The association of varying treatment thresholds of mepolizumab on asthma exacerbations in adults.

Background: Asthma has a high healthcare burden globally, with up to 10% of the asthma population suffering from severe disease. Biologic agents are a newer class of asthma treatments for severe asthma, with good evidence for efficacy in clinical trials. Nevertheless, real-world studies of its impact on clinical outcomes are limited.Methods: This is an observational cohort study using administrative claims data. The study population consisted of patients aged ≥18 years who had a diagnosis of asthma and initiated mepolizumab after November 4, 2015 and had continuous medical and drug coverage in both the 365 days prior to and following mepolizumab initiation. In patients treated with mepolizumab, we described clinically significant asthma exacerbations by minimum continuous treatment thresholds following initiation of mepolizumab, medication switching patterns and chronic oral corticosteroid (≥28 days) use.Results: We identified 2,536 adults with asthma who initiated mepolizumab. There was an association toward reduction in severe asthma-related events over the first one year of exposure. We observed associations with reduced dispensings of oral corticosteroids over the first year after mepolizumab initiation. Very few patients switched to other biologics during the study period.Conclusions: Treatment with mepolizumab may be associated with fewer asthma-related events in the first year. Over the first one year after initiating mepolizumab, we found associations with decreased concomitant dispensings of oral corticosteroids and medium to high dose ICS/LABA. Additionally, most patients who initiated mepolizumab did not switch to other biologics.

Use of a mobile app to capture supplemental health information during pregnancy: Implications for clinical research.

PURPOSE: Mobile applications ("apps") may be efficient tools for improving the quality of clinical research among pregnant women, but evidence is sparse. We assess the feasibility and generalizability of a mobile app for capturing supplemental data during pregnancy. METHODS: In 2017, we conducted a pilot study of the FDA MyStudies mobile app within a pregnant population identified through Kaiser Permanente Washington (KPWA), an integrated healthcare delivery system. We ascertained health conditions, medications, and substance use through app-based questionnaires. In a post-hoc analysis, we utilized electronic health records (EHR) to summarize sociodemographic and health characteristics of pilot participants and, for comparison, a pregnant population identified using similar methods. RESULTS: Six percent (64/1070) of contacted women enrolled in the pilot study. Nearly half (23/53) reported taking medication for headaches and one-fourth for constipation (13/53) and nausea (12/53) each. Few instances (2/92) of over-the-counter medication use were identified in electronic dispensing records. One-quarter to one-third of participants with depression and anxiety/panic, respectively, reported recently discontinuing medications for these conditions. Eighty-eight percent of pilot participants reported White race (95%CI: 81-95%), versus 67% of the comparison population (N = 2065). More pilot participants filled ≥1 prescription for antianxiety medication (22% [95%CI: 13-35%]) and antidepressants (19% [95%CI 10-31%]) pre-pregnancy than the comparison population (10 and 9%, respectively). CONCLUSIONS: Mobile apps may be a feasible tool for capturing health data not routinely available in EHR. Pregnant women willing to use a mobile app for research may differ from the general pregnant population, but confirmation is needed.

Patient characteristics, pain treatment patterns, and incidence of total joint replacement in a US population with osteoarthritis.

