Evidence map›Paper›PMID 34541549›Full record

ArticleLiver cancer international2021

Salivary Metabolites are Promising Non-Invasive Biomarkers of Hepatocellular Carcinoma and Chronic Liver Disease.

Courtney E Hershberger, Alejandro I Rodarte, Shirin Siddiqi, Amika Moro, Lou-Anne Acevedo-Moreno, J Mark Brown, Daniela S Allende, Federico Aucejo, Daniel M Rotroff

Open access · diamondAbstract read
In one paragraph

Article in Liver cancer international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

27 citing papers in PubMed, 30 citations in OpenAlex.

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  20. [Research and exploration of salivary biological markers for hepatitis B-related hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2023
    Article
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

9 authors at 2 institutions in 1 country.

Courtney E HershbergerDepartment of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, OH, USA.
Alejandro I RodarteDepartment of General Surgery, Cleveland Clinic, OH, USA.
Shirin SiddiqiDepartment of General Surgery, Cleveland Clinic, OH, USA.
Amika MoroDepartment of General Surgery, Cleveland Clinic, OH, USA.
Lou-Anne Acevedo-MorenoDepartment of General Surgery, Cleveland Clinic, OH, USA.
J Mark BrownDepartment of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, OH, USA.
Daniela S AllendeDepartment of Pathology, Cleveland Clinic, OH, USA.
Federico AucejoDepartment of General Surgery, Cleveland Clinic, OH, USA.
Daniel M RotroffDepartment of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, OH, USA.ORCID 0000-0003-0553-3220
Cleveland Clinic · USCleveland Clinic Lerner College of Medicine · US

Funding

Project Two - Exercise Training Decreases Alcohol Drinking by an FGF21-Dependent MechanismP50AA024333 · NIAAA · CLEVELAND CLINIC LERNER COM-CWRU · PI Srinivasan Dasarathy · 2016 to 2026
$19.6M
Project 3: Microbiota generated aryl sulfates and secondary bile acids in cardiometabolic diseaseP01HL147823 · NHLBI · CLEVELAND CLINIC LERNER COM-CWRU · PI Stanley L Hazen · 2019 to 2026
$17.0M
The Role of Bacterial Choline Metabolism in Host Stress ResponsesR01DK120679 · NIDDK · CLEVELAND CLINIC LERNER COM-CWRU · PI BROWN, JONATHAN MARK · 2019 to 2022
$1.6M
NHLBI NIH HHS P01 HL147823NIAAA NIH HHS P50 AA024333NIDDK NIH HHS R01 DK120679
6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) is a leading causes of cancer mortality worldwide. Improved tools are needed for detecting HCC so that treatment can begin as early as possible. Current diagnostic approaches and existing biomarkers, such as alpha-fetoprotein (AFP) lack sensitivity, resulting in too many false negative diagnoses. Machine-learning may be able to identify combinations of biomarkers that provide more robust predictions and improve sensitivity for detecting HCC. We sought to evaluate whether metabolites in patient saliva could distinguish those with HCC, cirrhosis, and those with no documented liver disease. METHODS AND

resultsWe tested 125 salivary metabolites from 110 individuals (43 healthy, 37 HCC, 30 cirrhosis) and identified 4 metabolites that displayed significantly different abundance between groups (FDR CONCLUSIONS AND IMPACT: Metabolites detectable in saliva may represent products of disease pathology or a breakdown in liver function. Notably, combinations of salivary metabolites derived from machine-learning may serve as promising non-invasive biomarkers for the detection of HCC.

Indexed as

cirrhosisliver cancermachine learningsMetabolomicsrisk factor

Identifiers

PMID34541549
PMCPMC8447405
OpenAlexW3164701234

What OpenQuestion holds

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Registered trials

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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.