Evidence map›Paper›PMID 31221165›Full record

Trial reportBMC medicine2019

Optimising trial designs to identify appropriate antibiotic treatment durations.

Koen B Pouwels, Mo Yin, Christopher C Butler, Ben S Cooper, Sarah Wordsworth, A Sarah Walker, Julie V Robotham

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
6.6field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 4 countries.

Koen B PouwelsHealth Econonomics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK. koen.pouwels@npdh.ox.ac.uk.ORCID 0000-0001-7097-8950
Mo YinMahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Christopher C ButlerThe National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK.
Ben S CooperMahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Sarah WordsworthHealth Econonomics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
A Sarah WalkerThe National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK.
Julie V RobothamModelling and Economics Unit, National Infection Service, Public Health England, London, UK.
John Radcliffe Hospital · GBMahidol University · THNational Institute for Health Research · GBPublic Health England · GBUniversity Medical Center Groningen · NL

Funding

Medical Research Council MC_UU_12023/22Medical Research Council MC_UU_12023/29Medical Research Council MR/K006924/1
6 · The paper itself

Abstract

backgroundFor 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.

conclusionMulti-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.

Indexed as

Anti-Bacterial AgentsDrug Resistance, MicrobialHumansAnti-Bacterial AgentsAntibioticsAntimicrobial resistanceBayesianDesignDuration of therapyFrequentistRandomised trial

Identifiers

PMID31221165
PMCPMC6587258
OpenAlexW2946500929

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.