Markar, Sheraz, Wiggins, Tom, Antonowicz, Stefan, Chin, Sung-tong, Romano, Andrea, Nikolic, Konstantin ORCID: https://orcid.org/0000-0002-6551-2977, Evans, Benjamin, Cunningham, David, Mughal, Muntzer, Lagergren, Jesper and Hanna, George (2018) Assessment of a noninvasive exhaled breath test for the diagnosis of oesophagogastric cancer. JAMA oncology, 4 (7). pp. 970-976. ISSN 2374-2437

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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.

Item Type:	Article
Identifier:	10.1001/jamaoncol.2018.0991
Subjects:	Construction and engineering > Biomedical engineering Medicine and health > Research methodologies
Related URLs:	Publisher
Depositing User:	Konstantin Nikolic
Date Deposited:	15 Jun 2021 12:42
Last Modified:	04 Nov 2024 11:45
URI:	https://repository.uwl.ac.uk/id/eprint/7965

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