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Journal article

Optimising trial designs to identify appropriate antibiotic treatment durations

Abstract:

Background

For many infectious conditions, the optimal antibiotic course length remains unclear. The estimation of course length must consider the important trade-off between maximising short- and long-term efficacy and minimising antibiotic resistance and toxicity.

Main body

Evidence on optimal treatment durations should come from randomised controlled trials. However, most antibiotic randomised controlled trials compare two arbitrarily chosen durations. We argue that alternative trial designs, which allow allocation of patients to multiple different treatment durations, are needed to better identify optimal antibiotic durations. There are important considerations when deciding which design is most useful in identifying optimal treatment durations, including the ability to model the duration–response relationship (or duration–response ‘curve’), the risk of allocation concealment bias, statistical efficiency, the possibility to rapidly drop arms that are clearly inferior, and the possibility of modelling the trade-off between multiple competing outcomes.

Conclusion

Multi-arm designs modelling duration–response curves with the possibility to drop inferior arms during the trial could provide more information about the optimal duration of antibiotic therapies than traditional head-to-head comparisons of limited numbers of durations, while minimising the probability of assigning trial participants to an ineffective treatment regimen.

Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1186/s12916-019-1348-z

Authors

More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
Nuffield Department of Population Health
Sub department:
Population Health
Department:
Unknown
Role:
Author
ORCID:
0000-0001-7097-8950
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM
Sub department:
Primary Care Health Sciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM
Sub department:
Tropical Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
Nuffield Department of Population Health
Sub department:
Population Health
Role:
Author


Publisher:
BioMed Central
Journal:
BMC Medicine More from this journal
Volume:
17
Article number:
115
Publication date:
2019-06-21
Acceptance date:
2019-05-20
DOI:
EISSN:
1741-7015


Keywords:
Pubs id:
pubs:997513
UUID:
uuid:ba3a2182-f3de-42a4-a23b-0806cbf8bd4b
Local pid:
pubs:997513
Source identifiers:
997513
Deposit date:
2019-05-10
ARK identifier:

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