Evidence map›Paper›PMID 28505268›Full record

ArticleThe Journal of antimicrobial chemotherapy2017

Pharmacodynamics of dose-escalated 'front-loading' polymyxin B regimens against polymyxin-resistant mcr-1-harbouring Escherichia coli.

Nicholas M Smith, Zackery P Bulman, Arthur O Sieron, Jürgen B Bulitta, Patricia N Holden, Roger L Nation, Jian Li, Gerard D Wright, Brian T Tsuji

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of antimicrobial chemotherapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 38% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

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  8. Acquisition of theInfection and drug resistance · 2021
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  9. In pursuit of the triple crown: mechanism-based pharmacodynamic modelling for the optimization of three-drug combinations against KPC-producing Klebsiella pneumoniae.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2020
    Article
  10. Using machine learning to optimize antibiotic combinations: dosing strategies for meropenem and polymyxin B against carbapenem-resistant Acinetobacter baumannii.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2020
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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

9 authors at 5 institutions in 3 countries.

Nicholas M SmithLaboratory for Antimicrobial Pharmacodynamics, University at Buffalo, School of Pharmacy and Pharmaceutical Sciences, Buffalo, NY, USA.
Zackery P BulmanLaboratory for Antimicrobial Pharmacodynamics, University at Buffalo, School of Pharmacy and Pharmaceutical Sciences, Buffalo, NY, USA.
Arthur O SieronMichael G. DeGroote Institute for Infectious Disease Research and the Department of Biochemistry and Biomedical Sciences, McMaster University, Ontario, Canada.
Jürgen B BulittaDepartment of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL, USA.
Patricia N HoldenLaboratory for Antimicrobial Pharmacodynamics, University at Buffalo, School of Pharmacy and Pharmaceutical Sciences, Buffalo, NY, USA.
Roger L NationDrug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Australia.
Jian LiDrug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Australia.
Gerard D WrightMichael G. DeGroote Institute for Infectious Disease Research and the Department of Biochemistry and Biomedical Sciences, McMaster University, Ontario, Canada.
Brian T TsujiLaboratory for Antimicrobial Pharmacodynamics, University at Buffalo, School of Pharmacy and Pharmaceutical Sciences, Buffalo, NY, USA.
Center for Excellence in Education · USMcMaster University · CAMonash University · AUUniversity at Buffalo, State University of New York · USUniversity of Florida · US

Funding

Novel PK/PD Strategies for Polymyxin Combinations against Gram-negative SuperbugsR01AI111990 · NIAID · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI LI, JIAN, TSUJI, BRIAN · 2014 to 2018
$4.4M
NIAID NIH HHS R01 AI111990
6 · The paper itself

Abstract

Objectives: Gram-negative bacteria harbouring the mcr-1 plasmid are resistant to the 'last-line' polymyxins and have been reported worldwide. Our objective was to define the impact of increasing the initial polymyxin B dose intensity against an mcr-1 -harbouring strain to delineate the impact of plasmid-mediated polymyxin resistance on the dynamics of bacterial killing and resistance. Methods: A hollow fibre infection model (HFIM) was used to simulate polymyxin B regimens against an mcr-1 -harbouring Escherichia coli (MIC 8 mg/L) over 10 days. Four escalating polymyxin B 'front-loading' regimens (3.33, 6.66, 13.3 or 26.6 mg/kg for one dose followed by 1.43 mg/kg every 12 h starting 12 h later) simulating human pharmacokinetics were utilized in the HFIM. A mechanism-based, mathematical model was developed using S-ADAPT to characterize bacterial killing. Results: The 3.33 mg/kg 'front-loading' regimen resulted in regrowth mirroring the growth control. The 6.66, 13.3 and 26.6 mg/kg 'front-loading' regimens resulted in maximal bacterial reductions of 1.91, 3.79 and 6.14 log 10 cfu/mL, respectively. Irrespective of the early polymyxin B exposure (24 h AUC), population analysis profiles showed similar growth of polymyxin B-resistant subpopulations. The HFIM data were well described by the mechanism-based model integrating three subpopulations (susceptible, intermediate and resistant). Compared with the susceptible subpopulation of mcr-1 -harbouring E. coli , the resistant subpopulation had an approximately 10-fold lower rate of killing due to polymyxin B treatment. Conclusions: Manipulating initial dose intensity of polymyxin B was not able to overcome plasmid-mediated resistance due to mcr-1 in E. coli . This reinforces the need to develop new combinatorial strategies to combat these highly resistant Gram-negative bacteria.

Indexed as

Drug Resistance, BacterialAnti-Bacterial AgentsEscherichia coli InfectionsEscherichia coli ProteinsMicrobial Sensitivity TestsMicrobial ViabilityModels, TheoreticalPolymyxin BAnti-Bacterial AgentsEscherichia coli ProteinsMCR-1 protein, E coliPolymyxin B

Identifiers

PMID28505268
PMCPMC5890756
OpenAlexW2738109995

What OpenQuestion holds

Textmetadata
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Registered trials

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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.