Evidence map›Paper›PMID 42817452›Full record

Observational studySensors (Basel, Switzerland)2026

Urinary Volatile Organic Compounds as Non-Invasive Biomarkers to Distinguish Hepatocellular Carcinoma from Cirrhosis: A Multicentre Diagnostic Accuracy Study.

Yaqza Hussain, Arif Atique, Ayman Bannaga, Krishna C Persaud, Ramesh P Arasaradnam, Tendency Study Group

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Sensors (Basel, Switzerland), 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

6 authors.

Yaqza HussainDepartment of Gastroenterology, Sandwell and West Birmingham NHS Trust, Birmingham B71 4HJ, UK.
Arif AtiqueInstitute of Precision Diagnostics & Translational Medicine, University Hospitals Coventry and Warwickshire NHS Trust, Coventry CV2 2DX, UK.ORCID 0009-0008-2598-8760
Ayman BannagaDepartment of Gastroenterology, Queen Elizabeth Hospital Birmingham, Birmingham B15 2GW, UK.ORCID 0000-0003-4814-7864
Krishna C PersaudDepartment of Chemical Engineering and Analytical Science, University of Manchester, Manchester M13 9PL, UK.
Ramesh P ArasaradnamInstitute of Precision Diagnostics & Translational Medicine, University Hospitals Coventry and Warwickshire NHS Trust, Coventry CV2 2DX, UK.ORCID 0000-0002-2231-3062
Tendency Study Group

Funding

Guts UK TRN2021_05
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) typically arises on a background of cirrhosis and carries high mortality, in large part because current surveillance tools-ultrasound and serum AFP-have suboptimal sensitivity for early-stage disease. We investigated whether urinary volatile organic compounds (VOCs) could provide a more accurate non-invasive approach. Across four UK centres, 256 participants were recruited: 72 with confirmed HCC and 184 with cirrhosis but no malignancy. Complete urine VOC profiles were obtained using an eight-sensor electronic nose in 190 participants (58 HCC, 132 cirrhosis). Seven of the eight sensors showed statistically significant differences between groups, all reaching

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularLiver CirrhosisLiver NeoplasmsVolatile Organic CompoundsAgedBiomarkersDiagnosis, DifferentialFemaleHumansMaleMiddle AgedROC CurveBiomarkersBiomarkers, TumorVolatile Organic Compoundsbiomarkerscirrhosisearly diagnosishepatocellular carcinomanon-invasive screeningvolatile organic compounds

Identifiers

PMID42817452
PMCPMC13611087

What Socratic holds

Textmetadata
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.