Evidence map›Paper›PMID 41310736›Full record

SynthesisCritical care (London, England)2025

Predictive enrichment using biomarkers in studies of critically-ill patients with sepsis: a systematic review.

Logan R Van Nynatten, Diyaa Bokhary, Michelle Yee Suet Wong, Jocelyn Wang, Henri Fero, Christopher McChesney, Kyle Fiorini, Leann Blake, Douglas D Fraser, Marat Slessarev and 3 more

Abstract readSystematic Review
In one paragraph

Synthesis in Critical care (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Observational
  5. Observational
  6. Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Proteomic profiling and pathway analyses reveal molecular signatures and immune networks in pediatric sepsis.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
    Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Review
  17. Review
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.

Logan R Van NynattenDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada. Logan.VanNynatten@lhsc.on.ca.
Diyaa BokharyDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Michelle Yee Suet WongDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Jocelyn WangDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Henri FeroDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Christopher McChesneyDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Kyle FioriniDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Leann BlakeDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Douglas D FraserDivision of Pediatric Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Marat SlessarevDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Aleksandra LeligdowiczDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Bram RochwergDepartment of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.
John BasmajiDivision of Critical Care Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis remains one of the most prevalent conditions necessitating admission to intensive care units and is associated with high mortality. Unfortunately, randomized trials examining therapeutics for critically-ill patients with sepsis have been disproportionately negative, failing to identify effective interventions, likely due to the dilution of treatment effects across highly diverse populations. Designing trials to identify patients that are most likely to benefit from an intervention based on biologic mechanism, known as predictive enrichment, may be an effective strategy for enhancing clinical trial efficacy. We conducted a systematic review to summarize the use of biological markers (biomarkers) used for predictive enrichment in randomized controlled trials (RCTs) including patients with sepsis.

methodsWe conducted this review following PRISMA-ScR guidelines. We searched OVID Medline, Embase, and the Cochrane Central Register of Controlled Trials databases. We included RCTs that enrolled adult patients with sepsis that used molecular biomarkers for predictive enrichment in their study design. We summarize study characteristics, biomarkers used, predictive enrichment strategies, and trial outcomes narratively without statistical pooling. Risk of bias of individual studies was assessed using the Cochrane Risk of Bias tool.

resultsOf the 1,718 citations found with the search, we included 12 eligible studies. All studies used either blood-based circulating proteins or lipopolysaccharide markers for predictive enrichment. Five studies (42%) reported statistically significant impacts on the primary outcome, with three showing patient-important benefit (reduced mortality or disease severity) and two demonstrating improvements in surrogate outcomes related to biomarkers. Interventions that demonstrated benefit included immune, antimicrobial or coagulation modulating therapies. These five trials that showed benefit used suPAR, AT, mHLA-DR, IL-6 and EAA as biomarkers for predictive enrichment.

conclusionsThis review characterizes the use of biomarkers for predictive enrichment in randomized trials of critically-ill patients with sepsis. Although the studies were heterogeneous in design and limited in number, those that employed biomarker-based enrichment strategies demonstrate a promising signal for enhanced clinical trial efficiency. The use of biomarkers for predictive enrichment in critical care trial design requires further exploration, investigation and validation.

Indexed as

BiomarkersSepsisCritical IllnessHumansIntensive Care UnitsRandomized Controlled Trials as TopicBiomarkersBiomarkerCritical illnessPredictive enrichmentProteomicsSepsis

Identifiers

PMID41310736
PMCPMC12659080

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.