Clinical trial NCT06217900: a PROspective Case Control Study to Develop and Validate a Blood Test FOr mUlti-caNcers Early Detection（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
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Cancer
Keywords: cell-free DNA
methylation
cancer early detection
Lead sponsor: Shanghai Weihe Medical Laboratory Co., Ltd.
Sponsor class: INDUSTRY
Collaborators: name: Peking University People's Hospital
First posted: 2024-01-23
Enrollment: 16666
Sex: ALL
Minimum age (years): 40
Maximum age (years): 74
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Confirmed cancers or individuals without confirmed cancer will be invited to participate in this case-control study by a designated consenting professional.

Brief 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.

Detailed 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.

Eligibility criteria: 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

Primary outcomes:
measure: The performance of cfDNA methylation-based multiple cancers early detection model in case-control study
timeFrame: 12 months
Secondary outcomes:
measure: The performance of cfDNA methylation-based multiple cancers early detection model in early stage cancer cases
timeFrame: 12 months
measure: The performance of multi-omic-based multiple cancers early detection model in case-control study
timeFrame: 12 months
measure: The performance of different multi-cancer early detection models in different subgroups
timeFrame: 12 months
Other outcomes:
measure: To develop a questionnaire to evaluate the risk factors in the multi-cancer early screening
timeFrame: 12 months
measure: To evaluate the performance of multi-omics early detection models in the population with suspected cancer
timeFrame: 12 months
measure: 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
timeFrame: 12 months
measure: To simulate the benefits of clinical utility and health economics using different multi-cancer early detection models
timeFrame: 12 months
measure: To explore biomarkers for cancer screening and construct a multimodal machine learning model based on multi-omics data
timeFrame: 12 months
Locations:
city: Beijing
country: China
facility: Peking University People's Hospital
state: Beijing
city: Beijing
country: China
facility: Peking University Cancer Hospital and Institute
state: Beijing
Study officials:
affiliation: Peking University People's Hospital
name: Jun Wang
role: PRINCIPAL_INVESTIGATOR
affiliation: Shanghai Weihe Medical Laboratory Co., Ltd.
name: Xiaohui Wu
role: STUDY_DIRECTOR
References: