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Assessment of a noninvasive exhaled breath test for the diagnosis of oesophagogastric cancer

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Title: Assessment of a noninvasive exhaled breath test for the diagnosis of oesophagogastric cancer
Authors: Markar, S
Wiggins, T
Antonowicz, S
Chin, S-T
Romano, A
Nikolic, K
Evans, B
Cunningham, D
Mughal, M
Lagergren, J
Hanna, G
Item Type: Journal Article
Abstract: Importance Early esophagogastric cancer (OGC) stage presents with nonspecific symptoms. Objective The aim of this study was to determine the accuracy of a breath test for the diagnosis of OGC in a multicenter validation study. Design, Setting, and Participants Patient recruitment for this diagnostic validation study was conducted at 3 London hospital sites, with breath samples returned to a central laboratory for selected ion flow tube mass spectrometry (SIFT-MS) analysis. Based on a 1:1 cancer:control ratio, and maintaining a sensitivity and specificity of 80%, the sample size required was 325 patients. All patients with cancer were on a curative treatment pathway, and patients were recruited consecutively. Among the 335 patients included; 172 were in the control group and 163 had OGC. Interventions Breath samples were collected using secure 500-mL steel breath bags and analyzed by SIFT-MS. Quality assurance measures included sampling room air, training all researchers in breath sampling, regular instrument calibration, and unambiguous volatile organic compounds (VOCs) identification by gas chromatography mass spectrometry. Main Outcomes and Measures The risk of cancer was identified based on a previously generated 5-VOCs model and compared with histopathology-proven diagnosis. Results Patients in the OGC group were older (median [IQR] age 68 [60-75] vs 55 [41-69] years) and had a greater proportion of men (134 [82.2%]) vs women (81 [47.4%]) compared with the control group. Of the 163 patients with OGC, 123 (69%) had tumor stage T3/4, and 106 (65%) had nodal metastasis on clinical staging. The predictive probabilities generated by this 5-VOCs diagnostic model were used to generate a receiver operator characteristic curve, with good diagnostic accuracy, area under the curve of 0.85. This translated to a sensitivity of 80% and specificity of 81% for the diagnosis of OGC. Conclusions and Relevance This study shows the potential of breath analysis in noninvasive diagnosis of OGC in the clinical setting. The next step is to establish the diagnostic accuracy of the test among the intended population in primary care where the test will be applied. Introduction
Issue Date: 17-May-2018
Date of Acceptance: 16-Feb-2018
URI: http://hdl.handle.net/10044/1/61303
DOI: https://dx.doi.org/10.1001/jamaoncol.2018.0991
ISSN: 2374-2445
Publisher: American Medical Association
Start Page: 970
End Page: 976
Journal / Book Title: JAMA Oncology
Volume: 4
Issue: 7
Copyright Statement: This is an open access article distributed under the terms of the CC-BY License. © 2018 Markar SR et al. JAMA Oncology. (https://jamanetwork.com/journals/jamaoncology/pages/instructions-for-authors#SecOpenAccess)
Sponsor/Funder: Biotechnology and Biological Sciences Research Council (BBSRC)
Imperial College Healthcare Charity
Biotechnology and Biological Sciences Research Cou
Engineering & Physical Science Research Council (EPSRC)
European Research Council
Funder's Grant Number: BB/L018268/1
141514
4020012831
EP/N002474/1
319818
Publication Status: Published
Open Access location: https://jamanetwork.com/journals/jamaoncology/fullarticle/2681564?utm_campaign=articlePDF&utm_medium=articlePDFlink&utm_source=articlePDF&utm_content=jamaoncol.2018.0991
Appears in Collections:Division of Surgery
Electrical and Electronic Engineering
Faculty of Medicine



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