- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03967652
Cancer Diagnoses From Exhaled Breath With Na-nose
May 29, 2019 updated by: Hu Liu, Anhui Medical University
Diagnosing Cancers From Healthy From Human Exhaled Breath With Na-nose
Early diagnoses of malignant tumors are pivotal for improving their prognoses.
The Exhaled Breath is made up of oxygen, carbon dioxide, nitrogen, water, inert gases and volatile organic compounds (VOCs).
Theoretically, the concentration of VOCs in exhalation produced by metabolism in human body is only about nmol/L-pmol/L, which can significantly increase under certain pathological conditions.
A series of studies of VOCs diagnosing solid tumors the investigators had been conducted in the past decade.
It was found that VOCs in exhaled breath can not only distinguish different types of tumors, but also can make a clear distinction between different stages.
Our long-term collaborator, Professor Hossam Haick (Israel Institute of Technology) has developed a nano sensor array, so called Na-nose, which can detect VOCs of the exhaled breath by binding gases to specific chemiresistors coated with gold nanomaterials.
The Na-nose has the advantages of low cost, easy to use, good reproducibility and real-time detection for large scale clinical application.
This study was to use large clinical samples to validate the diagnostic efficacy of the newly developed Nano-nose( Sniffphone and Breath Screener) for malignant tumors .
Study Overview
Status
Not yet recruiting
Conditions
Intervention / Treatment
Detailed Description
Israel Institute of Technology provides two type of Na-nose.
One is Breath Screener used for large-scale sampling and feature VOCs extraction to establish database.
The other is called Sniff Phone aim at clinical real-time VOCs detection assisted by software.
About 10,000 patients will participate in the subject of Breath Screener in batches.
First, 7000 patients will have a definitive diagnosis and exhaled breath collected.
Feature VOCs of specific tumors will be extracted from these samples and employed to build predictive model by using discriminant factor analysis (DFA).
After the predictive model had been completed, 3000 definitively diagnosed patients will participate in validating the specificity and sensitivity of the prediction model.
With the assistance of Breath Screener clinical database and software services, Sniff Phone is more suitable for clinical real-time detection for its small and convenient design characteristics.
At last, Breath Screener and Sniff Phone will continue enriching databases and improve diagnosis efficacy in their clinical applications.
Study Type
Observational
Enrollment (Anticipated)
10000
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Bao Chuyang, MD
- Phone Number: +86 18555039598
- Email: des_mond@outlook.com
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
18 years to 75 years (Adult, Older Adult)
Accepts Healthy Volunteers
No
Genders Eligible for Study
All
Sampling Method
Non-Probability Sample
Study Population
10,000 volunteers who had a definitively diagnosis with surgery or endoscope
Description
Inclusion Criteria:
- 18-75 years
- Cancer/benign disease having been diagnosed by pathology
- ECOG < 2
Exclusion Criteria:
- Concomitant malignancies other than one malignant tumor
- Diabetes, Fatty liver
- Autoimmune disease
- Ventilation and transaired function obstacle
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Observational Models: Other
- Time Perspectives: Prospective
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
cancer
Patients with definitively diagnosed of solid tumors
|
Chemical sensors based on Monolayer-Capped Metallic Nanoparticles (MCMNPs) can recognize and classify exhaled breath by special recognition algorithm, which achieves the purpose of disease diagnosis.
|
Benign disease
Patients with definitively diagnosed of benign disease or precancerous lesion
|
Chemical sensors based on Monolayer-Capped Metallic Nanoparticles (MCMNPs) can recognize and classify exhaled breath by special recognition algorithm, which achieves the purpose of disease diagnosis.
|
Normal
Healthy volunteers
|
Chemical sensors based on Monolayer-Capped Metallic Nanoparticles (MCMNPs) can recognize and classify exhaled breath by special recognition algorithm, which achieves the purpose of disease diagnosis.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Build predictive diagnosis database
Time Frame: From July 01,2019 to December 31,2021
|
First, feature VOCs of specific tumors will be extracted from part of collected samples and employed to build predictive model.
