Evidence map›Paper›PMID 42582583›Full record

ArticleTranslational lung cancer research2026

Baseline IL-6, IL-8, IFN-ω, and perforin as prognostic biomarkers in immune checkpoint inhibitor-treated metastatic non-small cell lung cancer.

Varshini Odayar, Hyojung Jang, Ashley Pearson, Jadyn James, Emily Kloska, Benjamin H Singer, Shadia Jalal, Charles J Nock, Lili Zhao, Michael Green and 1 more

Abstract read
In one paragraph

Article in Translational lung cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Varshini Odayar *Division of Hematology/Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Hyojung Jang *Division of Biostatistics and Informatics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Ashley PearsonDepartment of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
Jadyn JamesDepartment of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
Emily KloskaSection of Oncology, Lieutenant Colonel Charles S. Kettles VA Medical Center, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Benjamin H SingerDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Shadia JalalSection of Oncology, Richard L. Roudebush VA Medical Center, VA Indiana Healthcare System, Indianapolis, IN, USA.
Charles J NockSection of Oncology, Louis Stokes Cleveland VA Medical Center, VA Northeast Ohio Healthcare System, Cleveland, OH, USA.
Lili ZhaoDivision of Biostatistics and Informatics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Michael GreenDepartment of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
Nithya RamnathDivision of Hematology/Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.

Funding

CSRD VA I01 CX001560
6 · The paper itself

Abstract

Background: Prognostic serum biomarkers of immune checkpoint inhibitor (ICI) efficacy in non-small cell lung cancer (NSCLC) are sparse. We evaluated baseline cytokines as markers of outcomes in ICI-treated metastatic NSCLC. Methods: Baseline serum cytokines were quantified in 96 patients with metastatic NSCLC receiving ICIs. Separate multivariable models were fit for progression-free survival (PFS) and overall survival (OS), adjusting for clinical covariates. Hazard ratios (HRs) were expressed per doubling in cytokine concentration. Significant cytokines were then incorporated into multivariable Cox models, and model discrimination was assessed using time-dependent area under the curve (AUC). Latent class analysis (LCA) was performed to identify cytokine-defined patient phenotypes associated with survival. Results: Each doubling of interleukin-6 (IL-6) increased the hazard of death by 34% [HR =1.34; 95% confidence interval (CI): 1.13-1.60; P<0.001] and interleukin-8 (IL-8) by 36% (HR =1.36; 95% CI: 1.16-1.59; P<0.001). Conversely, each doubling of interferon-omega (IFN-ω) (HR =0.87; 95% CI: 0.80-0.95; P=0.001) and perforin (HR =0.50; 95% CI: 0.33-0.76; P<0.001) decreased mortality risk. Multivariable cytokine models incorporating IL-6, IL-8, IFN-ω, and perforin achieved time-dependent AUCs >0.70 for PFS and OS. LCA identified two cytokine classes: one enriched for IL-6/IL-8 (poor outcomes) and another enriched for IFN-ω/perforin (favorable outcomes). Conclusions: Higher baseline serum IL-6 and IL-8 concentrations were associated with inferior survival, whereas higher baseline serum IFN-ω and perforin were associated with improved survival in ICI-treated metastatic NSCLC, defining distinct host immune-inflammatory phenotypes with prognostic relevance.

Indexed as

immune checkpoint inhibitor (ICI)interferon-omega (IFN-ω)Interleukin-6 (IL-6)interleukin-8 (IL-8)perforin

Identifiers

PMID42582583
PMCPMC13458376

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.