Evidence mapPaperPMID 39400560Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2025

Characterization of the Biological Variability of the Angiome Biomarkers over Time in Healthy Participants.

Yingmiao Liu, Jiatong Li, Jing Lyu, Lauren E Howard, Alexander B Sibley, Mark D Starr, John C Brady, Christy Arrowood, Elise C Kohn, S Percy Ivy and 4 more

Abstract read
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 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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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

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Yingmiao LiuDepartment of Medicine, Duke University Medical Center, Durham, North Carolina.ORCID 0000-0003-3516-5844
Jiatong LiYale University, New Haven, Connecticut.ORCID 0000-0003-0084-2470
Jing LyuDuke Cancer Institute, Durham, North Carolina.ORCID 0009-0008-8078-8569
Lauren E HowardDuke Cancer Institute, Durham, North Carolina.ORCID 0000-0003-3355-4483
Alexander B SibleyDuke Cancer Institute, Durham, North Carolina.ORCID 0000-0003-4552-1865
Mark D StarrDepartment of Medicine, Duke University Medical Center, Durham, North Carolina.ORCID 0009-0003-9664-6235
John C BradyDepartment of Medicine, Duke University Medical Center, Durham, North Carolina.ORCID 0009-0004-7982-1211
Christy ArrowoodDepartment of Medicine, Duke University Medical Center, Durham, North Carolina.ORCID 0009-0000-3263-9659
Elise C KohnNational Cancer Institute, Rockville, Maryland.ORCID 0000-0002-8631-9762
S Percy IvyNational Cancer Institute, Rockville, Maryland.ORCID 0000-0001-7747-072X
Herbert I HurwitzDepartment of Medicine, Duke University Medical Center, Durham, North Carolina.ORCID 0000-0003-3242-9197
James L AbbruzzeseDepartment of Medicine, Duke University Medical Center, Durham, North Carolina.ORCID 0000-0001-9223-2965
Kouros OwzarDuke Cancer Institute, Durham, North Carolina.ORCID 0000-0002-3340-1287
Andrew B NixonDepartment of Medicine, Duke University Medical Center, Durham, North Carolina.ORCID 0000-0003-3971-2964

Funding

Women's Cancer ProgramP30CA014236 · NCI · DUKE UNIVERSITY · 1985 to 2025
$66.3M
Division of Cancer Prevention, National Cancer Institute (DCP, NCI) UM1CA186704National Cancer Institute (NCI) CCSGNCI NIH HHS P30 CA014236NCI NIH HHS UM1 CA186704
6 · The paper itself

Abstract

backgroundBiomarker analyses are an integral part of cancer research. Despite the intense efforts to identify and characterize biomarkers in patients with cancer, little is known regarding the natural variation of biomarkers in healthy populations. Here we conducted a clinical study to evaluate the natural variability of biomarkers over time in healthy participants.

methodsThe angiome multiplex array, a panel of 25 circulating protein biomarkers, was assessed in 28 healthy participants across eight timepoints over the span of 60 days. We utilized the intraclass correlation coefficient (ICC) to quantify the reliability of the biomarkers. Adjusted ICC values were calculated under the framework of a linear mixed-effects model, taking into consideration age, sex, body mass index, fasting status, and sampling factors.

resultsICC was calculated to determine the reliability of each biomarker. Hepatocyte growth factor was the most stable marker (ICC = 0.973), while platelet-derived growth factor (PDGF)-BB was the most variable marker (ICC = 0.167). In total, ICC analyses revealed that 22 out of 25 measured biomarkers display good (≥0.4) to excellent (>0.75) ICC values. Three markers (PDGF-BB, TGFβ1, PDGF-AA) had ICC values <0.4. Greater age was associated with higher IL6 (P = 0.0114). Higher body mass index was associated with higher levels of IL6 (P = 0.0003) and VEGF-R3 (P = 0.0045).

conclusionsOf the 25 protein biomarkers measured over this short time period, 22 markers were found to have good or excellent ICC values, providing additional validation for this biomarker assay. IMPACT: These data further support the validation of the angiome biomarker assay and its application as an integrated biomarker in clinical trial testing.

Indexed as

Healthy VolunteersAdultBiomarkersBiomarkers, TumorFemaleHumansMaleMiddle AgedYoung AdultBiomarkersBiomarkers, Tumor

Identifiers

PMID39400560
PMCPMC11717622

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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 Socratic graph.