Prostate Cancer MetastaticNCT07660276
AI-based Prediction of Prostate Cancer Metastasis Using Biopsy Pathology
An observational study of Prostate Cancer Metastatic, run by Xiangya Hospital of Central South University at 1 site in China.
Trial summary
This observational study aims to develop and validate an artificial intelligence-based model using prostate cancer biopsy pathology to predict lymph node metastasis and distant metastasis in patients with prostate cancer. Read more about this study
- Who is it for?
- Ages 18 to 90 years, men only
- Conditions the study is for
- Prostate Cancer Metastatic
- What is being tested?
- Artificial Intelligence-Based Pathology Analysis
- How many people
- 3,000 participants
- Where
- 1 siteChina
- Study dates
- 8 Jan 2026to 1 Aug 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 90 years
- Men only
- No healthy volunteers
- Adult, Older adult
Study population: The study population consists of patients with pathologically confirmed prostate cancer from multiple participating hospitals led by Xiangya Hospital. Eligible patients underwent prostate biopsy with available biopsy pathology specimens and relevant clinical and imaging data for assessment of lymph node and distant metastasis. Retrospective clinical and pathological data will be collected for development and validation of an artificial intelligence-based metastasis prediction model.
Who may be able to join
- Male patients aged between 18 and 90 years; Patients who underwent prostate biopsy due to elevated prostate-specific antigen (PSA), abnormal digital rectal examination (DRE), or abnormal imaging findings, were pathologically diagnosed with prostate cancer, and had available prostate biopsy pathology specimens; Patients who underwent radical prostatectomy with extended pelvic lymph node dissection (ePLND) or pelvic lymph node dissection (PLND), with definitive pathological information regarding lymph node metastasis; Patients who underwent PSMA PET/CT, MRI, bone scintigraphy, or prostate MRI capable of identifying regional lymph node metastasis or distant metastasis; Adequate cardiac, pulmonary, hepatic, and renal function; Eastern Cooperative Oncology Group (ECOG) performance status of 0-1; Expected survival time greater than 1 year; Written informed consent signed by the patient or legally authorized representative.
Who cannot join
- History of other malignancies; Severe dysfunction of major organs, including cardiac, pulmonary, hepatic, or renal insufficiency, or an expected survival time of less than 1 year; Prostate biopsy pathology specimens with inadequate whole-slide image scanning quality or failure of quality control assessment; Patients with prostate cancer diagnosed from transurethral resection specimens.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
About this study
Official title: Development and Validation of an AI-Based Metastasis Prediction Model Using Prostate Cancer Biopsy Pathology
This observational study aims to develop and validate an artificial intelligence-based model using prostate cancer biopsy pathology to predict lymph node metastasis and distant metastasis in patients with prostate cancer. The main questions it aims to answer are:
Can artificial intelligence-assisted analysis of prostate cancer biopsy pathology accurately predict lymph node metastasis? Can the model accurately predict distant metastasis and assess metastatic risk in patients with prostate cancer?
Read more
Researchers aim to evaluate whether the model can provide additional information for clinical decision-making and surgical planning.
Participants will:
Provide prostate biopsy pathology specimens and related clinical information; Undergo assessment of lymph node and distant metastatic status based on clinical and imaging data; Be included in the development and validation of the artificial intelligence prediction model.
- Conditions
- Prostate Cancer Metastatic
- Being tested
- Artificial Intelligence-Based Pathology Analysis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence-Based Pathology AnalysisOther
Artificial intelligence-assisted analysis of prostate cancer biopsy pathology specimens for prediction of lymph node and distant metastasis risk.
| Study group | Role | What they receive |
|---|---|---|
| Prostate Cancer Cohort | Patients with prostate cancer undergoing biopsy pathology assessment for development and validation of an AI-based metastasis prediction model. Receives: Other: Artificial Intelligence-Based Pathology Analysis |
What is being measured
The primary outcome is the main question the study is designed to answer.
Prediction of Regional Lymph Node Metastasis
Assessment of the ability of the artificial intelligence-based model using prostate cancer biopsy pathology to predict regional lymph node metastasis.
Measured: Baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Jun 2026
- Study start8 Jan 2026
- Primary completion1 Aug 2026 (estimated)
- Study completion1 Aug 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Prostate Cancer MetastaticStudies of the same condition, open and under way.
- More trials run by Xiangya Hospital of Central South UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Xiangya Hospital of Central South University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Yi Cai, Principal investigator, Xiangya Hospital Central South University Department of Urology
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07660276
- Sponsor's protocol ID
- 2026010083_4
- Status last verified
- May 2026
- First submitted
- 16 Jun 2026
- Last updated
- 22 Jun 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Except for essential information, no other information will be shared to protect patient privacy.