BACKGROUND: Currently available medications for chronic osteoarthritis pain are only moderately effective, and their use is limited in many patients because of serious adverse effects and contraindications. The primary surgical option for osteoarthritis is total joint replacement (TJR). The objectives of this study were to describe the treatment history of patients with osteoarthritis receiving prescription pain medications and/or intra-articular corticosteroid injections, and to estimate the incidence of TJR in these patients. METHODS: This retrospective, multicenter, cohort study utilized health plan administrative claims data (January 1, 2013, through December 31, 2019) of adult patients with osteoarthritis in the Innovation in Medical Evidence Development and Surveillance Distributed Database, a subset of the US FDA Sentinel Distributed Database. Patients were analyzed in two cohorts: those with prevalent use of "any pain medication" (prescription non-steroidal anti-inflammatory drugs [NSAIDs], opioids, and/or intra-articular corticosteroid injections) using only the first qualifying dispensing (index date); and those with prevalent use of "each specific pain medication class" with all qualifying treatment episodes identified. RESULTS: Among 1 992 670 prevalent users of "any pain medication", pain medications prescribed on the index date were NSAIDs (596 624 [29.9%] patients), opioids (1 161 806 [58.3%]), and intra-articular corticosteroids (323 459 [16.2%]). Further, 92 026 patients received multiple pain medications on the index date, including 71 632 (3.6%) receiving both NSAIDs and opioids. Altogether, 20.6% of patients used an NSAID at any time following an opioid index dispensing and 17.2% used an opioid following an NSAID index dispensing. The TJR incidence rates per 100 person-years (95% confidence interval [CI]) were 3.21 (95% CI: 3.20-3.23) in the "any pain medication" user cohort, and among those receiving "each specific pain medication class" were NSAIDs, 4.63 (95% CI: 4.58-4.67); opioids, 7.45 (95% CI: 7.40-7.49); and intra-articular corticosteroids, 8.05 (95% CI: 7.97-8.13). CONCLUSIONS: In patients treated with prescription medications for osteoarthritis pain, opioids were more commonly prescribed at index than NSAIDs and intra-articular corticosteroid injections. Of the pain medication classes examined, the incidence of TJR was highest in patients receiving intra-articular corticosteroids and lowest in patients receiving NSAIDs.

Operational Insights Into Mosquito Control Disaster Response in Coastal North Carolina: Experiences With the Federal Emergency Management Agency After Hurricane Florence.

Preparation for post-hurricane mosquito control is essential for an effective emergency response to protect public health and promote recovery efforts. Effective pre-hurricane planning includes laying the groundwork for a successful reimbursement application to the Federal Emergency Management Agency. The critical and overlapping need to sustain funding for mosquito control programs is highlighted here in the context of both normal and emergency responses. Community support is an integral component of an effective integrated pest management program and is established over time with appropriate communication and engagement. Experienced mosquito control operators who are familiar with treatment areas are an essential component of successful operations. Here, practical advice is provided to plan, prepare, and implement a successful ground- and aerial-based mosquito control response.

BBCIC Research Network Analysis of First-Cycle Prophylactic G-CSF Use in Patients Treated With High-Neutropenia Risk Chemotherapy.

BACKGROUND: Chemotherapy-induced febrile neutropenia (FN) is prevented or minimized with granulocyte colony-stimulating factors (G-CSFs). Several G-CSF biosimilars are approved in the United States. The Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) is a nonprofit initiative whose objective is to provide scientific evidence on real-world use and comparative safety and effectiveness of biologics and biosimilars using the BBCIC distributed research network (DRN). PATIENTS AND METHODS: We describe real-world G-CSF use in patients with breast or lung cancer receiving first-cycle chemotherapy associated with high FN risk. We assessed hospitalizations for FN, availability of absolute neutrophil counts, and G-CSF-induced adverse events to inform future observational comparative effectiveness studies of G-CSF reference products and their biosimilars. A descriptive analysis of 5 participating national health insurance plans was conducted within the BBCIC DRN. RESULTS: A total of 57,725 patients who received at least one G-CSF dose were included. Most (92.5%) patients received pegfilgrastim. FN hospitalization rates were evaluated by narrow (<0.5%), intermediate (1.91%), and broad (2.99%) definitions. Anaphylaxis and hyperleukocytosis were identified in 1.15% and 2.28% of patients, respectively. This analysis provides real-world evidence extracted from a large, readily available database of diverse patients, characterizing G-CSF reference product use to inform the feasibility of future observational comparative safety and effectiveness analyses of G-CSF biosimilars. We showed that the rates of FN and adverse events in our research network are consistent with those reported by previous small studies. CONCLUSIONS: Readily available BBCIC DRN data can be used to assess G-CSF use with the incidence of FN hospitalizations. Insufficient laboratory result data were available to report absolute neutrophil counts; however, other safety data are available for assessment that provide valuable baseline data regarding the effectiveness and safety of G-CSFs in preparation for comparative effectiveness studies of reference G-CSFs and their biosimilars.

