A systematic analysis and data mining of opioid-related adverse events submitted to the FAERS database.

The opioid epidemic has become a serious national crisis in the United States. An indepth systematic analysis of opioid-related adverse events (AEs) can clarify the risks presented by opioid exposure, as well as the individual risk profiles of specific opioid drugs and the potential relationships among the opioids. In this study, 92 opioids were identified from the list of all Food and Drug Administration (FDA)-approved drugs, annotated by RxNorm and were classified into 13 opioid groups: buprenorphine, codeine, dihydrocodeine, fentanyl, hydrocodone, hydromorphone, meperidine, methadone, morphine, oxycodone, oxymorphone, tapentadol, and tramadol. A total of 14,970,399 AE reports were retrieved and downloaded from the FDA Adverse Events Reporting System (FAERS) from 2004, Quarter 1 to 2020, Quarter 3. After data processing, Empirical Bayes Geometric Mean (EBGM) was then applied which identified 3317 pairs of potential risk signals within the 13 opioid groups. Based on these potential safety signals, a comparative analysis was pursued to provide a global overview of opioid-related AEs for all 13 groups of FDA-approved prescription opioids. The top 10 most reported AEs for each opioid class were then presented. Both network analysis and hierarchical clustering analysis were conducted to further explore the relationship between opioids. Results from the network analysis revealed a close association among fentanyl, oxycodone, hydrocodone, and hydromorphone, which shared more than 22 AEs. In addition, much less commonly reported AEs were shared among dihydrocodeine, meperidine, oxymorphone, and tapentadol. On the contrary, the hierarchical clustering analysis further categorized the 13 opioid classes into two groups by comparing the full profiles of presence/absence of AEs. The results of network analysis and hierarchical clustering analysis were not only consistent and cross-validated each other but also provided a better and deeper understanding of the associations and relationships between the 13 opioid groups with respect to their adverse effect profiles.

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.

Using inpatient electronic medical records to study influenza for pandemic preparedness.

BACKGROUND: We assessed the ability to identify key data relevant to influenza and other respiratory virus surveillance in a large-scale US-based hospital electronic medical record (EMR) dataset using seasonal influenza as a use case. We describe characteristics and outcomes of hospitalized influenza cases across three seasons. METHODS: We identified patients with an influenza diagnosis between March 2017 and March 2020 in 140 US hospitals as part of the US FDA's Sentinel System. We calculated descriptive statistics on the presence of high-risk conditions, influenza antiviral administrations, and severity endpoints. RESULTS: Among 5.1 million hospitalizations, we identified 29,520 hospitalizations with an influenza diagnosis; 64% were treated with an influenza antiviral within 2 days of admission, and 25% were treated >2 days after admission. Patients treated >2 days after admission had more comorbidities than patients treated within 2 days of admission. Patients never treated during hospitalization had more documentation of cardiovascular and other diseases than treated patients. We observed more severe endpoints in patients never treated (death = 3%, mechanical ventilation [MV] = 9%, intensive care unit [ICU] = 26%) or patients treated >2 days after admission (death = 2%, MV = 14%, ICU = 32%) than in patients treated earlier (treated on admission: death = 1%, MV = 5%, ICU = 23%, treated within 2 days of admission: death = 1%, MV = 7%, ICU = 27%). CONCLUSIONS: We identified important trends in influenza severity related to treatment timing in a large inpatient dataset, laying the groundwork for the use of this and other inpatient EMR data for influenza and other respiratory virus surveillance.

Who gets treated for influenza: A surveillance study from the US Food and Drug Administration's Sentinel System.

