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Liquid biopsy technology based on cell-free nucleic acids and protein characteristics has unique advantages and significant application prospects in cancer early detection. The purpose of this study is to collect peripheral blood samples from participants with new diagnosis of cancer and from participants who do not have a diagnosis of cancer in order to develop machine learning models for discovering cancer from non-cancer.
Full description
The PROFUTURE study: A prospective, multicenter, observational, case-control study with collection of peripheral blood and clinical data from clinical networks in order to develop machine learning models for discovering cancer from non-cancer. According to the statistical hypothesis based on expected detection performance, the study will enroll approximately 3,830 participants, including 2,138 participants with cancer (case arm) and approximately 1,692 representative participants without a clinical diagnosis of cancer after medical screening (control arm). Participants pre-matched by age and gender will be divided into training set and validation set in a ratio of approximately 7:3. The validation set will be blinded until the models are developed. Clinical information, demographics, and medical data relevant to cancer status are collected from all participants and their medical records at baseline. The participants of control arm will be asked to report suspected cancer diagnosis status within 6 months after blood collection.
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Inclusion and exclusion criteria
Inclusion Criteria for Cancer Arm Participants:
Exclusion Criteria for Cancer Arm Participants:
Inclusion Criteria for Non-Cancer Arm Participants:
Exclusion Criteria for Non-Cancer Arm Participants:
3,830 participants in 2 patient groups
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Central trial contact
Xiaosheng He, M.D.
Data sourced from clinicaltrials.gov
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