Health outcomes coding trends in the US Food and Drug Administration's Sentinel System during transition to International Classification of Diseases-10 coding system: A brief review.

BACKGROUND AND PURPOSE: The transition from International Classification of Diseases, 9th revision, clinical modification (ICD-9-CM) to ICD-10-CM poses a challenge to epidemiologic studies that use diagnostic codes to identify health outcomes and covariates. We evaluated coding trends in health outcomes in the US Food and Drug Administration's Sentinel System during the transition. METHODS: We reviewed all health outcomes coding trends reports on the Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the ICD-9-CM and ICD-10-CM eras by visual inspection. RESULTS: We identified 78 unique health outcomes (22 acute, 32 chronic, and 24 acute or chronic) and 140 time-series graphs of incidence and prevalence. The reports also included code lists and code mapping methods used. Of the 140 graphs reviewed, 81 (57.9%) showed consistent trends across the ICD-9-CM and ICD-10-CM eras, while 51 (36.4%) and 8 (5.7%) graphs showed inconsistent and uncertain trends, respectively. Chronic HOIs and acute/chronic HOIs had higher proportions of consistent trends in prevalence definitions (83.9% and 78.3%, respectively) than acute HOIs (28.6%). For incidence, 55.6% of acute HOIs showed consistent trends, while 41.2% of chronic HOIs and 39.3% of acute/chronic HOIs showed consistency. CONCLUSIONS: Researchers using ICD-10-CM algorithms obtained by standardized mappings from ICD-9-CM algorithms should assess the mapping performance before use. The Sentinel reports provide a valuable resource for researchers who need to develop and assess mapping strategies. The reports could benefit from additional information about the algorithm selection process and additional details on monthly incidence and prevalence rates. KEY POINTS: We reviewed health outcomes coding trends reports on the US FDA Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) and ICD-10-CM eras by code mapping method and the type of health outcomes of interest (acute, chronic, acute or chronic). More than a third of the 140 time-series graphs of incidence and prevalence of health outcomes showed inconsistent or uncertain trends. Consistency in trends varied by code mapping method, type of health outcomes of interest, and whether the measurement was incidence or prevalence. Studies using ICD-9-CM-based algorithms mapped to ICD-10-CM codes need to assess the performance of the mappings and conduct manual refinement of the algorithms as needed before using them.

A COVID-19-ready public health surveillance system: The Food and Drug Administration's Sentinel System.

The US Food and Drug Administration's Sentinel System was established in 2009 to use routinely collected electronic health data for improving the national capability to assess post-market medical product safety. Over more than a decade, Sentinel has become an integral part of FDA's surveillance capabilities and has been used to conduct analyses that have contributed to regulatory decisions. FDA's role in the COVID-19 pandemic response has necessitated an expansion and enhancement of Sentinel. Here we describe how the Sentinel System has supported FDA's response to the COVID-19 pandemic. We highlight new capabilities developed, key data generated to date, and lessons learned, particularly with respect to working with inpatient electronic health record data. Early in the pandemic, Sentinel developed a multi-pronged approach to support FDA's anticipated data and analytic needs. It incorporated new data sources, created a rapidly refreshed database, developed protocols to assess the natural history of COVID-19, validated a diagnosis-code based algorithm for identifying patients with COVID-19 in administrative claims data, and coordinated with other national and international initiatives. Sentinel is poised to answer important questions about the natural history of COVID-19 and is positioned to use this information to study the use, safety, and potentially the effectiveness of medical products used for COVID-19 prevention and treatment.

Leveraging the Capabilities of the FDA's Sentinel System To Improve Kidney Care.