OBJECTIVE: We describe the baseline characteristics and complications of individuals with influenza in the US FDA's Sentinel System by antiviral treatment timing. DESIGN: Retrospective cohort design. PATIENTS: Individuals aged ≥6 months with outpatient diagnoses of influenza in June 2014-July 2017, 3 influenza seasons. METHODS: We identified the comorbidities, vaccination history, influenza testing, and outpatient antiviral dispensings of individuals with influenza using administrative claims data from 13 data partners including the Centers for Medicare and Medicaid Services, integrated delivery systems, and commercial health plans. We assessed complications within 30 days: hospitalization, oxygen use, mechanical ventilation, critical care, ECMO, and death. RESULTS: There were 1,090,333 influenza diagnoses in 2014-2015; 1,005,240 in 2016-2017; and 578,548 in 2017-2018. Between 49% and 55% of patients were dispensed outpatient treatment within 5 days. In all periods >80% of treated individuals received treatment on the day of diagnosis. Those treated on days 1-5 after diagnosis had higher prevalences of diabetes, chronic obstructive pulmonary disease, asthma, and obesity compared to those treated on the day of diagnosis or not treated at all. They also had higher rates of hospitalization, oxygen use, and critical care. In 2014-2015, among those aged ≥65 years, the rates of hospitalization were 45 per 1,000 diagnoses among those treated on day 0; 74 per 1,000 among those treated on days 1-5; and 50 per 1,000 among those who were untreated. CONCLUSIONS: In a large, national analysis, approximately half of people diagnosed with influenza in the outpatient setting were treated with antiviral medications. Delays in outpatient dispensed treatment were associated with higher prevalence of comorbidities and higher rates of complication.

Clinical Data Extraction During Public Health Emergencies: A Blockchain Technology Assessment.

OBJECTIVE: We sought to explore the technical and legal readiness of healthcare institutions for novel data-sharing methods that allow clinical information to be extracted from electronic health records (EHRs) and submitted securely to the Food and Drug Administration's (FDA's) blockchain through a secure data broker (SDB). MATERIALS AND METHODS: This assessment was divided into four sections: an institutional EHR readiness assessment, legal consultation, institutional review board application submission, and a test of healthcare data transmission over a blockchain infrastructure. RESULTS: All participating institutions reported the ability to electronically extract data from EHRs for research. Formal legal agreements were deemed unnecessary to the project but would be needed in future tests of real patient data exchange. Data transmission to the FDA blockchain met the success criteria of data connection from within the four institutions' firewalls, externally to the FDA blockchain via a SDB. DISCUSSION: The readiness survey indicated advanced analytic capability in hospital institutions and highlighted inconsistency in Fast Healthcare Interoperability Resources format utilitzation across institutions, despite requirements of the 21st Century Cures Act. Further testing across more institutions and annual exercises leveraging the application of data exchange over a blockchain infrastructure are recommended actions for determining the feasibility of this approach during a public health emergency and broaden the understanding of technical requirements for multisite data extraction. CONCLUSION: The FDA's RAPID (Real-Time Application for Portable Interactive Devices) program, in collaboration with Discovery, the Critical Care Research Network's PREP (Program for Resilience and Emergency Preparedness), identified the technical and legal challenges and requirements for rapid data exchange to a government entity using the FDA blockchain infrastructure.

Theoretical modelling of single-mode lasing in microcavity lasers via optical interference injection.

The effective manipulation of mode oscillation and competition is of fundamental importance for controlling light emission in semiconductor lasers. Here we develop a rate equation model which considers the spatially modulated gain and spontaneous emission, which are inherently governed by the ripple of the vacuum electromagnetic field in a Fabry-Pérot (FP) microcavity. By manipulating the interplay between the spatial oscillation of the vacuum field and external optical injection via dual-beam laser interference, single longitudinal mode operation is observed in a FP-type microcavity with a side mode suppression ratio exceeding 40 dB. An exploration of this extended rate equation model bridges the gap between the classical model of multimode competition in semiconductor lasers and a quantum-optics understanding of radiative processes in microcavities.

Broadband, wide-angle antireflection in GaAs through surface nano-structuring for solar cell applications.

We demonstrate broadband and wide-angle antireflective surface nanostructuring in GaAs semiconductors using variable dose electron-beam lithography (EBL). Various designed structures are written with EBL on a positive EB-resist coated GaAs and developed followed by shallow inductively coupled plasma etching. An optimized nanostructured surface shows a reduced surface reflectivity down to less than 2.5% in the visible range of 450-700 nm and an average reflectance of less than 4% over a broad near-infrared wavelength range from 900-1400 nm. The results are obtained over a wide incidence angle of 33.3°. This study shows the potential for anti-reflective structures using a simpler reverse EBL process which can provide optical absorption or extraction efficiency enhancement in semiconductors relevant to improved performance in solar photovoltaics or light-emitting diodes.

