Empiric antibiotic treatment of erythema migrans-like skin lesions as a function of geography: a clinical and cost effectiveness modeling study.
Abstract
The skin lesion of early Lyme disease, erythema migrans (EM), is so characteristic
that routine practice is to treat all such patients with antibiotics. Because other
skin lesions may resemble EM, it is not known whether presumptive treatment of EM
is appropriate in regions where Lyme disease is rare. We constructed a decision model
to compare the cost and clinical effectiveness of three strategies for the management
of EM: Treat All, Observe, and Serology as a function of the probability that an EM-like
lesion is Lyme disease. Treat All was found to be the preferred strategy in regions
that are endemic for Lyme disease. Where Lyme disease is rare, Observe is the preferred
strategy, as presumptive treatment would be expected to produce excessive harm and
increased costs. Where Lyme disease is rare, clinicians and public health officials
should consider observing patients with EM-like lesions who lack travel to Lyme disease-endemic
areas.
Type
Journal articleSubject
AnimalsAnti-Bacterial Agents
Arachnid Vectors
Borrelia burgdorferi
Cost-Benefit Analysis
Decision Making
Decision Support Techniques
Erythema Chronicum Migrans
Geography
Humans
Ixodes
Ixodidae
Skin
United States
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https://hdl.handle.net/10161/13965Published Version (Please cite this version)
10.1089/vbz.2013.1365Publication Info
Lantos, Paul M; Brinkerhoff, R Jory; Wormser, Gary P; & Clemen, Robert (2013). Empiric antibiotic treatment of erythema migrans-like skin lesions as a function of
geography: a clinical and cost effectiveness modeling study. Vector Borne Zoonotic Dis, 13(12). pp. 877-883. 10.1089/vbz.2013.1365. Retrieved from https://hdl.handle.net/10161/13965.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Robert T. Clemen
Professor Emeritus
Robert T. Clemen is Professor of Decision Sciences at Duke University’s Fuqua School
of Business. He has broad interests in the use of decision analysis for organizational
decision making, and special interests in the psychology of judgment, assessing expert
probabilities, the effectiveness of decision-making techniques, and using decision
analysis to help organizations become environmentally sustainable. He has taught courses
on decision making and environmental sustainability in Duke&rsq
Paul Michael Lantos
Professor of Medicine
I am interested in the spatial epidemiology of infectious diseases. My research utilizes
geographic information systems (GIS) and geostatistical analyses to understand the
spatial and spatiotemporal distribution of diseases, and their relationship with environmental
and demographic factors. I currently have active studies evaluating the spatial distribution
of numerous domestic and international infectious diseases, including SARS-CoV-2 (COVID-19),
cytomegalovirus, influenza, and Lyme disease. A
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