The Sentinel System is a national electronic postmarketing resource established by the US Food and Drug Administration to support assessment of the safety and effectiveness of marketed medical products. It has built a large, multi-institutional, distributed data network that contains comprehensive electronic health data, covering about 700 million person-years of longitudinal observation time nationwide. With its sophisticated infrastructure and a large selection of flexible analytic tools, the Sentinel System permits rapid and secure analyses, while preserving patient privacy and health-system autonomy. The Sentinel System also offers enhanced capabilities, including accessing full-text medical records, supporting randomized clinical trials embedded in healthcare delivery systems, and facilitating effective collection of patient-reported data using mobile devices, among many other research programs. The nephrology research community can use the infrastructure, tools, and data that this national resource offers for evidence generation. This review summarizes the Sentinel System and its ability to rapidly generate high-quality, real-world evidence; discusses the program's experience in, and potential for, addressing gaps in kidney care; and outlines avenues for conducting research, leveraging this national resource in collaboration with Sentinel investigators.

Chemotherapy-induced peripheral neuropathy (CIPN) and its treatment: an NIH Collaboratory study of claims data.

PURPOSE: Chemotherapy-induced peripheral neuropathy (CIPN) is a disabling complication of many chemotherapies. We investigated the feasibility of using health plan claims and administrative data to identify CIPN occurrence by comparing patients who received neurotoxic and non-neurotoxic chemotherapies. METHODS: The sample included over 53,000,000 patients from two regional and one national insurer in the USA (> 400,000 exposed to chemotherapy). Peripheral neuropathy was identified using a broad definition (definition 1) and a specific definition (i.e., drug-induced polyneuropathy code) (definition 2). RESULTS: CIPN incidence as measured by definition 1 within 6 months of chemotherapy initiation was 18.1% and 6.2% for patients who received neurotoxic and non-neurotoxic chemotherapy, respectively (relative risk neurotoxic vs. non-neurotoxic (RR), 2.93 (95% CI, 2.87-2.98)). For definition 2, these incidences were 3.6% and 0.1% (RR, 25.2 (95% CI, 22.8-27.8)). The incidences of new analgesic prescriptions for neurotoxic and non-neurotoxic groups were as follows: gabapentin, 7.1%/1.7%; pregabalin, 0.69%/0.31%; and duloxetine, 0.78%/0.76%. The incidence of CIPN as defined by definitions 1 and 2 was low compared with that of published research studies, but the relative risk of CIPN among patients who received neurotoxic chemotherapies compared with those who received non-neurotoxic chemotherapies was high using definition 2. CONCLUSIONS: These data suggest that as used currently by clinicians, administrative codes likely underestimate CIPN incidence. Thus, studies using administrative data to estimate CIPN incidence are not currently feasible. However, the drug-induced polyneuropathy code is a specific indicator of CIPN in administrative data and may be useful for investigating predictors or potentially preventive therapies of CIPN.

Graphical Depiction of Longitudinal Study Designs in Health Care Databases.

Pharmacoepidemiologic and pharmacoeconomic analysis of health care databases has become a vital source of evidence to support health care decision making and efficient management of health care organizations. However, decision makers often consider studies done in nonrandomized health care databases more difficult to review than randomized trials because many design choices need to be considered. This is perceived as an important barrier to decision making about the effectiveness and safety of medical products. Design flaws in longitudinal database studies are avoidable but can be unintentionally obscured in the convoluted prose of methods sections, which often lack specificity. We propose a simple framework of graphical representation that visualizes study design implementations in a comprehensive, unambiguous, and intuitive way; contains a level of detail that enables reproduction of key study design variables; and uses standardized structure and terminology to simplify review and communication to a broad audience of decision makers. Visualization of design details will make database studies more reproducible, quicker to review, and easier to communicate to a broad audience of decision makers.

How pharmacoepidemiology networks can manage distributed analyses to improve replicability and transparency and minimize bias.

Several pharmacoepidemiology networks have been developed over the past decade that use a distributed approach, implementing the same analysis at multiple data sites, to preserve privacy and minimize data sharing. Distributed networks are efficient, by interrogating data on very large populations. The structure of these networks can also be leveraged to improve replicability, increase transparency, and reduce bias. We describe some features of distributed networks using, as examples, the Canadian Network for Observational Drug Effect Studies, the Sentinel System in the USA, and the European Research Network of Pharmacovigilance and Pharmacoepidemiology. Common protocols, analysis plans, and data models, with policies on amendments and protocol violations, are key features. These tools ensure that studies can be audited and repeated as necessary. Blinding and strict conflict of interest policies reduce the potential for bias in analyses and interpretation. These developments should improve the timeliness and accuracy of information used to support both clinical and regulatory decisions.