Harnessing scientific literature reports for pharmacovigilance. Prototype software analytical tool development and usability testing.

OBJECTIVES: We seek to develop a prototype software analytical tool to augment FDA regulatory reviewers' capacity to harness scientific literature reports in PubMed/MEDLINE for pharmacovigilance and adverse drug event (ADE) safety signal detection. We also aim to gather feedback through usability testing to assess design, performance, and user satisfaction with the tool. METHODS: A prototype, open source, web-based, software analytical tool generated statistical disproportionality data mining signal scores and dynamic visual analytics for ADE safety signal detection and management. We leveraged Medical Subject Heading (MeSH) indexing terms assigned to published citations in PubMed/MEDLINE to generate candidate drug-adverse event pairs for quantitative data mining. Six FDA regulatory reviewers participated in usability testing by employing the tool as part of their ongoing real-life pharmacovigilance activities to provide subjective feedback on its practical impact, added value, and fitness for use. RESULTS: All usability test participants cited the tool's ease of learning, ease of use, and generation of quantitative ADE safety signals, some of which corresponded to known established adverse drug reactions. Potential concerns included the comparability of the tool's automated literature search relative to a manual 'all fields' PubMed search, missing drugs and adverse event terms, interpretation of signal scores, and integration with existing computer-based analytical tools. CONCLUSIONS: Usability testing demonstrated that this novel tool can automate the detection of ADE safety signals from published literature reports. Various mitigation strategies are described to foster improvements in design, productivity, and end user satisfaction.

Use of data mining at the Food and Drug Administration.

OBJECTIVES: This article summarizes past and current data mining activities at the United States Food and Drug Administration (FDA). TARGET AUDIENCE: We address data miners in all sectors, anyone interested in the safety of products regulated by the FDA (predominantly medical products, food, veterinary products and nutrition, and tobacco products), and those interested in FDA activities. SCOPE: Topics include routine and developmental data mining activities, short descriptions of mined FDA data, advantages and challenges of data mining at the FDA, and future directions of data mining at the FDA.

Leveraging MEDLINE indexing for pharmacovigilance - Inherent limitations and mitigation strategies.

BACKGROUND: Traditional approaches to pharmacovigilance center on the signal detection from spontaneous reports, e.g., the U.S. Food and Drug Administration (FDA) adverse event reporting system (FAERS). In order to enrich the scientific evidence and enhance the detection of emerging adverse drug events that can lead to unintended harmful outcomes, pharmacovigilance activities need to evolve to encompass novel complementary data streams, for example the biomedical literature available through MEDLINE. OBJECTIVES: (1) To review how the characteristics of MEDLINE indexing influence the identification of adverse drug events (ADEs); (2) to leverage this knowledge to inform the design of a system for extracting ADEs from MEDLINE indexing; and (3) to assess the specific contribution of some characteristics of MEDLINE indexing to the performance of this system. METHODS: We analyze the characteristics of MEDLINE indexing. We integrate three specific characteristics into the design of a system for extracting ADEs from MEDLINE indexing. We experimentally assess the specific contribution of these characteristics over a baseline system based on co-occurrence between drug descriptors qualified by adverse effects and disease descriptors qualified by chemically induced. RESULTS: Our system extracted 405,300 ADEs from 366,120 MEDLINE articles. The baseline system accounts for 297,093 ADEs (73%). 85,318 ADEs (21%) can be extracted only after integrating specific pre-coordinated MeSH descriptors and additional qualifiers. 22,889 ADEs (6%) can be extracted only after considering indirect links between the drug of interest and the descriptor that bears the ADE context. CONCLUSIONS: In this paper, we demonstrate significant improvement over a baseline approach to identifying ADEs from MEDLINE indexing, which mitigates some of the inherent limitations of MEDLINE indexing for pharmacovigilance. ADEs extracted from MEDLINE indexing are complementary to, not a replacement for, other sources.

Emergency use authorization for intravenous peramivir: evaluation of safety in the treatment of hospitalized patients infected with 2009 H1N1 influenza A virus.

