The FuSion Program: A Prospective and Multicenter Cohort Study of Pan-Cancer Screening in Chinese Population

Cancer Clinical Trial

Official title:

A Prospective, Multicenter, Noninterventional Cohort Study of Muti-Omics Models for Pan-Cancer Screening

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05159544
• Other study ID #: FuSion
• Status: Recruiting
• Start date: July 6, 2021
• Est. completion date: December 7, 2024

Study information

• Verified date: April 2024
• Source: Singlera Genomics Inc.
• Contact: Wen Zou, Ph.D
• Phone: +8615152621812
• Email: zouwen[@]fdtzihs.org.cn
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The integrative study by Fudan and Singlera for cancer early detection(The FuSion Program ) will evaluate sensitivity,specificity and positive/negative predictive value of the screening model jointly developed by FuDan University and Singlera in a 2-year follow-up corhort including 10,000 persons in routine annual physicals from dozens of hospitals. The multi-omics model for pan-cancer screening will be developed in a 3-year follow-up corhort including 50,000 natural persons in community containing genetic information of tumor families, assessment of epidemiological risk factors, tumor markers, proteomics, genomics and DNA methylation. After optimizing, the ability of this model will be validated in the Taizhou corhort in reality.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 60000
• Est. completion date: December 7, 2024
• Est. primary completion date: July 6, 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 40 Years to 75 Years

Eligibility

Inclusion Criteria:

1. Take physical examinations in our research centers and have no cancer history;

2. "Population Health tracking Survey - simplified version of the questionnaire" must be filled according to the research program and an annual physical examination can be received as follow-up ;

3. Timely feed back the information related to tumor diagnosis in other hospitals to the investigator during the program;

4. Have no birth plan for the last 3 years;

5. Fully understand the study and voluntarily sign the informed consent.

Exclusion Criteria:

1. Have been diagnosed with esophageal cancer, gastric cancer, colorectal cancer, liver cancer, lung cancer, pancreatic cancer, breast cancer (including non-primary, such as recurrence, metastasis or other complications) and other malignant tumors;

2. Received blood transfusion, transplantation and other major operations within 3 months;

3. Participated in other interventional clinical researchs within 3 months;

4. Pregnant or lactating women;

5. Patients with autoimmune diseases, genetic diseases, mental diseases/disabilities and other diseases considered unsuitable for the study by the investigator;

6. Due to poor compliance, the researcher judged that the study could not be completed.

Related Conditions & MeSH terms

• Cancer

Locations

Country	Name	City	State
China	Beijing Hospital	Beijing	Beijing
China	Third Xiangya Hospital of Central South University	Changsha	Hunan
China	Xiangya Hospital of Central South University	Changsha	Hunan
China	Sichuan Provincial People's Hospital	Chengdu	Sichuan
China	West China Hospital of Sichuan University	Chengdu	Sichuan
China	The First Affiliated Hospital of Chongqing Medical University	Chongqing	Chongqing
China	Guangdong Provincial People's Hospital	Guangzhou	Guangdong
China	The First Affiliated Hospital of USTC (Anhui Provincial Hospital)	Hefei	Anhui
China	Jiangsu Province Hospital	Nanjing	Jiangsu
China	Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine	Shanghai	Shanghai
China	Fudan University Taizhou Institute of Health Sciences, Taizhou, China	Taihou	Jiangsu
China	Union Hospital affiliated to Tongji Hospital, Huazhong University of Science and Technology	Wuhan	Hubei

Sponsors (2)

Lead Sponsor	Collaborator
Singlera Genomics Inc.	Fudan University

Country where clinical trial is conducted

China, 

References & Publications (1)

Chen X, Gole J, Gore A, He Q, Lu M, Min J, Yuan Z, Yang X, Jiang Y, Zhang T, Suo C, Li X, Cheng L, Zhang Z, Niu H, Li Z, Xie Z, Shi H, Zhang X, Fan M, Wang X, Yang Y, Dang J, McConnell C, Zhang J, Wang J, Yu S, Ye W, Gao Y, Zhang K, Liu R, Jin L. Non-invasive early detection of cancer four years before conventional diagnosis using a blood test. Nat Commun. 2020 Jul 21;11(1):3475. doi: 10.1038/s41467-020-17316-z. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	To develop a multi-omics model for pan-cancer screening integrating the markers of ctDNA mutation, DNA fragmentation and methylation et al.	To construct a multi-dimensional ensembled stacked machine learning approach, employing several different base models on ctDNA mutation, DNA fragmentation and mehylation, to provide an effective model for cancer early detection.	assessed up to 36 months
Primary	To evaluate sensitivity,specificity,positive/negative predictive value of the screening model in participants taking routine annual physicals	Sensitivity: the ability of a test to correctly identify patients with a disease. Specificity: the ability of a test to correctly identify people without the disease. Positive predictive value refers to the probability of the person having the disease when the test is positive. Negative predictive value refers to the probability of the person not having the disease when the test is negative.	assessed up to 24 months
Primary	To validate model's efficacy and clinical value in the diagnosis of cancers in Taizhou cohort.	Cancer early detection could increase detection of cancer at early stages, when survival outcomes are better and treatment costs are lower. we will explore whether this model with high specificity could potentially improve long-term health outcomes and reduce cancer treatment costs.	assessed up to 12 months