Identifying cancer risk using digital and molecular markers
Digital and Molecular Detection of Markers for Disease Risk Prediction, Improvement of Diagnostic Detection Accuracy and Implementation for Preventive Measures of Cancer - A Combined Case-control and Cohort Study
This study is trying to find new ways to predict the risk of developing different types of cancer, especially breast cancer, by looking at biological markers and lifestyle factors in both cancer patients and healthy people.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 1250 (estimated) |
| Ages | 18 Years and up |
| Sex | Female |
| Sponsor | University of Erlangen-Nürnberg Medical School Academic / other |
| Locations | 1 site (Please Refer to Project Homepage For Details (see Link Below), Bavaria) |
| Trial ID | NCT06962670 on ClinicalTrials.gov |
What this trial studies
This study aims to discover new markers that can predict the risk of developing various cancers, with a primary focus on breast cancer. Researchers will collect data from both cancer patients and healthy individuals to identify differences in biomarkers, lifestyle factors, and family history that may indicate an increased risk of cancer. Participants will use the BayPass mobile application to facilitate data collection and analysis. The study involves biomaterial collection to support the identification of these predictive markers.
Who should consider this trial
Good fit: Ideal candidates include adult women aged 18 and older with a current or past diagnosis of specific cancers such as breast, lung, colorectal, or gynecologic cancers.
Not a fit: Patients with known infections like HIV or active SARS-CoV2, or those with acute severe illnesses unrelated to the specified cancers, may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to improved methods for early cancer detection and risk assessment.
How similar studies have performed: Other studies have shown promise in using digital and molecular markers for cancer risk prediction, making this approach both relevant and potentially impactful.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Biological adult (at least 18 years old) women 2. Written informed consent for study participation and processing of personal data 3. Own smartphone that can run the BayPass mobile application and willingness to use said smartphone for study purposes Additional inclusion criterion for case group: 4. Pre-existing or current diagnosis of at least one of the following oncological diseases: breast cancer, lung cancer, colorectal cancer, gynecologic cancer (incl. ovarian cancer, endometrial cancer, cervical cancer, fallopian tube cancer, vaginal cancer and vulvar cancer) Exclusion Criteria: 1. Known infection with HIV (Human Immunodeficiency Virus), HepA (Hepatitis A), HepB (Hepatitis B), HepC (Hepatitis C) or active SARS-CoV2 (Severe acute respiratory syndrome coronavirus type 2) infection 2. Acute severe or potentially life-threatening illness, except those specified in inclusion criterion #4
Where this trial is running
Please Refer to Project Homepage For Details (see Link Below), Bavaria
- DigiOnko Präventionsmobil — Please Refer to Project Homepage For Details (see Link Below), Bavaria, Germany (Recruiting)
Study contacts
- Study coordinator: Peter A. Fasching, Prof. Dr. med.
- Email: fk-digionko@uk-erlangen.de
- Phone: +49 9131 85 33572
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.