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Randomized clinical trials to identify optimal antibiotic treatment duration

Horsburgh, CR; Shea, KM; Phillips, P; LaValley, M; (2013) Randomized clinical trials to identify optimal antibiotic treatment duration. Trials , 14 , Article 88. 10.1186/1745-6215-14-88. Green open access

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Abstract

Background Antibiotic resistance is a major barrier to the continued success of antibiotic treatment. Such resistance is often generated by overly long durations of antibiotic treatment. A barrier to identifying the shortest effective treatment duration is the cost of the sequence of clinical trials needed to determine shortest optimal duration. We propose a new method to identify the optimal treatment duration of an antibiotic treatment regimen. Methods Subjects are randomized to varying treatment durations and the cure proportions of these durations are linked using a logistic regression model, making effective use of information across all treatment duration groups. In this paper, Monte Carlo simulation is used to evaluate performance of such a model. Results Using a hypothetical dataset, the logistic regression model is seen to provide increased precision in defining the point estimate and confidence interval (CI) of the cure proportion at each treatment duration. When applied to the determination of non-inferiority, the regression model allows identification of the shortest duration meeting the predefined non-inferiority margin. Conclusions This analytic strategy represents a practical way to develop shortened regimens for tuberculosis and other infectious diseases. Application of this strategy to clinical trials of antibiotic therapy could facilitate decreased antibiotic usage, reduce cost, minimize toxicity, and decrease the emergence of antibiotic resistance.

Type: Article
Title: Randomized clinical trials to identify optimal antibiotic treatment duration
Open access status: An open access version is available from UCL Discovery
DOI: 10.1186/1745-6215-14-88
Publisher version: http://dx.doi.org/10.1186/1745-6215-14-88
Language: English
Additional information: © 2013 Horsburgh et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. PubMed ID: 23536969
Keywords: Antibiotic trials, Antibiotic treatment duration, Tuberculosis, Logistic regression
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health > Infection and Population Health
URI: https://discovery.ucl.ac.uk/id/eprint/1394476
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