Kevin Lamote

Dr. Kevin Lamote

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 September 2020 in Critical Reviews in Oncology/Hematology
Verified
Journal Article
Closed access
EJEline Janssens
Eline Janssens
JMJan P van Meerbeeck
Jan P van Meerbeeck
KLKevin Lamote
Kevin Lamote

1 October 2012 in Soil Dynamics and Earthquake Engineering
Verified
Journal Article
Closed access
AZA. Athanasopoulos - Zekkos
A. Athanasopoulos - Zekkos
KLKevin Lamote
Kevin Lamote
GAG.A. Athanasopoulos
G.A. Athanasopoulos

27 September 2017 in Oncotarget
Verified
Journal Article
Open access
PDF file
KLKevin Lamote
Kevin Lamote
PBPaul Brinkman
Paul Brinkman
LVLore Vandermeersch
Lore Vandermeersch
MVMatthijs Vynck
Matthijs Vynck
PSPeter J. Sterk
Peter J. Sterk
JMJan P. van Meerbeeck
Jan P. van Meerbeeck
Breath analysis by gas chromatography-mass spectrometry and electronic nose to screen for pleural mesothelioma: a cross-sectional case-control study Breath analysis by gas chromatography-mass spectrometry and electronic nose to screen for pleural mesothelioma: A cross-sectional case-control study

21 July 2020 in Journal of Breath Research
Verified
Journal Article
Closed access
KLKevin Lamote
Kevin Lamote
EJEline Janssens
Eline Janssens
ESEline Schillebeeckx
Eline Schillebeeckx
TLTherese S Lapperre
Therese S Lapperre
BWBenedicte De Winter
Benedicte De Winter
JMJan P van Meerbeeck
Jan P van Meerbeeck

17 November 2021 in European Respiratory Review
Verified
Journal Article
Open access
PDF file
ESEline Schillebeeckx
Eline Schillebeeckx
JMJan P. van Meerbeeck
Jan P. van Meerbeeck
KLKevin Lamote
Kevin Lamote
Malignant pleural mesothelioma (MPM) is characterised by late-stage diagnosis and poor prognosis. Currently, no screening tool is advocated and diagnosis is based on invasive techniques, which are not well tolerated. Non-invasive diagnostic biomarkers have shown potential and could have a huge clinical benefit. However, despite extensive research, there is no consensus yet on their clinical use, with many articles reporting contradicting results, limiting their clinical implementation. The aim of this systematic review is therefore to explore the different semi- and non-invasive diagnostic markers in several human matrices and identify those that might clinically be relevant. A total of 100 articles were selected through Web of Science and PubMed, with 56 articles included in the quantitative analysis. Although many studies have reported on the diagnostic accuracy of MPM biomarkers such as serum mesothelin and high-mobility group box protein 1 and plasma fibulin-3, none have resulted in a validated test for early detection. Future research should focus on external validation, combinations into biomarker panels, the inclusion of early stage MPM patients and a combination of different biomarker matrices, as well as new markers.

21 December 2017 in European Respiratory Journal
Verified
Journal Article
Closed access
KLKevin Lamote
Kevin Lamote
MVMatthijs Vynck
Matthijs Vynck
OTOlivier Thas
Olivier Thas
JCJoris Van Cleemput
Joris Van Cleemput
KNKristiaan Nackaerts
Kristiaan Nackaerts
JMJan P. van Meerbeeck
Jan P. van Meerbeeck
Malignant pleural mesothelioma (MPM) is predominantly caused by asbestos exposure and has a poor prognosis. Breath contains volatile organic compounds (VOCs) and can be explored as an early detection tool. Previously, we used multicapillary column/ion mobility spectrometry (MCC/IMS) to discriminate between patients with MPM and asymptomatic high-risk persons with a high rate of accuracy. Here, we aim to validate these findings in different control groups.Breath and background samples were obtained from 52 patients with MPM, 52 healthy controls without asbestos exposure (HC), 59 asymptomatic former asbestos workers (AEx), 41 patients with benign asbestos-related diseases (ARD), 70 patients with benign non-asbestos-related lung diseases (BLD) and 56 patients with lung cancer (LC).After background correction, logistic lasso regression and receiver operating characteristic (ROC) analysis, the MPM group was discriminated from the HC, AEx, ARD, BLD and LC groups with 65%, 88%, 82%, 80% and 72% accuracy, respectively. Combining AEx and ARD patients resulted in 94% sensitivity and 96% negative predictive value (NPV). The most important VOCs selected were P1, P3, P7, P9, P21 and P26.We discriminated MPM patients from at-risk subjects with great accuracy. The high sensitivity and NPV allow breath analysis to be used as a screening tool for ruling out MPM.