After the predictive model had been completed, number of definitively diagnosed patients will participate in validating the specificity and sensitivity of the prediction model.
|
From July 01,2019 to December 31,2021
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Associated feature exhaled breath with differentially expressed genes
Time Frame: From Juan 01,2022 to December 31,2022
|
Integrate the correlation and relevance between the exhaled samples and the differentially expressed genes in the cancer group and the benign / normal control group to explore the mechanism of feature VOCs' production.
|
From Juan 01,2022 to December 31,2022
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Collaborators
Investigators
- Principal Investigator: Hu Liu, MD, Anhui Provincial Hospital
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Nakhleh MK, Amal H, Jeries R, Broza YY, Aboud M, Gharra A, Ivgi H, Khatib S, Badarneh S, Har-Shai L, Glass-Marmor L, Lejbkowicz I, Miller A, Badarny S, Winer R, Finberg J, Cohen-Kaminsky S, Perros F, Montani D, Girerd B, Garcia G, Simonneau G, Nakhoul F, Baram S, Salim R, Hakim M, Gruber M, Ronen O, Marshak T, Doweck I, Nativ O, Bahouth Z, Shi DY, Zhang W, Hua QL, Pan YY, Tao L, Liu H, Karban A, Koifman E, Rainis T, Skapars R, Sivins A, Ancans G, Liepniece-Karele I, Kikuste I, Lasina I, Tolmanis I, Johnson D, Millstone SZ, Fulton J, Wells JW, Wilf LH, Humbert M, Leja M, Peled N, Haick H. Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules. ACS Nano. 2017 Jan 24;11(1):112-125. doi: 10.1021/acsnano.6b04930. Epub 2016 Dec 21.
- Barash O, Zhang W, Halpern JM, Hua QL, Pan YY, Kayal H, Khoury K, Liu H, Davies MP, Haick H. Differentiation between genetic mutations of breast cancer by breath volatolomics. Oncotarget. 2015 Dec 29;6(42):44864-76. doi: 10.18632/oncotarget.6269.
- Amal H, Shi DY, Ionescu R, Zhang W, Hua QL, Pan YY, Tao L, Liu H, Haick H. Assessment of ovarian cancer conditions from exhaled breath. Int J Cancer. 2015 Mar 15;136(6):E614-22. doi: 10.1002/ijc.29166. Epub 2014 Sep 5.
- Amal H, Leja M, Broza YY, Tisch U, Funka K, Liepniece-Karele I, Skapars R, Xu ZQ, Liu H, Haick H. Geographical variation in the exhaled volatile organic compounds. J Breath Res. 2013 Dec;7(4):047102. doi: 10.1088/1752-7155/7/4/047102. Epub 2013 Nov 1.
- Leja MA, Liu H, Haick H. Breath testing: the future for digestive cancer detection. Expert Rev Gastroenterol Hepatol. 2013 Jul;7(5):389-91. doi: 10.1586/17474124.2013.811033. No abstract available.
- Amal H, Ding L, Liu BB, Tisch U, Xu ZQ, Shi DY, Zhao Y, Chen J, Sun RX, Liu H, Ye SL, Tang ZY, Haick H. The scent fingerprint of hepatocarcinoma: in-vitro metastasis prediction with volatile organic compounds (VOCs). Int J Nanomedicine. 2012;7:4135-46. doi: 10.2147/IJN.S32680. Epub 2012 Jul 30.
- Xu ZQ, Broza YY, Ionsecu R, Tisch U, Ding L, Liu H, Song Q, Pan YY, Xiong FX, Gu KS, Sun GP, Chen ZD, Leja M, Haick H. A nanomaterial-based breath test for distinguishing gastric cancer from benign gastric conditions. Br J Cancer. 2013 Mar 5;108(4):941-50. doi: 10.1038/bjc.2013.44.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Anticipated)
July 1, 2019
Primary Completion (Anticipated)
December 31, 2020
Study Completion (Anticipated)
December 31, 2022
Study Registration Dates
First Submitted
May 27, 2019
First Submitted That Met QC Criteria
May 27, 2019
First Posted (Actual)
May 30, 2019
Study Record Updates
Last Update Posted (Actual)
May 31, 2019
Last Update Submitted That Met QC Criteria
May 29, 2019
Last Verified
May 1, 2019
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- NanoBreathDiag
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
No
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
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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