Study at a glance
From the registry record, last updated by the sponsor on 22 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development and Validation of an AI-Based Metastasis Prediction Model Using Prostate Cancer Biopsy Pathology
- ClinicalTrials.gov ID
- NCT07660276
- Acronym / sponsor ID
- 2026010083_4
- Conditions
- Prostate Cancer Metastatic
- Study type
- Observational
- Recruitment status
- Enrolling by invitation
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- Xiangya Hospital of Central South UniversityUniversity, hospital or other
- Study start
- 8 Jan 2026 (actual)
- Primary completion
- 1 Aug 2026 (estimated)
- Study completion
- 1 Aug 2026 (estimated)
- First posted
- 22 Jun 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This observational study aims to develop and validate an artificial intelligence-based model using prostate cancer biopsy pathology to predict lymph node metastasis and distant metastasis in patients with prostate cancer. The main questions it aims to answer are:
Can artificial intelligence-assisted analysis of prostate cancer biopsy pathology accurately predict lymph node metastasis? Can the model accurately predict distant metastasis and assess metastatic risk in patients with prostate cancer?
Researchers aim to evaluate whether the model can provide additional information for clinical decision-making and surgical planning.
Participants will:
Provide prostate biopsy pathology specimens and related clinical information; Undergo assessment of lymph node and distant metastatic status based on clinical and imaging data; Be included in the development and validation of the artificial intelligence prediction model.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Prostate Cancer Cohort | – | Other: Artificial Intelligence-Based Pathology AnalysisPatients with prostate cancer undergoing biopsy pathology assessment for development and validation of an AI-based metastasis prediction model. |
Who may qualify
- Ages
- 18 to 90 years
- Sex
- Male only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study population consists of patients with pathologically confirmed prostate cancer from multiple participating hospitals led by Xiangya Hospital. Eligible patients underwent prostate biopsy with available biopsy pathology specimens and relevant clinical and imaging data for assessment of lymph node and distant metastasis. Retrospective clinical and pathological data will be collected for development and validation of an artificial intelligence-based metastasis prediction model.
Key inclusion criteria (1 listed)
- Male patients aged between 18 and 90 years; Patients who underwent prostate biopsy due to elevated prostate-specific antigen (PSA), abnormal digital rectal examination (DRE), or abnormal imaging findings, were pathologically diagnosed with prostate cancer, and had available prostate biopsy pathology specimens; Patients who underwent radical prostatectomy with extended pelvic lymph node dissection (ePLND) or pelvic lymph node dissection (PLND), with definitive pathological information regarding lymph node metastasis; Patients who underwent PSMA PET/CT, MRI, bone scintigraphy, or prostate MRI capable of identifying regional lymph node metastasis or distant metastasis; Adequate cardiac, pulmonary, hepatic, and renal function; Eastern Cooperative Oncology Group (ECOG) performance status of 0-1; Expected survival time greater than 1 year; Written informed consent signed by the patient or legally authorized representative.
Key exclusion criteria (1 listed)
- History of other malignancies; Severe dysfunction of major organs, including cardiac, pulmonary, hepatic, or renal insufficiency, or an expected survival time of less than 1 year; Prostate biopsy pathology specimens with inadequate whole-slide image scanning quality or failure of quality control assessment; Patients with prostate cancer diagnosed from transurethral resection specimens.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence-Based Pathology AnalysisArtificial intelligence-assisted analysis of prostate cancer biopsy pathology specimens for prediction of lymph node and distant metastasis risk. | Other | Prostate Cancer Cohort |
Primary outcome
Prediction of Regional Lymph Node Metastasis
Time frame: Baseline
Assessment of the ability of the artificial intelligence-based model using prostate cancer biopsy pathology to predict regional lymph node metastasis.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Jun 2026.
- Individual participant dataSharing planned: No. Except for essential information, no other information will be shared to protect patient privacy.
Related trials for Prostate Cancer Metastatic
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RecruitingPhase 2
A Study to Test Inavolisib Treatment in Participants With Metastatic Castration-Resistant Prostate Cancer
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RecruitingPhase 1/2
Docetaxel and SX-682 in Recurrent/Metastatic Head and Neck Squamous Cell Carcinoma, Salivary Gland Carcinoma, and Advanced Prostate Cancer
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RecruitingObservational study
ARCTIC: Liquid Biomarkers in the Prospective Androgen Receptor Signaling Inhibitors (ARSI) Resistance Clinical Trials
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Active, not recruitingPhase 2
FPI-2265 (225Ac-PSMA-I&T) and Olaparib for Patients With Metastatic Castration-Resistant Prostate Cancer (mCRPC)
Metastatic Castration-resistant Prostate Cancer
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Yi Cai principal investigator
Xiangya Hospital Central South University Department of Urology
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Prostate Cancer Metastatic, run by Xiangya Hospital of Central South University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: enrolling by invitation, as of the sponsor's last update on 22 Jun 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Prediction of Regional Lymph Node Metastasis (time frame: Baseline). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 22 Jun 2026.