BACKGROUND: On 23 October 2009, the US Food and Drug Administration (FDA) issued an Emergency Use Authorization (EUA) for intravenous peramivir, an unapproved antiviral, to treat suspected or confirmed 2009 H1N1 influenza A virus infection. Eligible hospitalized patients were unresponsive to or unable to tolerate available antivirals or lacked dependable oral or inhaled drug delivery routes. The EUA required healthcare providers to report medication errors, selected adverse events (AEs), serious AEs, and deaths to the FDA. METHODS: An FDA safety team analyzed reports submitted to the Adverse Event Reporting System (AERS) and sought follow-up in selected cases. RESULTS: The FDA received AERS reports for 344 patients (including 28 children and 3 pregnant women). Many patients were critically ill on mechanical ventilation (41%) and renal replacement therapies (19%); 38% had received oseltamivir. The most frequently reported serious AEs by MedDRA preferred term were death (15%), H1N1 influenza (8%), respiratory failure (8%), acute renal failure (7%), and acute respiratory distress syndrome (7%). Six medication errors were reported. Most deaths occurred among patients who were obese, immunosuppressed, aged >65 years, or received oseltamivir. Rash was the only treatment-emergent AE attributable to peramivir. Influenza severity, comorbidities, and concomitant medications confounded additional peramivir AE assessments. Missing clinical and laboratory data precluded evaluation of some reports. CONCLUSIONS: Many peramivir recipients under the EUA were critically ill and at risk for influenza-related complications. The safety data were insufficient to assess whether peramivir affected outcome or caused adverse reactions other than rash. Clinical trials in hospitalized patients with serious influenza infections should provide additional information.

Integration of pharmacotherapy for opioid addiction into HIV primary care for HIV/hepatitis C virus-co-infected patients.

Pharmacotherapy for substance abuse is a rapidly evolving field comprising both old and new effective treatments for substance use. Opiate agonist therapy has been shown to diminish and often eliminate opiate use. This behavior change has resulted in the reduced transmission of many infections, including HIV, hepatitis C virus (HCV), and an enhanced quality of life. For the past 35 years, the provision of opioid agonist therapy has been limited to opioid treatment programmes. Opioid treatment programmes treat approximately 200,000 of the estimated million opiate-addicted individuals in the United States. With the need to increase the number of treatment opportunities available for opioid-dependent patients, Congress passed the Drug Addiction Treatment Act of 2000, which allows for the treatment of opioid dependence using buprenorphine by a properly licensed physician, including HIV primary care physicians. The integration of buprenorphine treatment for opioid addiction into HIV primary care thus provides a new treatment paradigm to address substance abuse in patients with HIV and HCV infections.

Co-occurring Hepatitis C, substance use, and psychiatric illness: treatment issues and developing integrated models of care.

Hepatitis C virus (HCV) infection is transmitted by injection drug use and associated with psychiatric conditions. Patients with drug use or significant psychiatric illness have typically been excluded from HCV treatment trials noting the 1997 National Institutes of Health Consensus Statement on HCV that indicated active drug use and major depressive illness were contraindications to treatment of HCV infection. However, the 2002 NIH Consensus Statement recognized that these patients could be effectively treated for HCV infection and recommended that treatment be considered on a case-by-case basis. Treating HCV infection in these patients is challenging, with drug use relapse possibly leading to psychosocial instability, poor adherence, and HCV reinfection. Interferon therapy may exacerbate preexisting psychiatric symptoms. Co-occurring human immunodeficiency virus or hepatitis B virus provide additional challenges, and access to ancillary medical and psychiatric services may be limited. Patients with co-occurring HCV infection, substance use, and psychiatric illness can complete interferon treatment with careful monitoring and aggressive intervention. Clinicians must integrate early interventions for psychiatric conditions and drug use into their treatment algorithm. Few programs or treatment models are designed to manage co-occurring substance use, psychiatric illness, and HCV infection and therapy. The National Institute on Drug Abuse convened a panel of experts to address the current status and the long-range needs through a 2-day workshop, Co-occurring Hepatitis C, Substance Abuse, and Psychiatric Illness: Addressing the Issues and Developing Integrated Models of Care. This conference report summarizes current data, medical management issues, and strategies discussed.

Hepatitis C infection and injection drug use: the role of hepatologists in evolving treatment efforts.

