Important note: Information in this article was accurate in February 1999. The state of the art may have changed since the publication date.AIDSWEEKLY Plus; Monday, February 8, 1999
Daniel J. DeNoon, Senior Editor
A new model using population genetics and epidemiologic observations predicts that the incidence of a drug-resistant pathogen will rapidly increase once the use of a drug to which the pathogen is sensitive exceeds a critical threshold. Reducing consumption below this threshold, the model predicts, will only slowly decrease resistance.
"Given the observed decline in the rate of development of novel antibiotics, in the future more attention must be given to the development of prescribing policies designed to maximize the life expectancy of a given compound," wrote Oxford researcher Daren J. Austin and colleagues.
"It must always be remembered that the strength of the selective pressure (i.e., the rate of drug consumption) is intimately and positively associated with the rate of evolution of resistance, as clearly illustrated in our analysis.
Austin et al. reported their findings in the Proceedings of the National Academy of Sciences ("The Relationship Between the Volume of Antimicrobial Consumption in Human Communities and the Frequency of Resistance," Proc Natl Acad Sci U S A 1999 Feb 2;96(3):1152-6).
The researchers based their model based on the assumption that in developed nations, community-acquired infections prompt most drug consumption. Application of the model explains what has happened in communities where antimicrobial resistance is high.
"Specifically, there is a critical level of drug consumption required to trigger the emergence of resistance to significant levels," Austin et al. wrote. "Significant reductions in the frequency of resistance will only result from equally significant changes in antibiotic use patterns. ... The decay in resistance after a reduction in prescribing volume will typically occur on a slower time scale than the rise in resistance once the critical threshold drug consumption is crossed."
What is extremely important to find out, the researchers suggest, is whether increased antibiotic resistance will lead to changes in clinical outcome for the affected community. While the impact of resistant organisms on an individual is obviously harmful, there may be mitigating factors for the community. This is because increases in resistance lower the ability of organisms to cause superinfections. So long as a certain number of people in a community have drug- sensitive infections, there may be a sort of herd immunity to resistant organisms.
Interestingly, Austin et al. noted that drug sales may not necessarily determine consumption patterns in a given area. They suggested that pharmaceutical companies studying the impact of new drugs should employ the techniques set forth in the present study.
"The principles of population genetics rarely are applied by those directly concerned with the study of antimicrobial resistance, and an obvious need is to meld these techniques with those more commonly used in pharmacoepidemiological studies," they wrote.
This study was supported by the Wellcome Trust and by grants from the Science Funds of National University Hospital and the University of Iceland.
The corresponding author for this study is D.J. Austin, Wellcome Trust Centre for the Epidemiology of Infectious Disease, University of Oxford, South Parks Road, Oxford OX1 35, United Kingdom. Email: <daren.austin@zoology.ox.ac.uk>.
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