An observational study in Pancreas Cancer, Hepatocellular Carcinoma and Lung Cancer, sponsored by University of Oklahoma. Not yet recruiting at 1 site in United States. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-07-29.
Sponsored by University of Oklahoma · Observational
The purpose of this clinical trial is to evaluate whether volatile organic compound (VOC) signatures detected in the breath of patients with cancer can serve as a potential screening tool for the early detection of cancer.
This study aims to determine whether metabolic changes associated with cancer produce distinct alterations in exhaled breath compared with those of healthy individuals. Breath samples will be analyzed using machine learning techniques to identify volatile organic compound (VOC) patterns and develop diagnostic algorithms capable of detecting multiple types of cancer. The long-term goal is to establish a noninvasive, breath-based screening tool that can facilitate the early detection of various cancers.
Additionally, patients and healthy participants who consent to this study may opt in to be contacted in the future to provide additional breath samples.
3,235 studies on the registry are indexed under Pancreatic Neoplasms; 899 are open to participants now.
This study's planned enrollment of 2,000 is above the median of 200 across 620 observational studies indexed under Pancreatic Neoplasms.
Browse Pancreatic Neoplasms studies →University of Oklahoma is the lead sponsor of 424 studies on the registry; 99 are open to participants now.
Of its 42 completed or terminated interventional studies of FDA-regulated products, 16 (38%) have results posted.
Counted across the registry records on this site, refreshed daily.
Patients diagnosed with malignancies and healthy individuals who meet the inclusion criteria.
Exclusion Criteria:
Participants in this group either have a newly diagnosed, untreated cancer or a pre-existing cancer diagnosis but are not currently receiving anticancer therapy. Participants with a pre-existing diagnosis must not have received any anticancer treatment within the previous month.
Device: Proton Transfer Reaction Mass Spectrometry Analysis
Participants in this control group have no current or prior diagnosis of a malignancy.
Device: Proton Transfer Reaction Mass Spectrometry Analysis
This is a noninvasive intervention. Participants will be asked to provide a breath sample using a disposable mouthpiece equipped with a saliva/moisture trap and a non-rebreathing valve. Breath samples will be collected through normal, steady exhalation. The entire breath collection process is expected to take no more than 30 minutes to complete.
Also known as: PTR-MS
VOC Signature Collection.
The successful collection of breath samples from 1000 cancer patients and 1000 healthy volunteers.
Time frame: 2 Years
Assess the sensitivity of Machine Learning (ML) Algorithm In The Test Dataset.
Using the training dataset, qualitative output generated by the PTR-MS instrument will be analyzed using machine learning methods to identify volatile organic compound (VOC) patterns associated with different cancer types, including pancreatic, esophageal, hepatocellular carcinoma, lung, and ovarian cancers. The trained machine learning model will be tested using the dataset.
Time frame: 1 Years
Assess The Specificity and Accuracy of ML Analysis In The Test Dataset.
To determine the specificity, and overall diagnostic accuracy of the machine learning (ML) algorithm for detecting pancreatic, esophageal, hepatocellular carcinoma, lung, and ovarian cancers within the test dataset.
Time frame: 1 year
Plan to share: No
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This study is not yet recruiting, as verified in Jul 2026. You cannot join it, but the record below documents what was studied.
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University of Oklahoma