ArticleBritish journal of cancer2024
Prediction of response to neoadjuvant chemo-immunotherapy in patients with esophageal squamous cell carcinoma by a rapid breath test.
Article in British journal of cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 4 citations in OpenAlex.
- AI-based neoadjuvant immunotherapy response prediction across pan-cancer: a comprehensive review.Cancer cell international · 2025Review
- A computed tomography-based deep learning radiomics for predicting the response to neoadjuvant chemotherapy combined with immunotherapy in patients with locally advanced esophageal cancer: a multicenter cohort study.Journal of thoracic disease · 2025Article
- Application of machine learning based on habitat imaging and vision transformer to predict treatment response of locally advanced esophageal squamous cell carcinoma following neoadjuvant chemoimmunotherapy: a multi-center study.Frontiers in immunology · 2025Article
- A machine learning radiomics based on enhanced computed tomography to predict neoadjuvant immunotherapy for resectable esophageal squamous cell carcinoma.Frontiers in immunology · 2024Article
- From tumor microenvironment to emerging biomarkers: the reshaping of the esophageal squamous cell carcinoma tumor microenvironment by neoadjuvant chemotherapy combined with immunotherapy.Frontiers in immunology · 2024Review
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Authors and funding
15 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundNeoadjuvant chemo-immunotherapy combination has shown remarkable advances in the management of esophageal squamous cell carcinoma (ESCC). However, the identification of a reliable biomarker for predicting the response to this chemo-immunotherapy regimen remains elusive. While computed tomography (CT) is widely utilized for response evaluation, its inherent limitations in terms of accuracy are well recognized. Therefore, in this study, we present a novel technique to predict the response of ESCC patients before receiving chemo-immunotherapy by testing volatile organic compounds (VOCs) in exhaled breath.
methodsThis study employed a prospective-specimen-collection, retrospective-blinded-evaluation design. Patients' baseline breath samples were collected and analyzed using high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS). Subsequently, patients were categorized as responders or non-responders based on the evaluation of therapeutic response using pathology (for patients who underwent surgery) or CT images (for patients who did not receive surgery).
resultsA total of 133 patients were included in this study, with 91 responders who achieved either a complete response (CR) or a partial response (PR), and 42 non-responders who had stable disease (SD) or progressive disease (PD). Among 83 participants who underwent both evaluations with CT and pathology, the paired t-test revealed significant differences between the two methods (p < 0.05). For the breath test prediction model using breath test data from all participants, the validation set demonstrated mean area under the curve (AUC) of 0.86 ± 0.06. For 83 patients with pathological reports, the breath test achieved mean AUC of 0.845 ± 0.123.
conclusionsSince CT has inherent weakness in hollow organ assessment and no other ideal biomarker has been found, our study provided a noninvasive, feasible, and inexpensive tool that could precisely predict ESCC patients' response to neoadjuvant chemo-immunotherapy combination using breath test based on HPPI-TOFMS.
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