Evidence map›Paper›PMID 34811968›Full record

ArticleCPT: pharmacometrics & systems pharmacology2021

Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients.

Patrick O Hanafin, Roger L Nation, Marc H Scheetz, Alexandre P Zavascki, Ana M Sandri, Andrea L Kwa, Benjamin P Z Cherng, Christine J Kubin, Michael T Yin, Jiping Wang and 3 more

Open access · goldAbstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

18 citing papers in PubMed, 31 citations in OpenAlex.

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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

13 authors at 10 institutions in 4 countries.

Patrick O HanafinDivision of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Roger L NationDrug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia.
Marc H ScheetzDepartment of Pharmacy Practice and Pharmacometric Center of Excellence, Midwestern University Chicago College of Pharmacy, Downers Grove, Illinois, USA.
Alexandre P ZavasckiDepartment of Internal Medicine, Medical School, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
Ana M SandriInfectious Diseases Service, Hospital São Lucas da Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil.
Andrea L KwaDepartment of Pharmacy, Singapore General Hospital, Singapore, Singapore.
Benjamin P Z CherngDepartment of Infectious Diseases, Singapore General Hospital, Singapore, Singapore.
Christine J KubinNew York-Presbyterian Hospital/Columbia University Irving Medical Center, New York, New York, USA.
Michael T YinDivision of Infectious Diseases, Department of Internal Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA.
Jiping WangBiomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.
Jian LiBiomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.
Keith S KayeDivision of Infectious Diseases, University of Michigan Medical School, Ann Arbor, Michigan, USA.
Gauri G RaoDivision of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Monash University · AUSingapore General Hospital · SGUniversity of North Carolina at Chapel Hill · USAustralian Regenerative Medicine Institute · AUColumbia University · USColumbia University Irving Medical Center · USMidwestern University · USPontifícia Universidade Católica do Rio Grande do Sul · BRUniversidade Federal do Rio Grande do Sul · BRUniversity of Michigan–Ann Arbor · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polymyxin B (PMB) has reemerged as a last-line therapy for infections caused by multidrug-resistant gram-negative pathogens, but dosing is challenging because of its narrow therapeutic window and pharmacokinetic (PK) variability. Population PK (POPPK) models based on suitably powered clinical studies with appropriate sampling strategies that take variability into consideration can inform PMB dosing to maximize efficacy and minimize toxicity and resistance. Here we reviewed published PMB POPPK models and evaluated them using an external validation data set (EVD) of patients who are critically ill and enrolled in an ongoing clinical study to assess their utility. Seven published POPPK models were employed using the reported model equations, parameter values, covariate relationships, interpatient variability, parameter covariance, and unexplained residual variability in NONMEM (Version 7.4.3). The predictive ability of the models was assessed using prediction-based and simulation-based diagnostics. Patient characteristics and treatment information were comparable across studies and with the EVD (n = 40), but the sampling strategy was a main source of PK variability across studies. All models visually and statistically underpredicted EVD plasma concentrations, but the two-compartment models more accurately described the external data set. As current POPPK models were inadequately predictive of the EVD, creation of a new POPPK model based on an appropriately powered clinical study with an informed PK sampling strategy would be expected to improve characterization of PMB PK and identify covariates to explain interpatient variability. Such a model would support model-informed precision dosing frameworks, which are urgently needed to improve PMB treatment efficacy, limit resistance, and reduce toxicity in patients who are critically ill.

Indexed as

Critical IllnessAdolescentAdultAgedAged, 80 and overAnti-Bacterial AgentsAPACHEComputer SimulationFemaleHumansMaleMiddle AgedModels, BiologicalMonte Carlo MethodPolymyxin BYoung AdultAnti-Bacterial AgentsPolymyxin B

Identifiers

PMID34811968
PMCPMC8674003
OpenAlexW3216835035

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.