Lung Cancer Detection in Never Smokers Using Urine Volatile Organic Compound (VOCs)
ConditionLung Cancer
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorThomas Jefferson University
About this trial
The goal of this observational study is to learn whether a urine-based test that measures volatile organic compounds (VOCs) can help detect lung cancer in people who have never smoked. The study will include adults who have never smoked, both with and without lung cancer.
The main questions it aims to answer are:
Can a urine VOC biosensor distinguish between people who have lung cancer and those who do not? Could this urine-based biomarker serve as a non-invasive approach for the early detection of lung cancer in people who are not currently eligible for standard lung cancer screening?
Researchers will compare participants with lung cancer to participants without lung cancer to determine whether the urine VOC signature can identify differences between the two groups.
Participants will:
Provide a urine sample for VOC testing. Provide health and demographic information as required by the study. Be classified into groups based on whether they have been diagnosed with lung cancer.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Adults over 18 years of age. Participants must be legally competent to provide informed consent.
Presence of a new, solid lung nodule identified on diagnostic CT chest scan ≥6mm in maximum diameter (representing indeterminate or suspicious nodules that may be due to a benign lung etiology or suspicious for primary lung cancer). If multiple lung nodules are present, the dominant lung nodule ≥6mm will be considered the index nodule.
Neversmoking status, defined as <100 lifetime cigarettes.
Confirmed or pending clinical diagnosis of either benign or malignant lung lesions, based on radiological and/or histopathological evaluation performed as part of routine care.
Disqualifiers
Pregnant or breastfeeding women. Pregnancy may alter urinary metabolite composition, potentially affecting analytical accuracy.
Patients with end-stage renal disease, defined as estimated glomerular filtration rate (eGFR) <15mL/min/1.73m2 or the initiation of long-term dialysis or transplantation.
Previous diagnosis or treatment for any type of cancer. Prior malignancy or cancer therapy (surgery, chemotherapy, radiotherapy, biologic or immunotherapy) could influence urinary volatile compound profiles and confound results.
Active severe illness or other conditions that, in the opinion of the investigator, would interfere with participation or pose unnecessary risk.
Trial population
Eighty-seven patients at least 18 years of age without a smoking history (defined as fewer than 100 lifetime cigarettes), undergoing evaluation for an indeterminate pulmonary nodule ≥6mm on CT chest and planned for a lung biopsy or surgical resection at TJU CC and MHD, without previous diagnosis of or treatment for any type of cancer.
Trial design
Design model
Case-control
Time perspective
Prospective
Treatments tested in this trial
Biosensor Platform
Diagnostic testThe company developed a new system known as the "Biosensor Platform" (BSP). This platform integrates hardware, software, and database infrastructure designed by Early Labs. The outcomes are generated by a machine-learning algorithm powered by AI, which considers both the current and historical performance data of the biological sensors. Various controls are implemented to ensure the performance of the sensors is evaluated 100% of the time.
Treatment groups
87 Participants
are divided into 2 treatment groupsGroup A: Cohort 1: Lung Cancer Cases1 intervention
Group B: Cohort 2: Non-Cancer Controls1 intervention
Trial outcomes
Primary outcomes
1
Sensitivity of the Biosensor Platform (BSP) for Detection of Lung Cancer in the Jefferson Health Cohort
Percentage of participants with lung cancer who have positive Biosensor Platform (BSP) result. Sensitivity will be estimated using exact logistic regression and reported with 95% confidence interval.
Time frame
Up to 24 months2
Specificity of the Biosensor Platform (BSP) for Detection of Lung Cancer in the Jefferson Health Cohort
Percentage of participants without lung cancer who have a negative Biosensor Platform (BSP) result. Specificity will be estimated using exact logistic regression and reported with 95% confidence interval.
Time frame
Up to 24 monthsSecondary outcomes
1
Sensitivity of the Biosensor Platform (BSP) for Detection of Lung Cancer in the Combined Jefferson Health Cohort and EARLY Labs Cohort
Percentage of participants with lung cancer who have positive Biosensor Platform (BSP) result. Sensitivity will be estimated using exact logistic regression and reported with 95% confidence interval.
Time frame
Up to 24 months2
Specificity of the Biosensor Platform (BSP) for Detection of Lung Cancer in the Combined Jefferson Health Cohort and EARLY Labs Cohort
Percentage of participants without lung cancer who have a negative Biosensor Platform (BSP) result. Specificity will be estimated using exact logistic regression and reported with 95% confidence interval.
Time frame
Up to 24 monthsSponsors and contacts
Click on the lead sponsor to view all of their trials.
Thomas Jefferson University
Lead sponsor
EARLY Labs
Collaborator
Source ClinicalTrials.gov