Do FDA label changes work? Assessment of the 2010 class label change for proton pump inhibitors using the Sentinel System's analytic tools.

PURPOSE: To pilot use of the US Food and Drug Administration's (FDA's) Sentinel System data and analytic tools by a non-FDA stakeholder through the Innovation in Medical Evidence Development and Surveillance system of the Reagan Udall Foundation. We evaluated the US FDA 2010 proton pump inhibitor (PPI) class label change that warned of increased risk of bone fracture, to use PPIs for the lowest dose and shortest duration, and to manage bone status for those at risk for osteoporosis. METHODS: The cohort consisted of adults aged 18 years or older prescribed PPIs without fracture risk factors. We evaluated incident and prevalent uses of the 8 PPIs noted in the label change. Outcomes evaluated before and after label change were PPI dispensing patterns, incident fractures, and osteoporosis screening or interventions. Consistent with FDA use of descriptive tools, we did not include direct comparisons or statistical testing. RESULTS: There were 1 488 869 and 2 224 420 incident PPI users in the before [PRE] and after [POST] periods, respectively. Users with 1 year or more of exposure decreased (8.4% vs 7.5%), as did mean days supplied/user (130.4 to 113.7 d among all users and 830.8 to 645.4 d among users with 1 y or more of exposure). Osteoporosis screening and interventions did not appear to increase, but the proportion of patients with fractures decreased (4.4% vs 3.1%). Prevalent user results were similar. CONCLUSIONS: This analysis demonstrated the ability to use Sentinel tools to assess the effectiveness of a label change and accompanying communication at the population level and suggests an influence on subsequent dispensing behavior.

Use of the TRH Stimulation Test to Assess Long Term Changes of Thyroid Function in an Olympic Athlete.

This case report presents the utility of the thyroid-releasing hormone (TRH) stimulation test for assessing endocrine disease in athletes. On two occasions, 4 years apart (1992 and 1996), a TRH stimulation test was performed to corroborate clinical symptoms and observation. On the first occasion, the patient's symptoms were not attributed to thyroid disease. He was treated for a sinus infection with amoxicillin/clavulanate 500 mg three times per day for 1 wk. On the second occasion, thyroid disease was confirmed and treatment with 100-µg L-thyroxine was initiated. Baseline screening and TRH stimulation testing were used at both assessment time points. Baseline screen for TSH was 2.2 and 1.2 uUI·mL and stimulated TSH was at 15.2 uUI·mL at 30 min and 30.6 uUI·mL at 45 min for the first (1992) and second (1996) assessment, respectively. Patient was positive on the second visit for antithyroglobulin antibodies at 70 IU·mL (normal, 0-59 IU·mL). Three months postdiagnosis, TSH was 0.66 uIU·mL and the patient was asymptomatic. At the most recent visit, 20 years and 4 months later, no symptomology was reported and TSH was 0.55 uIU·mL A greater understanding of the interaction between stress and end organ function is warranted in occupations undergoing unique stressors.

The feasibility of using multiple databases to study rare outcomes: the potential effect of long-acting beta agonists with inhaled corticosteroid therapy on asthma mortality.

