Evidence map›Paper›PMID 40248699›Full record

Trial reportFrontiers in immunology2025

Exhaled breath analysis with the use of an electronic nose to predict response to immune checkpoint inhibitors in patients with metastatic melanoma: melaNose trial.

Brigit van Dijk, Ivonne J H Schoenaker, Astrid A M van der Veldt, Jan Willem B de Groot

Abstract readClinical TrialObservational Study
In one paragraph

Trial report in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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5 · Who and what money

Authors and funding

4 authors.

Brigit van DijkDepartment of Medical Oncology, Erasmus Medical Center Medical Center (MC), Rotterdam, Netherlands.
Ivonne J H SchoenakerIsala Oncology Center, Isala, Zwolle, Netherlands.
Astrid A M van der VeldtDepartment of Medical Oncology, Erasmus Medical Center Medical Center (MC), Rotterdam, Netherlands.
Jan Willem B de GrootIsala Oncology Center, Isala, Zwolle, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Immune checkpoint inhibitors (ICIs) have significantly improved the overall survival for patients with different solid tumors. However, there is an urgent need for predictive biomarkers to identify patients with metastatic melanoma who do not benefit from treatment with ICIs, to prevent unnecessary immune related adverse events (irAEs). Electronic noses (eNoses) showed promising results in the detection of cancer as well as the prediction of response outcome in patients with cancer. In this feasibility study, we aimed to investigate whether the breath pattern measured using eNose can be used as a simple biomarker to predict clinical benefit to first-line treatment with ICIs in patients with metastatic melanoma. Methods: In this prospective, observational single-center feasibility study, patients with metastatic melanoma performed a breath test using Aeonose™ before start of first-line treatment with ICIs. The detected exhaled breath pattern of volatile organic compounds (VOC) was used for machine learning in a training set to develop a model to identify patients who do not benefit from treatment with ICIs. Lack of clinical benefit was defined as progressive disease according to best tumor response using RECIST v1.1. Primary outcome measures were sensitivity, specificity and accuracy. Results: The eNose showed a distinct breath pattern between patients with and without clinical benefit from ICIs. To identify patients who do not benefit from first-line ICIs treatment, breath pattern analysis using the eNose resulted in a sensitivity of 88%, specificity of 79%, and accuracy of 85%. Conclusion: Exhaled breath analysis using eNose can identify patients with metastatic melanoma who will not benefit from first-line treatment with ICIs and guide treatment strategies. When validated in an external cohort, eNose could be a useful tool to select these patients for alternative treatment strategies in clinical practice.

Indexed as

Electronic NoseImmune Checkpoint InhibitorsMelanomaAdultAgedBiomarkers, TumorBreath TestsExhalationFeasibility StudiesFemaleHumansMaleMiddle AgedNeoplasm MetastasisProspective StudiesTreatment OutcomeBiomarkers, TumorImmune Checkpoint InhibitorsVolatile Organic Compoundsclinical benefit predictioneNoseexhaled breath analysisimmune checkpoint inhibitor (ICI)melanomavolatile organic compound (VOC)

Identifiers

PMID40248699
PMCPMC12003352

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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.