Trial reportBMC medicine2019
Optimising trial designs to identify appropriate antibiotic treatment durations.
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.
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.
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.
Who cites it
6 citing papers in PubMed, 17 citations in OpenAlex.
- Antibiotic duration for common bacterial infections-a systematic review.JAC-antimicrobial resistance · 2025Review
- Protecting healthcare and patient pathways from infection and antimicrobial resistance.BMJ (Clinical research ed.) · 2024Article
- Optimising antibiotic exposure by customising the duration of treatment for respiratory tract infections based on patient needs in primary care.EClinicalMedicine · 2024Review
- A comparison of clinical development pathways to advance tuberculosis regimen development.BMC infectious diseases · 2022Article
- The DURATIONS randomised trial design: Estimation targets, analysis methods and operating characteristics.Clinical trials (London, England) · 2020Article
- Optimising efficacy of antibiotics against systemic infection by varying dosage quantities and times.PLoS computational biology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 4 countries.
Funding
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
Identifiers
What OpenQuestion holds
Registered trials
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.