Treatment regimens for both substance abuse and hepatitis C infection are complex and evolving. New pharmacotherapy for opioid addiction allows for office-based treatment and, thus, an opportunity for expanded treatment in the context of hepatitis C infection. The current article addresses the newly evolving, complex issues in the medical management of hepatitis C and injection drug use.

Addressing the need for treatment paradigms for drug-abusing patients with multiple morbidities.

Persons who use and abuse drugs are at risk for multiple morbidities that involve addiction, bloodborne infectious diseases, and sexually transmitted diseases, in addition to psychiatric illness and social instability. Infectious diseases acquired as a result of drug use can diffuse into non-drug using populations through other high-risk behaviors. Drug users also have substantial comorbidities from noncommunicable diseases and complications that can affect virtually every organ system in the body. Diagnosis of comorbidities and complications associated with drug abuse usually occurs late in the disease course, particularly for persons who are disenfranchised and have limited or no access to medical care. Medical management of these comorbid conditions constitutes a significant challenge. Directly observed therapy (DOT) can be useful but needs to conform to the needs of the targeted treatment population for full efficacy. DOT may have its greatest impact with drug users destabilized by cocaine or methamphetamine use but has yet to be fully investigated in this patient population.

Bloodborne and sexually transmitted infections in drug abusers in the United States, Latin America, the Caribbean, and Spain.

In the United States, approximately 1 million Americans are infected with human immunodeficiency virus (HIV), and several thousand new infections are reported each year. More than one-third of cases of acquired immunodeficiency syndrome (AIDS) are associated with injection drug use. An estimated 1.8 million adults and children are currently living with HIV in Latin America and the Caribbean, and injection drug abuse remains a major factor in initial exposures to HIV in these parts of the world. Although only 3 cases of AIDS related to drug abuse have been reported in Bolivia, a country with a nascent epidemic, >19,000 cases of AIDS have been reported in Argentina and >22,000 in Brazil, with a significant number associated with injection drug use. Extensive epidemiological and clinical research has been conducted in the United States and elsewhere to determine the extent and nature of the problem and to design and develop interventions (prevention and treatment) for drug abusers infected with HIV. The articles in this supplement present a current view of the nature and extent of the bloodborne and sexually transmitted infections in drug abusers and their partners in the Western Hemisphere.

Interventions for metabolic and endocrine complications of human immunodeficiency virus/acquired immune deficiency syndrome and illicit drug use.

Illicit drug use and concurrent infection with human immunodeficiency virus (HIV) are associated with metabolic and endocrine complications that may include lipid, carbohydrate, and endocrine metabolism disorders and nutritional deficiencies. Interventions for these metabolic and endocrine complications range from micronutrient supplementation to hormone-replacement therapy. We present the current strategies for the management of metabolic and endocrine disorders of HIV/acquired immunodeficiency virus and drug use. In addition, the panel members (contributing authors of the present supplement) recommend further research to determine the nature and extent of problems and to design better and effective therapies.

Substance abuse and HIV infection.

Substance abuse facilitates the spread of HIV infection and complicates its management. Successful treatment of HIV disease and other comorbidities in substance abusers requires treatment of substance abuse. At the Clinical Pathway of the Ryan White CARE Act 2002 All Grantee Conference held in Washington, DC, in August 2002, Henry Francis, MD, discussed characteristics of substance abuse in the United States and obstacles and approaches to successful treatment.

Clinical consequences of marijuana.

As documented in national surveys, for the past several years, marijuana has been the most commonly abused drug in the United States, with approximately 6% of the population 12 years and older having used the drug in the month prior to interview. The use of marijuana is not without significant health hazards. Marijuana is associated with effects on almost every organ system in the body, ranging from the central nervous system to the cardiovascular, endocrine, respiratory/pulmonary, and immune systems. Research presented in this special supplement will show that in addition to marijuana abuse/dependence, marijuana use is associated in some studies with impairment of cognitive function in the young and old, fetal and developmental consequences, cardiovascular effects (heart rate and blood pressure changes), respiratory/pulmonary complications such as chronic cough and emphysema, impaired immune function leading to vulnerability to and increased infections, and the risk of developing head, neck, and/or lung cancer. In general, acute effects are better studied than those of chronic use, and more studies are needed that focus on disentangling effects of marijuana from those of other drugs and adverse environmental conditions.