Improving diagnosis of cardiovascular, cancer, and neurological diseases using machine learning

This is a Human Analytics Longitudinal Observational (HALO) Study. A Phase I Study to Analyze All Available Biomarkers and Determinants of Health to Increase Diagnostic Accuracy While Reducing the Time to Diagnosis of Disease.

This study is testing if using machine learning can help doctors diagnose heart problems, cancer, and brain injuries faster and more accurately in patients who haven't started treatment yet.

Quick facts

• Study type: Observational
• Enrollment: 2000 (estimated)
• Ages: 45 Years to 90 Years
• Sex: Male
• Sponsor: HALO Diagnostics (industry)
• Locations: 1 site (Indian Wells, California)
• Trial ID: NCT05423860 on ClinicalTrials.gov

What this trial studies

This observational study aims to discover, optimize, standardize, and validate clinical measures and biomarkers for diagnosing cardiovascular diseases, cancer, dementia, and traumatic brain injury. By utilizing electronic medical records and advanced data analysis techniques, the study seeks to enhance diagnostic accuracy and reduce the time to diagnosis through machine learning algorithms. Additionally, it will develop multivariate biomarker risk scores to predict the future development of these diseases and direct participants to relevant clinical trials. The focus is on treatment-naïve patients with specific conditions, particularly prostate adenocarcinoma.

Who should consider this trial

Good fit: Ideal candidates include treatment-naïve males aged 45 and older diagnosed with prostate adenocarcinoma at specific clinical stages.

Not a fit: Patients with conditions incompatible with MRI or severe lower urinary tract issues may not benefit from this study.

Why it matters

Potential benefit: If successful, this study could lead to earlier and more accurate diagnoses of serious diseases, improving patient outcomes.

How similar studies have performed: Other studies utilizing machine learning for diagnostic purposes have shown promise, indicating potential success for this approach.

Eligibility criteria

Inclusion Criteria:

Treatment Naïve patients:

* Male, 45 years of age or older.
* Diagnosis of prostate adenocarcinoma.
* Clinical stage T1c or T2a.
* Gleason score of 7 (3+4 or 4+3) or less.
* Three or fewer biopsy cores with prostate cancer.
* PSA density not exceeding 0.375.
* One, two, or three tumor suspicious regions identified on multiparametric MRI.
* Negative radiographic indication of extra-capsular extent.
* Karnofsky performance status of at least 70.
* Estimated survival of 5 years or greater, as determined by treating physician.
* Tolerance for anesthesia/sedation.
* Ability to give informed consent.
* At least 6 weeks since any previous prostate biopsy.
* MR-guided biopsy confirmation of one or more MRI-visible prostate lesion(s) with Gleason score of 7 (3+4 or 4+3) or less.

Salvage candidates will be accepted upon physician referral.

Exclusion Criteria:

* Presence of any condition (e.g., metal implant, shrapnel) not compatible with MRI.
* Severe lower urinary tract symptoms as measured by an International Prostate Symptom Score (IPSS) of 20 or greater
* History of other primary non-skin malignancy within previous three years.
* Diabetes
* Smoker

Where this trial is running

Indian Wells, California

• Desert Medical Imaging — Indian Wells, California, United States (RECRUITING)

Study contacts

• Principal investigator: Christopher R. Hancock, MD — HALO Diagnostics
• Study coordinator: Christopher R Hancock, MD,MBA

Conditions: Cardiovascular Diseases, Cancer, Dementia, Traumatic Brain Injury, brain, breast, prostate, cardiac