Evidence map›Paper›PMID 37940985›Full record

ArticleCritical care (London, England)2023

Bayesian methods: a potential path forward for sepsis trials.

George Tomlinson, Ali Al-Khafaji, Steven A Conrad, Faith N F Factora, Debra M Foster, Claude Galphin, Kyle J Gunnerson, Sobia Khan, Roopa Kohli-Seth, Paul McCarthy and 8 more

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Critical care (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Review
  2. Article
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  4. Observational
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  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

George TomlinsonDalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-9328-6399
Ali Al-KhafajiDepartment of Critical Care Medicine, University of Pittsburgh, 3550 Terrace Street, 600 Scaife Hall, Pittsburgh, PA, 15261, USA.
Steven A ConradDepartments of Medicine, Emergency Medicine, Pediatrics and Surgery, Louisiana State University Health, Shreveport, LA, USA.ORCID https://orcid.org/0000-0002-4014-969X
Faith N F FactoraDepartment of Intensive Care and Resuscitation, Cleveland Clinic, Cleveland, OH, USA.ORCID https://orcid.org/0000-0003-4204-9825
Debra M FosterSpectral Medical Inc, Toronto, ON, Canada.
Claude GalphinSoutheast Renal Research Institute, CHI Memorial Hospital, Chattanooga, TN, USA.
Kyle J GunnersonDepartments of Emergency Medicine, Anesthesiology, and Internal Medicine, University of Michigan Medical Center, Ann Arbor, MI, USA.ORCID https://orcid.org/0000-0002-0977-194X
Sobia KhanDepartment of Medicine, Stony Brook University Hospital, Stony Brook, NY, USA.
Roopa Kohli-SethInstitute for Critical Care Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Paul McCarthyWest Virginia University, Heart & Vascular Institute, Morgantown, WV, USA.
Nikhil K MeenaDivision of Pulmonary and Critical Care Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Ronald G PearlDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA, USA.ORCID https://orcid.org/0000-0002-3998-7637
Jean-Sebastien RachoinCooper University Healthcare, Cooper Medical School of Rowan University, Camden, NJ, USA.
Ronald RainsPulmonary Associates, Univ of Colorado Health-Memorial Hospital, Colorado Springs, CO, USA.
Michael SeneffDepartment of Anesthesia and Critical Care, George Washington University Hospital, Washington, DC, USA.
Mark TidswellPulmonary and Critical Care Division, Baystate Medical Center, Springfield, MA, USA.
Paul M WalkerSpectral Medical Inc, Toronto, ON, Canada.
John A KellumDepartment of Critical Care Medicine, University of Pittsburgh, 3550 Terrace Street, 600 Scaife Hall, Pittsburgh, PA, 15261, USA. kellum@pitt.edu.ORCID https://orcid.org/0000-0003-1995-2653

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGiven the success of recent platform trials for COVID-19, Bayesian statistical methods have become an option for complex, heterogenous syndromes like sepsis. However, study design will require careful consideration of how statistical power varies using Bayesian methods across different choices for how historical data are incorporated through a prior distribution and how the analysis is ultimately conducted. Our objective with the current analysis is to assess how different uses of historical data through a prior distribution, and type of analysis influence results of a proposed trial that will be analyzed using Bayesian statistical methods.

methodsWe conducted a simulation study incorporating historical data from a published multicenter, randomized clinical trial in the US and Canada of polymyxin B hemadsorption for treatment of endotoxemic septic shock. Historical data come from a 179-patient subgroup of the previous trial of adult critically ill patients with septic shock, multiple organ failure and an endotoxin activity of 0.60-0.89. The trial intervention consisted of two polymyxin B hemoadsorption treatments (2 h each) completed within 24 h of enrollment.

resultsIn our simulations for a new trial of 150 patients, a range of hypothetical results were observed. Across a range of baseline risks and treatment effects and four ways of including historical data, we demonstrate an increase in power with the use of clinically defensible incorporation of historical data. In one possible trial result, for example, with an observed reduction in risk of mortality from 44 to 37%, the probability of benefit is 96% with a fixed weight of 75% on prior data and 90% with a commensurate (adaptive-weighting) prior; the same data give an 80% probability of benefit if historical data are ignored.

conclusionsUsing Bayesian methods and a biologically justifiable use of historical data in a prior distribution yields a study design with higher power than a conventional design that ignores relevant historical data. Bayesian methods may be a viable option for trials in critical care medicine where beneficial treatments have been elusive.

Indexed as

SepsisShock, SepticAdaptive Clinical Trials as TopicAdultBayes TheoremHumansPolymyxin BResearch DesignPolymyxin BEndotoxemiaEndotoxin septic shockHemadsorptionPolymyxin-BSeptic shockStatistical methodsTrial simulation

Identifiers

PMID37940985
PMCPMC10634134

What OpenQuestion holds

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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.