a PROspective Case Control Study to Develop and Validate a Blood Test FOr mUlti-caNcers Early Detection（PROFOUND）

Cancer Clinical Trial

— PROFOUND  

Official title:

PROFOUND Study: Development and Validation of a Multi-cancer Early Detection Model Based on Peripheral Blood Multi-omic Analysis and Machine Learning: a Multicenter, Prospective, Observational, Case-control Study

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06217900
• Other study ID #: PROFOUND
• Status: Recruiting
• Start date: December 28, 2023
• Est. completion date: March 31, 2027

Study information

• Verified date: December 2023
• Source: Shanghai Weihe Medical Laboratory Co., Ltd.
• Contact: Yong Qin
• Phone: +86 186 2629 2273
• Email: qinyong[@]bytedance.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

This study is a multi-center, case-control study aiming at developing and blinded testing machine learning-based multiple cancers early detection model by prospectively collecting blood samples from newly diagnosed cancer patients and individuals without confirmed cancer diagnosis.

Description:

Blood samples from newly diagnosed cancer patients and individuals without confirmed cancer diagnosis will be prospectively collected to identify cancer-specific circulating signals through integrative multi-omic analysis. Based on the comprehensive molecular profiling, a machine learning-driven model will be trained and blinded validated independent through a two-stage approach in clinically annotated individuals. Approximately 10327 cancer patients will be enrolled in this study and early-stage cancer patients will be enriched to improve the model sensitivity on distinguishing cancers with favorable prognosis. Approximately 6339 age and sex matched controls will be included in model development, which are volunteers without a cancer diagnosis after routine cancer screening tests.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 16666
• Est. completion date: March 31, 2027
• Est. primary completion date: October 31, 2026
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 40 Years to 74 Years

Eligibility

Inclusion Criteria for Case Arm Participants:

• 40-74 years old

• Clinically and/or pathologically diagnosed cancer

• No prior or undergoing any systemic or local antitumor therapy, including but not limited to surgical resection, radiochemotherapy, endocrinotherapy, targeted therapy, immunotherapy, interventional therapy, etc.

• Able to provide a written informed consent and willing to comply with all part of the protocol procedures

Exclusion Criteria for Case Arm Participants:

• Pregnancy or lactating women

• Known prior or current diagnosis of other types of malignancies comorbidities

• Severe acute infection (e.g. severe or critical COVID-19, sepsis, etc.) or febrile illness (body temperature of = 38.5 °C) within 14 days prior to screen

• Recipients of organ transplant or prior bone marrow transplant or stem cell transplant

• Recipients of blood transfusion within 30 days prior to screen

• Recipients of therapy in past 14 days prior to screen, including oral or IV antibiotics, glucocorticoid, azacitidine, decitabine, procainamide, hydrazine, arsenic trioxide

• Unsuitable for this trial determined by the researchers

Inclusion Criteria for Control Arm Participants:

• 40-74 years old

• Without confirmed cancer diagnosis

• Able to provide a written informed consent and willing to comply with all part of the protocol procedures

Exclusion Criteria for Control Arm Participants:

• Pregnancy or lactating women

• Known prior or current diagnosis of other types of malignancies comorbidities

• Severe acute infection (e.g. severe or critical COVID-19, sepsis, etc.) or febrile illness (body temperature of = 38.5 °C) within 14 days prior to screen

• Recipients of organ transplant or prior bone marrow transplant or stem cell transplant

• Recipients of blood transfusion within 30 days prior to screen

• Recipients of therapy in the past 14 days prior to screen, including oral or IV antibiotics, glucocorticoid, azacitidine, decitabine, procainamide, hydrazine, arsenic trioxide

• Unsuitable for this trial determined by the researchers

Related Conditions & MeSH terms

• Cancer

Locations

Country	Name	City	State
China	Peking University Cancer Hospital and Institute	Beijing	Beijing
China	Peking University People's Hospital	Beijing	Beijing

Sponsors (2)

Lead Sponsor	Collaborator
Shanghai Weihe Medical Laboratory Co., Ltd.	Peking University People's Hospital

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	To develop a questionnaire to evaluate the risk factors in the multi-cancer early screening	To develop a questionnaire to evaluate the high-risk factors in the multi-cancer early screening, including lung cancer, gastrointestinal cancer, gynecological cancer, urogenital neoplasms, etc.	12 months
Other	To evaluate the performance of multi-omics early detection models in the population with suspected cancer	The sensitivity, specificity and tissue origin accuracy of multi-omic-based multiple cancers early detection model in in the population with suspected cancer at 95% confidence interval.	12 months
Other	To simulate the positive predictive value and negative predictive value of different multi-cancer early detection models based on the cancer prevalence and staging data of individuals aged 40-75 years in China using multiple models	To simulate the positive predictive value and negative predictive value of different multi-cancer early detection models(cfDNA methylation-based or multi-omic-based),based on the sensitivity, specificity and tissue origin accuracy,according to multi cancer prevalence and staging data of individuals aged 40-75 years in China.	12 months
Other	To simulate the benefits of clinical utility and health economics using different multi-cancer early detection models	To simulate the stage-shift and incremental cost-effective ratio (ICER) benefit when compared to usual care (SOC screening) using Markov model based on MCED test performance	12 months
Other	To explore biomarkers for cancer screening and construct a multimodal machine learning model based on multi-omics data	Exploring biomarkers in methylomics and fragmentomics,and constructing multimodal for multi-cancer early detection based on multiomics analysis	12 months
Primary	The performance of cfDNA methylation-based multiple cancers early detection model in case-control study	The sensitivity, specificity and tissue origin accuracy of cfDNA methylation-based multiple cancers early detection model in detecting cancer or non-cancer at 95% confidence interval.	12 months
Secondary	The performance of cfDNA methylation-based multiple cancers early detection model in early stage cancer cases	The sensitivity and tissue origin accuracy of cfDNA methylation-based multiple cancers early detection model in detecting stage I to II cancer at 95% confidence interval.	12 months
Secondary	The performance of multi-omic-based multiple cancers early detection model in case-control study	The sensitivity, specificity and tissue origin accuracy of multi-omic-based multiple cancers early detection model in detecting cancer or non-cancer at 95% confidence interval.	12 months
Secondary	The performance of different multi-cancer early detection models in different subgroups	The sensitivity and specificity of cfDNA methylation-based or multi-omic-based multiple cancers early detection model in different subgroups of the population (such as age, gender, cancer pathological classification, and clinical stage) at 95% confidence interval.	12 months