Hypersensitivity cases associated with drug-eluting coronary stents: a review of available cases from the research on adverse drug events and reports (RADAR) project

Journal ArticleOBJECTIVES: We undertook the review of all available cases of hypersensitivity reactions after placement of a drug-eluting stent (DES) and classified potential causes. BACKGROUND: Six months after the approval of the first DES, the Food and Drug Administration (FDA) reported 50 hypersensitivity reactions after stent placement but later concluded these were due to concomitantly prescribed medications such as clopidogrel. Nevertheless, the FDA continued to receive reports of hypersensitivity. METHODS: Reports available from April 2003 through December 2004 for hypersensitivity-like reactions associated with the sirolimus-eluting stent (CYPHER, Cordis Corp., Miami Lakes, Florida) and paclitaxel-eluting stent (TAXUS, Boston Scientific Corp., Natick, Massachusetts) were reviewed. Sources of reports included the FDA's adverse-device-event database, the published literature, and investigators from the Research on Adverse Drug/Device events And Reports (RADAR) project. Causality was assessed using standardized World Health Organization criteria. RESULTS: Of 5,783 reports identified for the DES in the FDA database, 262 unique events included hypersensitivity symptoms. Of these reports, 2 were certainly and 39 unlikely caused by clopidogrel and 1 was certainly, 9 probably, and 13 unlikely caused by the DES. From all sources, we identified 17 distinct cases that were probably or certainly caused by the stent, of which 9 had symptoms that lasted longer than four weeks. Four autopsies confirmed intrastent eosinophilic inflammation, thrombosis, and lack of intimal healing. CONCLUSIONS: The FDA reports and autopsy findings suggest that DES may be a cause of systemic and intrastent hypersensitivity reactions that, in some cases, have been associated with late thrombosis and death

pSCANNER: Patient-centered scalable national network for effectiveness research

pre-printThis article describes the patient-centered Scalable National Network for Effectiveness Research (pSCANNER), which is part of the recently formed PCORnet, a national network composed of learning healthcare systems and patient-powered research networks funded by the Patient Centered Outcomes Research Institute (PCORI). It is designed to be a stakeholder-governed federated network that uses a distributed architecture to integrate data from three existing networks covering over 21 million patients in all 50 states: (1) VA Informatics and Computing Infrastructure (VINCI), with data from Veteran Health Administration's 151 inpatient and 909 ambulatory care and community-based outpatient clinics; (2) the University of California Research exchange (UC-ReX) network, with data from UC Davis, Irvine, Los Angeles, San Francisco, and San Diego; and (3) SCANNER, a consortium of UCSD, Tennessee VA, and three federally qualified health systems in the Los Angeles area supplemented with claims and health information exchange data, led by the University of Southern California. Initial use cases will focus on three conditions: (1) congestive heart failure; (2) Kawasaki disease; (3) obesity. Stakeholders, such as patients, clinicians, and health service researchers, will be engaged to prioritize research questions to be answered through the network. We will use a privacy-preserving distributed computation model with synchronous and asynchronous modes. The distributed system will be based on a common data model that allows the construction and evaluation of distributed multivariate models for a variety of statistical analyses

Factors associated with screening or treatment initiation among male United States veterans at risk for osteoporosis fracture

Male osteoporosis continues to be under-recognized and undertreated in men. An understanding of which factors cue clinicians about osteoporosis risk in men, and which do not, is needed to identify areas for improvement. This study sought to measure the association of a provider\u27s recognition of osteoporosis with patient information constructs that are available at the time of each encounter. Using clinical and administrative data from the Veterans Health Administration system, we used a stepwise procedure to construct prognostic models for a combined outcome of osteoporosis diagnosis, treatment, or a bone mineral density (BMD) test order using time-varying covariates and Cox regression. We ran separate models for patients with at least one primary care visit and patients with only secondary care visits in the pre-index period. Some of the strongest predictors of clinical osteoporosis identification were history of gonadotropin-releasing hormone (GnRH) agonist exposure, fragility fractures, and diagnosis of rheumatoid arthritis. Other characteristics associated with a higher likelihood of having osteoporosis risk recognized were underweight or normal body mass index, cancer, fall history, and thyroid disease. Medication exposures associated with osteoporosis risk recognition included opioids, glucocorticoids, and antidepressants. Several known clinical risk factors for fracture were not correlated with osteoporosis risk including smoking and alcohol abuse. Results suggest that clinicians are relying on some, but not all, clinical risk factors when assessing osteoporosis risk