoses to identify hospitalizations for serious infections among patients treated with biologic therapies.

Purpose: Identifying hospitalizations for serious infections among patients dispensed biologic therapies within healthcare databases is important for post-marketing surveillance of these drugs. We determined the positive predictive value (PPV) of an ICD-10-CM-based diagnostic coding algorithm to identify hospitalization for serious infection among patients dispensed biologic therapy within the FDA's Sentinel Distributed Database.

Methods: We identified health plan members who met the following algorithm criteria: (1) hospital ICD-10-CM discharge diagnosis of serious infection between July 1, 2016 and August 31, 2018; (2) either outpatient/emergency department infection diagnosis or outpatient antimicrobial treatment within 7 days prior to hospitalization; (3) inflammatory bowel disease, psoriasis, or rheumatological diagnosis within 1 year prior to hospitalization, and (4) were dispensed outpatient biologic therapy within 90 days prior to admission.

Electronic phenotyping of health outcomes of interest using a linked claims-electronic health record database: Findings from a machine learning pilot project.

Objective: Claims-based algorithms are used in the Food and Drug Administration Sentinel Active Risk Identification and Analysis System to identify occurrences of health outcomes of interest (HOIs) for medical product safety assessment. This project aimed to apply machine learning classification techniques to demonstrate the feasibility of developing a claims-based algorithm to predict an HOI in structured electronic health record (EHR) data.

Materials And Methods: We used the 2015-2019 IBM MarketScan Explorys Claims-EMR Data Set, linking administrative claims and EHR data at the patient level.

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.

Evaluation of Use of Technologies to Facilitate Medical Chart Review.

Introduction: While medical chart review remains the gold standard to validate health conditions or events identified in administrative claims and electronic health record databases, it is time consuming, expensive and can involve subjective decisions.

Aim: The aim of this study was to describe the landscape of technology-enhanced approaches that could be used to facilitate medical chart review within and across distributed data networks.

Method: We conducted a semi-structured survey regarding processes for medical chart review with organizations that either routinely do medical chart review or use technologies that could facilitate chart review.

Statistical Power for Postlicensure Medical Product Safety Data Mining.

Objective: To perform sample size calculations when using tree-based scan statistics in longitudinal observational databases.

Methods: Tree-based scan statistics enable data mining on epidemiologic datasets where thousands of disease outcomes are organized into hierarchical tree structures with automatic adjustment for multiple testing. We show how to evaluate the statistical power of the unconditional and conditional Poisson versions.

Reporting to Improve Reproducibility and Facilitate Validity Assessment for Healthcare Database Studies V1.0.

Purpose: Defining a study population and creating an analytic dataset from longitudinal healthcare databases involves many decisions. Our objective was to catalogue scientific decisions underpinning study execution that should be reported to facilitate replication and enable assessment of validity of studies conducted in large healthcare databases.

Methods: We reviewed key investigator decisions required to operate a sample of macros and software tools designed to create and analyze analytic cohorts from longitudinal streams of healthcare data.

Reporting to Improve Reproducibility and Facilitate Validity Assessment for Healthcare Database Studies V1.0.

Purpose: Defining a study population and creating an analytic dataset from longitudinal healthcare databases involves many decisions. Our objective was to catalogue scientific decisions underpinning study execution that should be reported to facilitate replication and enable assessment of validity of studies conducted in large healthcare databases.

Methods: We reviewed key investigator decisions required to operate a sample of macros and software tools designed to create and analyze analytic cohorts from longitudinal streams of healthcare data.

Automated Algorithm for Detection of Transient Adenosine Release.

Spontaneous adenosine release events have been discovered in the brain that last only a few seconds. The identification of these adenosine events from fast-scan cyclic voltammetry (FSCV) data is difficult due to the random nature of adenosine release. In this study, we develop an algorithm that automatically identifies and characterizes adenosine transient features, including event time, concentration, and duration.

Transient Adenosine Release Is Modulated by NMDA and GABA Receptors.

Adenosine is a neuroprotective agent that modulates neurotransmission and is modulated by other neurotransmitters. Spontaneous, transient adenosine is a recently discovered mode of signaling where adenosine is released and cleared from the extracellular space quickly, in less than three seconds. Spontaneous adenosine release is regulated by adenosine A and A receptors, but regulation by other neurotransmitter receptors has not been studied.

Laser Treated Carbon Nanotube Yarn Microelectrodes for Rapid and Sensitive Detection of Dopamine .

Carbon nanotube yarn microelectrodes (CNTYMEs) exhibit rapid and selective detection of dopamine with fast-scan cyclic voltammetry (FSCV); however, the sensitivity limits their application . In this study, we introduce laser treatment as a simple, reliable, and efficient approach to improve the sensitivity of CNTYMEs by three fold while maintaining high temporal resolution. The effect of laser treatment on the microelectrode surface was characterized by scanning electron microscopy, Raman spectroscopy, energy dispersion spectroscopy, and laser confocal microscopy.

