Application of Quantum Detection-Driven Artificial Intelligence Algorithms for Single-Molecule cfDNA Characterization in the Early Diagnosis of Prostate Cancer
Trial Snapshot
- Phase
- Not Applicable
- Status
- Not yet recruiting
- Sponsor
- Shanghai Changzheng Hospital
- Enrollment
- 1,100
- Locations
- 7
- Primary Endpoint
- Area under the receiver operating characteristic curve (AUC-ROC) for the predictive model in the general population for prostate cancer.
Study Overview
Brief Summary
This research project aims to develop a novel blood testing method integrating cutting-edge quantum sensing and artificial intelligence technologies to achieve precise, non-invasive early diagnosis of prostate cancer. The research will employ quantum sensors to perform ultra-high-sensitivity measurements of circulating free DNA (cfDNA) in blood, thereby training a dedicated AI diagnostic model. The ultimate objective is to establish the diagnostic efficacy of this approach through clinical validation, providing clinicians with a novel diagnostic tool capable of significantly reducing unnecessary prostate biopsy procedures.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Prospective
Eligibility Criteria
- Ages
- 18 Years to 80 Years (Adult, Older Adult)
- Sex
- Male
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •Male, aged 18-80 years;
- •PSA > 4 ng/ml;
- •Patients meeting criteria for prostate biopsy:
- •fPSA/PSA < 0.16 or PSA D > 0.15 or PSA V > 0.75; ② Positive digital rectal examination (DRE); ③ Imaging studies (ultrasound/MRI) showing suspicious lesions.
Exclusion Criteria
- •Patients diagnosed with any malignant tumour within the past five years;
- •Patients who have undergone transurethral resection or enucleation of the prostate;
- •Patients who have previously received treatment for prostate cancer, including but not limited to endocrine therapy, targeted therapy, or immunotherapy;
- •Patients on long-term anticoagulant or antiplatelet therapy (anticoagulants discontinued for less than one week);
- •Patients who have received any form of tumour treatment prior to enrolment blood sampling, including surgery, radiotherapy/chemotherapy, endocrine therapy, targeted therapy, or immunotherapy;
- •Concurrent severe systemic diseases deemed by the investigator likely to interfere with trial treatment, evaluation, or compliance, including serious respiratory, circulatory, neurological, psychiatric, gastrointestinal, endocrine, immunological, or urological disorders;
- •Organ transplant recipients or individuals with prior non-autologous (allogeneic) bone marrow or stem cell transplantation;
- •Subjects who have undergone blood transfusion within one month prior to blood sampling;
- •Patients currently participating in other clinical trials, or who have participated in other clinical trials within the past year;
- •Patients deemed unsuitable for this clinical trial by the investigator;
- •Patients meeting any of the above criteria shall not be eligible for inclusion as subjects.
Outcomes
Primary Outcomes
Area under the receiver operating characteristic curve (AUC-ROC) for the predictive model in the general population for prostate cancer.
Time Frame: Through primary completion which may take 12 months.
Specificity of the predictive model in detecting prostate cancer within the general population.
Time Frame: Through primary completion which may take 12 months.
Sensitivity of the predictive model in detecting prostate cancer within the general population.
Time Frame: Through primary completion which may take 12 months.
Secondary Outcomes
- The specificity of the predictive model in identifying prostate cancer among individuals in the PSA grey zone.(Through primary completion which may take 12 months.)
- Area under the ROC curve for the predictive model in identifying prostate cancer within the PSA grey zone cohort.(Through primary completion which may take 12 months.)
- Sensitivity of the predictive model in identifying prostate cancer within the PSA grey zone cohort.(Through primary completion which may take 12 months.)
Investigators
Ren Shancheng
Professor, Chief of Urology
Shanghai Changzheng Hospital