Evidence map›Paper›PMID 36675106›Full record

ArticleInternational journal of molecular sciences2023

GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer.

Elinor A Chapman, James Baker, Prashant Aggarwal, David M Hughes, Amara C Nwosu, Mark T Boyd, Catriona R Mayland, Stephen Mason, John Ellershaw, Chris S Probert and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
3.1field-weighted citation impact, top 8% 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

14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 28 citations in OpenAlex.

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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 at 1 institution in 1 country.

Elinor A ChapmanSchool of Medical and Health Sciences, Bangor University, Bangor LL57 2DG, UK.ORCID 0000-0002-4398-1705
James BakerInstitute of Systems Medicine and Integrative Biology, University of Liverpool, Liverpool L69 7BE, UK.ORCID 0000-0002-6562-1081
Prashant AggarwalInstitute of Systems Medicine and Integrative Biology, University of Liverpool, Liverpool L69 7BE, UK.ORCID 0000-0002-5146-1400
David M HughesDepartment of Health Data Science, University of Liverpool, Liverpool L69 3GF, UK.
Amara C NwosuAcademic Palliative & End of Life Care Department, Liverpool University Hospitals NHS Foundation Trust, Liverpool L7 8XP, UK.ORCID 0000-0003-0014-3741
Mark T BoydInstitute of Systems Medicine and Integrative Biology, University of Liverpool, Liverpool L69 7BE, UK.ORCID 0000-0002-2336-2106
Catriona R MaylandDepartment of Oncology and Metabolism, University of Sheffield, Sheffield S10 2RX, UK.ORCID 0000-0002-1440-9953
Stephen MasonPalliative Care Unit, Institute of Life Course & Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK.
John EllershawAcademic Palliative & End of Life Care Department, Liverpool University Hospitals NHS Foundation Trust, Liverpool L7 8XP, UK.
Chris S ProbertInstitute of Systems Medicine and Integrative Biology, University of Liverpool, Liverpool L69 7BE, UK.
Séamus CoyleLiverpool Head and Neck Cancer Centre, University of Liverpool, Liverpool L69 3BX, UK.
University of Liverpool · GB

Funding

Medical Research Council MR/R024847/1North West Cancer Research SI2018.11University of Liverpool Technology directorate, knowledge exchange "The Biology of Dying" projectWellcome Trust 202022/Z/16/Z
6 · The paper itself

Abstract

Predicting when a patient with advanced cancer is dying is a challenge and currently no prognostic test is available. We hypothesised that a dying process from cancer is associated with metabolic changes and specifically with changes in volatile organic compounds (VOCs). We analysed urine from patients with lung cancer in the last weeks of life by headspace gas chromatography mass spectrometry. Urine was acidified or alkalinised before analysis. VOC changes in the last weeks of life were identified using univariate, multivariate and linear regression analysis; 12 VOCs increased (11 from the acid dataset, 2 from the alkali dataset) and 25 VOCs decreased (23 from the acid dataset and 3 from the alkali dataset). A Cox Lasso prediction model using 8 VOCs predicted dying with an AUC of 0.77, 0.78 and 0.85 at 30, 20 and 10 days and stratified patients into a low (median 10 days), medium (median 50 days) or high risk of survival. Our data supports the hypothesis there are specific metabolic changes associated with the dying. The VOCs identified are potential biomarkers of dying in lung cancer and could be used as a tool to provide additional prognostic information to inform expert clinician judgement and subsequent decision making.

Indexed as

Lung NeoplasmsVolatile Organic CompoundsBiomarkersGas Chromatography-Mass SpectrometryHumansLinear ModelsSolid Phase MicroextractionBiomarkersVolatile Organic CompoundsbiomarkersdyingGC-MSlung cancerpalliativeSPMEurineVOCsvolatile

Identifiers

PMID36675106
PMCPMC9867309
OpenAlexW4316039757

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.