Fast-scan Cyclic Voltammetry for the Characterization of Rapid Adenosine Release.

Adenosine is a signaling molecule and downstream product of ATP that acts as a neuromodulator. Adenosine regulates physiological processes, such as neurotransmission and blood flow, on a time scale of minutes to hours. Recent developments in electrochemical techniques, including fast-scan cyclic voltammetry (FSCV), have allowed direct detection of adenosine with sub-second temporal resolution.

Carbon Nanotubes Grown on Metal Microelectrodes for the Detection of Dopamine.

Microelectrodes modified with carbon nanotubes (CNTs) are useful for the detection of neurotransmitters because the CNTs enhance sensitivity and have electrocatalytic effects. CNTs can be grown on carbon fiber microelectrodes (CFMEs) but the intrinsic electrochemical activity of carbon fibers makes evaluating the effect of CNT enhancement difficult. Metal wires are highly conductive and many metals have no intrinsic electrochemical activity for dopamine, so we investigated CNTs grown on metal wires as microelectrodes for neurotransmitter detection.

Prospective influenza vaccine safety surveillance using fresh data in the Sentinel System.

Purpose: To develop the infrastructure to conduct timely active surveillance for safety of influenza vaccines and other medical countermeasures in the Sentinel System (formerly the Mini-Sentinel Pilot), a Food and Drug Administration-sponsored national surveillance system that typically relies on data that are mature, settled, and updated quarterly.

Methods: Three Data Partners provided their earliest available ("fresh") cumulative claims data on influenza vaccination and health outcomes 3-4 times on a staggered basis during the 2013-2014 influenza season, collectively producing 10 data updates. We monitored anaphylaxis in the entire population using a cohort design and seizures in children ≤4 years of age using both a self-controlled risk interval design (primary) and a cohort design (secondary).

Evaluation of the risk of venous thromboembolism after quadrivalent human papillomavirus vaccination among US females.

After the Food and Drug Administration (FDA) licensed quadrivalent human papillomavirus vaccine (HPV4) in 2006, reports suggesting a possible association with venous thromboembolism (VTE) emerged from the Vaccine Adverse Event Reporting System and the Vaccine Safety Datalink. Our objective was to determine whether HPV4 increased VTE risk. The subjects were 9-26-year-old female members of five data partners in the FDA's Mini-Sentinel pilot project receiving HPV4 during 2006-2013.

A vaccine study design selection framework for the postlicensure rapid immunization safety monitoring program.

The Postlicensure Rapid Immunization Safety Monitoring Program, the vaccination safety monitoring component of the US Food and Drug Administration's Mini-Sentinel project, is currently the largest cohort in the US general population for vaccine safety surveillance. We developed a study design selection framework to provide a roadmap and description of methods that may be utilized to evaluate potential associations between vaccines and health outcomes of interest in the Postlicensure Rapid Immunization Safety Monitoring Program and other systems using administrative data. The strengths and weaknesses of designs for vaccine safety monitoring, including the cohort design, the case-centered design, the risk interval design, the case-control design, the self-controlled risk interval design, the self-controlled case series method, and the case-crossover design, are described and summarized in tabular form.

High temporal resolution measurements of dopamine with carbon nanotube yarn microelectrodes.

Fast-scan cyclic voltammetry (FSCV) can detect small changes in dopamine concentration; however, measurements are typically limited to scan repetition frequencies of 10 Hz. Dopamine oxidation at carbon-fiber microelectrodes (CFMEs) is dependent on dopamine adsorption, and increasing the frequency of FSCV scan repetitions decreases the oxidation current, because the time for adsorption is decreased. Using a commercially available carbon nanotube yarn, we characterized carbon nanotube yarn microelectrodes (CNTYMEs) for high-speed measurements with FSCV.

Mechanical stimulation evokes rapid increases in extracellular adenosine concentration in the prefrontal cortex.

Mechanical perturbations can release ATP, which is broken down to adenosine. In this work, we used carbon-fiber microelectrodes and fast-scan cyclic voltammetry to measure mechanically stimulated adenosine in the brain by lowering the electrode 50 μm. Mechanical stimulation evoked adenosine in vivo (average: 3.

Characterization of spontaneous, transient adenosine release in the caudate-putamen and prefrontal cortex.

Adenosine is a neuroprotective agent that inhibits neuronal activity and modulates neurotransmission. Previous research has shown adenosine gradually accumulates during pathologies such as stroke and regulates neurotransmission on the minute-to-hour time scale. Our lab developed a method using carbon-fiber microelectrodes to directly measure adenosine changes on a sub-second time scale with fast-scan cyclic voltammetry (FSCV).