- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06270992
Oral Microbiome Diagnostics of Lung Cancer
Developing an Artificial Intelligence-based Diagnostic Method Based on Oral Microbiome for Non-invasive Diagnosis of Lung Cancer
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Cancer is a global health issue that is on an increasing trend in terms of incidence and mortality rates, hindering the increase in life expectancy. According to the World Health Organization, lung, colorectal, and liver cancers are among the most common causes of cancer-related deaths. In Turkey, the incidence and mortality rates of lung cancer are higher than the world average. are among the risk factors that may increase the risk of lung cancer. In addition to risk factors like family history, smoking, different studies have shown that dysbiotic oral microbiome may contribute to the risk of lung cancer.
The oral microbiome is the second most diverse microenvironment in our body and has been associated with many diseases, including lung cancer. Studies to date on lung cancer-oral microbiome have generally involved designs aimed at resolving cause-and-effect relationships through statistical differences and/or mechanisms involving microbiome units.
However, there is no literature on any study aimed at developing a deep learning-based diagnostic method that focuses on the oral microbiome.Therefore, the proposed study aims to develop a microbiome based deep learning diagnostic method for lung cancer diagnosis. To this end, an observation cohort will be established consisting of 192 lung cancer patients, 192 non-cancerous benign lung disease patients, and 192 healthy controls. Tongue swab samples belonging to the cohort will be collected, and 16S rRNA sequencing will be performed. At the same time, an international observation cohort of approximately 1700 individuals will be created using in silico data. All data will be analyzed integratively, and an artificial intelligence diagnostic algorithm that can differentiate lung cancer patients from other lung diseases and healthy individuals will be developed using deep learning methods. In the final stage, the performance of the diagnostic method developed for a pilot clinical trial cohort of 96 individuals will be tested using a PRoBE (prospective specimen collection before outcome ascertainment and retrospective blinded evaluation) design.
The original aspects of the project are the proposal of a novel design in the literature, the creation of an experimental design/clinical trial and the presentation of a potential solution proposal that may have a high impact on an important diagnostic problem.
If the project is successfully completed, an artificial intelligence-based method that can potentially diagnose lung cancer through non-invasive oral microbiome samples will be developed. In addition to its patentability, if the method is further developed (in the medium to long term) into a product, it will enable lung cancer screening to be easily performed even in primary healthcare institutions with a simple oral swab sample.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Aycan Gundogdu, PhD
- Phone Number: +90 352 207 6666
- Email: agundogdu@erciyes.edu.tr
Study Locations
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Kayseri, Turkey, 38039
- Recruiting
- Erciyes University Hospital
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Contact:
- Aycan Gundogdu, PhD
- Phone Number: +90 352 207 6666
- Email: agundogdu@erciyes.edu.tr
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- To be between the ages of 18 and 65,
- Not to have a diagnosed lung disease or suspicion thereof,
- Not to have complaints related to the lungs and/or respiratory tract,
- Not to have alcohol or severe substance dependency,
- Not having a hospitalization history in the last year,
- Not having used antibiotics in the last six months,
- Not having used products manufactured to support the oral microbiome, such as probiotics (lozenges, sublingual drops) for at least the last six months,
- Not being pregnant or breastfeeding,
- Not having undergone dental procedures such as root canal treatment, implants, prostheses, tooth extraction, fillings in the last 6 months
- Not having dominant immune-origin lesions (such as aphthous ulcers, erythema multiforme, pemphigus), viral-origin lesions (such as herpes, Koplik spots, herpangina), dominant bacterial infections like tonsillitis, and/or thermal or chemical mucosal traumas in the mouth.
Exclusion Criteria:
- Not to satisfy inclusion or declining to participate even though all the inclusion criteria are satisfied.
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
Lung cancer group
192 patients diagnosed with lung cancer with the following inclusion criteria:
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For diagnostic evaluation, the necessary procedures from the standard protocols consisting of anamnesis, physical examination, laboratory tests, radiological imaging methods, and tissue biopsy will be followed.
Computerized Tomography (CT) and Positron Emission Tomography-Computed Tomography (PET-CT) will be used as imaging methods, while fiberoptic bronchoscopy and video-assisted mediastinoscopy will be applied for tissue diagnosis and staging.
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Benign lung disease group
192 patients diagnosed with non-cancer diseases with the following inclusion criteria:
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For diagnostic evaluation, the necessary procedures from the standard protocols consisting of anamnesis, physical examination, laboratory tests, radiological imaging methods, and tissue biopsy will be followed.
Computerized Tomography (CT) and Positron Emission Tomography-Computed Tomography (PET-CT) will be used as imaging methods, while fiberoptic bronchoscopy and video-assisted mediastinoscopy will be applied for tissue diagnosis and staging.
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Healthy control group
292 individuals without lung cancer or another lung disease diagnosis with the following inclusion criteria:
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Diagnostics accuracy assessment
Time Frame: 30 months
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Diagnostic technology under investigation will be evaluated using sensitivity, specificity, area under receiver operating curve.
Cross validation will be used for testing and NCCN diagnosis and patient follow-ups will be considered as the ground truth.
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30 months
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Collaborators and Investigators
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Estimated)
Study Record Updates
Last Update Posted (Estimated)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 123R030
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Sharing Supporting Information Type
- CSR
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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