PURPOSE: Long-acting beta agonists (LABAs) when used without concomitant inhaled corticosteroids (ICS) increase the risk of asthma-related deaths, but the effect on asthma-related death of LABA used in combination with ICS therapy is unknown. To address this question, we explored the feasibility of conducting an observational study using multiple US health care data sources. METHODS: Retrospective cohort study to evaluate the likelihood of getting an upper 95% confidence limit ≤1.4 for the asthma mortality rate ratio and ≤0.40 per 10 000 person-years for the mortality rate difference, assuming no effect of new use of combined LABA + ICS (versus non-LABA maintenance therapy) on asthma mortality. Ten research institutions executed centrally distributed analytic code based on a standard protocol using an extracted (2000-2010) persistent asthma cohort (asthma diagnosis and ≥4 asthma medications in 12 months). Pooled results were analyzed by the coordinating center. Asthma deaths were ascertained by linkage with the National Death Index. RESULTS: In a cohort of 994 627 persistent asthma patients (2.4 million person-years; 278 asthma deaths), probabilities of the upper 95% confidence limit for effect estimates being less than targeted values, assuming a null relation, were about 0.05. Modifications in cohort and exposure definitions increased exposed person-time and outcome events, but study size remained insufficient to attain study goals. CONCLUSIONS: Even with 10 data sources and a 10-year study period, the rarity of asthma deaths among patients using certain medications made it infeasible to study the association between combined LABA + ICS and asthma mortality with our targeted level of study precision. Copyright © 2016 John Wiley & Sons, Ltd.

Evidence generation from healthcare databases: recommendations for managing change.

There is an increasing reliance on databases of healthcare records for pharmacoepidemiology and other medical research, and such resources are often accessed over a long period of time so it is vital to consider the impact of changes in data, access methodology and the environment. The authors discuss change in communication and management, and provide a checklist of issues to consider for both database providers and users. The scope of the paper is database research, and changes are considered in relation to the three main components of database research: the data content itself, how it is accessed, and the support and tools needed to use the database. Copyright © 2016 John Wiley & Sons, Ltd.

Identifying health outcomes in healthcare databases.

PURPOSE: The purpose of this review is to assist researchers in developing, using, and interpreting case-identifying algorithms in electronic healthcare databases. METHODS: We review clinical characteristics of health outcomes, data settings and informatics, and epidemiologic and statistical methods aspects as they pertain to the development and use of case-identifying algorithms. RESULTS: We offer a framework for thinking critically about the use of electronic health insurance data and electronic health records to identify the occurrence of health outcomes. Accuracy of case ascertainment in database research depends on many factors, including clinical and behavioral aspects of the health outcome, and details of database construction as it pertains to completeness and reliability of database content. Existing methods for diagnostic and screening tests, misclassification, validation studies, and predictive modelling can be usefully applied to improve case ascertainment in database research. CONCLUSIONS: Good case-identifying algorithms are based on a sound understanding of care-seeking behavior and patterns of clinical diagnosis and treatment in the study population and details about the construction and characteristics of the database. Researchers should use quantitative bias analyses to take into account the performance characteristics of case-identifying algorithms and their impact on study results.

Orphan therapies: making best use of postmarket data.

BACKGROUND: Postmarket surveillance of the comparative safety and efficacy of orphan therapeutics is challenging, particularly when multiple therapeutics are licensed for the same orphan indication. To make best use of product-specific registry data collected to fulfill regulatory requirements, we propose the creation of a distributed electronic health data network among registries. Such a network could support sequential statistical analyses designed to detect early warnings of excess risks. We use a simulated example to explore the circumstances under which a distributed network may prove advantageous. METHODS: We perform sample size calculations for sequential and non-sequential statistical studies aimed at comparing the incidence of hepatotoxicity following initiation of two newly licensed therapies for homozygous familial hypercholesterolemia. We calculate the sample size savings ratio, or the proportion of sample size saved if one conducted a sequential study as compared to a non-sequential study. Then, using models to describe the adoption and utilization of these therapies, we simulate when these sample sizes are attainable in calendar years. We then calculate the analytic calendar time savings ratio, analogous to the sample size savings ratio. We repeat these analyses for numerous scenarios. KEY RESULTS: Sequential analyses detect effect sizes earlier or at the same time as non-sequential analyses. The most substantial potential savings occur when the market share is more imbalanced (i.e., 90% for therapy A) and the effect size is closest to the null hypothesis. However, due to low exposure prevalence, these savings are difficult to realize within the 30-year time frame of this simulation for scenarios in which the outcome of interest occurs at or more frequently than one event/100 person-years. CONCLUSIONS: We illustrate a process to assess whether sequential statistical analyses of registry data performed via distributed networks may prove a worthwhile infrastructure investment for pharmacovigilance.