Back to search results

Early Detection for Men at High Genetic Risk for Prostate Cancer

This study is looking at ways to improve early detection of prostate cancer in men who have a higher genetic risk. Researchers will be evaluating urinary biomarkers (substances in urine that can indicate disease) and PSA (prostate-specific antigen, a blood test for prostate health). The goal is to find the best approach for early detection in men aged 35 to 70 who have specific genetic mutations like BRCA1, BRCA2, Lynch syndrome, or p53, or other suspected prostate cancer-related genes. The study aims to identify predictors of any high-grade prostate cancer over a 5-year follow-up period. The current recruitment status is unclear, and they plan to enroll 200 participants.

Study design
This is an observational study, meaning researchers will observe participants without providing specific interventions. It plans to enroll 200 male participants.
What's involved
Not specified in the trial record.
Compensation
Not stated in the trial record.
Follow-up
Participants will be followed for 5 years to assess predictors of high-grade prostate cancer.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT07645391

Targeted Early Detection Program in Men at High Genetic Risk for Prostate Cancer

Recruiting
Not specifiedAges 35–70Observational
University of Michigan Rogel Cancer Center
~200 participants
Updated 2026-06-12 on ClinicalTrials.gov
What's tested:Non-Interventional Study

At a glance

Recruiting sites
1 of 1 listed site is recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Predictors of any HG PCa
Measured over At 5-years follow up

Conditions

Prostate Carcinoma

Explore related trials

Prostate CarcinomaABRAXAS1 wt AlleleATR GeneBRCA1 GeneBRCA2 GeneBRIP1 GeneDNA Mismatch Repair Protein Mlh1Double-Strand Break Repair Protein MRE11EPCAM GeneGEN1 GeneHOXB13 GeneMSH2 GeneMSH6 GeneNibrinPartner and Localizer of BRCA2PMS2 GeneRAD51C GeneRAD51D GeneSerine/Threonine-Protein Kinase Chk2TP53 Gene

NCT07645391

Where you'd take part

This study runs at 1 site. They're the same protocol — you choose where, and that choice sets who your contact draft is addressed to.

  • University of Michigan Rogel Cancer Center

    Ann Arbor, Michiganstudy coordinator listed

    Recruiting

Sites open and close at different times, so the status above is per site — it can differ from the study's overall status.

Study leadership

  • Todd M Morgan, MD · PRINCIPAL_INVESTIGATOR · University of Michigan Rogel Cancer Center

Who to contact

Cancer AnswerLine
[email protected]
1-800-865-1125
Email the study team

Opens a ready-to-send draft in your own email app — review before sending.

Want this trial checked against your situation?

Add a private profile and we'll compare every criterion below against your situation — and tell you which ones are met, uncertain, or excluding.

Check eligibility for this trial ~2 min · HIPAA-protected · delete anytime
Eligibility criteria

Inclusion

\* Age 35-70 years
Capable of providing informed consent
Prognosis of \> 5 years if affected by another cancer
Patients need one to meet at least one of the following high genetic risk categories:
Known PCa-related mutations: BRCA 1 and 2, Lynch syndrome, or p53
Carrier of mutation in a suspected PCa-related gene: e.g., ATM, PALB2, CHEK2, RAD51D, ATR, NBN, GEN1, RAD51C, MRE11A, BRIP1, FAM175A, HOXB13
Obligate carriers of the above mutations (e.g. their sisters/daughters have known mutations)
Men with any family history of above mutation
Family history of breast, prostate, or ovarian cancer in at least 2 individuals, or in 1 individual diagnosed before age 50

Exclusion

\* Anuria
Prior diagnosis or treatment for PCa
Failure to provide informed consent
Life expectancy \< 5 years

What this trial measures

  • Predictors of any HG PCaAt 5-years follow up

    Descriptive statistics, parametric and non-parametric statistical tests will be used to summarize the clinical variables. Will estimate the prevalence and incidence. Will fit two statistical models with cross-validation to evaluate the performance characteristics (Brier score, area under curve, sensitivity, specificity, positive and negative predictive values) of SelectMDx in predicting i) HG PCa and ii) any PCa.