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Antibiotic dose impact on resistance selection in the community: a mathematical model of beta-lactams and Streptococcus pneumoniae dynamics.

ABSTRACT: Streptococcus pneumoniae is a major pathogen in the community and presents high rates of resistance to the available antibiotics. To prevent antibiotic treatment failure caused by highly resistant bacteria, increasing the prescribed antibiotic dose has recently been suggested. The aim of the present study was to assess the influence of beta-lactam prescribed doses on the emergence of resistance and selection in the community. A mathematical model was constructed by combining S. pneumoniae pharmacodynamic and population-dynamic approaches. The received-dose heterogeneity in the population was specifically modeled. Simulations over a 50-year period were run to test the effects of dose distribution and antibiotic exposure frequency changes on community resistance patterns, as well as the accuracy of the defined daily dose as a predictor of resistance. When the frequency of antibiotic exposure per year was kept constant, dose levels had a strong impact on the levels of resistance after a 50-year simulation. The lowest doses resulted in a high prevalence of nonsusceptible strains (> or =70%) with MICs that were still low (1 mg/liter), whereas high doses resulted in a lower prevalence of nonsusceptible strains (<40%) and higher MICs (2 mg/liter). Furthermore, by keeping the volume of antibiotics constant in the population, different patterns of use (low antibiotic dose and high antibiotic exposure frequency versus high dose and low frequency) could lead to markedly different rates of resistance distribution and prevalence (from 10 to 100%). Our results suggest that pneumococcal resistance patterns in the community are strongly related to the individual beta-lactam doses received: limiting beta-lactam use while increasing the doses could help reduce the prevalence of resistance, although it should select for higher levels of resistance. Surveillance networks are therefore encouraged to collect both daily antibiotic exposure frequencies and individual prescribed doses.

SUBMITTER: Opatowski L

PROVIDER: S-EPMC2876390 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Antibiotic dose impact on resistance selection in the community: a mathematical model of beta-lactams and Streptococcus pneumoniae dynamics.

Opatowski Lulla L Mandel Jonas J Varon Emmanuelle E Boëlle Pierre-Yves PY Temime Laura L Guillemot Didier D

Antimicrobial agents and chemotherapy 20100315 6

Streptococcus pneumoniae is a major pathogen in the community and presents high rates of resistance to the available antibiotics. To prevent antibiotic treatment failure caused by highly resistant bacteria, increasing the prescribed antibiotic dose has recently been suggested. The aim of the present study was to assess the influence of beta-lactam prescribed doses on the emergence of resistance and selection in the community. A mathematical model was constructed by combining S. pneumoniae pharma ...[more]

PMID: 20231396

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Project description:It is widely thought that widespread antibiotic use selects for community antibiotic resistance, though this has been difficult to prove in the setting of a community-randomized clinical trial. In this study, we used a randomized clinical trial design to assess whether macrolide resistance was higher in communities treated with mass azithromycin for trachoma, compared to untreated control communities.In a cluster-randomized trial for trachoma control in Ethiopia, 12 communities were randomized to receive mass azithromycin treatment of children aged 1-10 years at months 0, 3, 6, and 9. Twelve control communities were randomized to receive no antibiotic treatments until the conclusion of the study. Nasopharyngeal swabs were collected from randomly selected children in the treated group at baseline and month 12, and in the control group at month 12. Antibiotic susceptibility testing was performed on Streptococcus pneumoniae isolated from the swabs using Etest strips. In the treated group, the mean prevalence of azithromycin resistance among all monitored children increased from 3.6% (95% confidence interval [CI] 0.8%-8.9%) at baseline, to 46.9% (37.5%-57.5%) at month 12 (p = 0.003). In control communities, azithromycin resistance was 9.2% (95% CI 6.7%-13.3%) at month 12, significantly lower than the treated group (p < 0.0001). Penicillin resistance was identified in 0.8% (95% CI 0%-4.2%) of isolates in the control group at 1 year, and in no isolates in the children-treated group at baseline or 1 year.This cluster-randomized clinical trial demonstrated that compared to untreated control communities, nasopharyngeal pneumococcal resistance to macrolides was significantly higher in communities randomized to intensive azithromycin treatment. Mass azithromycin distributions were given more frequently than currently recommended by the World Health Organization's trachoma program. Azithromycin use in this setting did not select for resistance to penicillins, which remain the drug of choice for pneumococcal infections.www.ClinicalTrials.gov NCT00322972. Please see later in the article for the Editors' Summary.

Project description:Streptococcus pneumoniae (Sp) is a commensal bacterium that normally resides on the upper airway epithelium without causing infection. However, factors such as co-infection with influenza virus can impair the complex Sp-host interactions and the subsequent development of many life-threatening infectious and inflammatory diseases, including pneumonia, meningitis or even sepsis. With the increased threat of Sp infection due to the emergence of new antibiotic resistant Sp strains, there is an urgent need for better treatment strategies that effectively prevent progression of disease triggered by Sp infection, minimizing the use of antibiotics. The complexity of the host-pathogen interactions has left the full understanding of underlying mechanisms of Sp-triggered pathogenesis as a challenge, despite its critical importance in the identification of effective treatments. To achieve a systems-level and quantitative understanding of the complex and dynamically-changing host-Sp interactions, here we developed a mechanistic mathematical model describing dynamic interplays between Sp, immune cells, and epithelial tissues, where the host-pathogen interactions initiate. The model serves as a mathematical framework that coherently explains various in vitro and in vitro studies, to which the model parameters were fitted. Our model simulations reproduced the robust homeostatic Sp-host interaction, as well as three qualitatively different pathogenic behaviors: immunological scarring, invasive infection and their combination. Parameter sensitivity and bifurcation analyses of the model identified the processes that are responsible for qualitative transitions from healthy to such pathological behaviors. Our model also predicted that the onset of invasive infection occurs within less than 2 days from transient Sp challenges. This prediction provides arguments in favor of the use of vaccinations, since adaptive immune responses cannot be developed de novo in such a short time. We further designed optimal treatment strategies, with minimal strengths and minimal durations of antibiotics, for each of the three pathogenic behaviors distinguished by our model. The proposed mathematical framework will help to design better disease management strategies and new diagnostic markers that can be used to inform the most appropriate patient-specific treatment options.

Dataset Information

Antibiotic dose impact on resistance selection in the community: a mathematical model of beta-lactams and Streptococcus pneumoniae dynamics.

Publications

Antibiotic dose impact on resistance selection in the community: a mathematical model of beta-lactams and Streptococcus pneumoniae dynamics.

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