RecruitingObservational

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.

NCT ID: NCT05423860Sponsor: HALO DiagnosticsLast updated: 2022-10-14

Summary

Discover, optimize, standardize, and validate clinical-trial measures and biomarkers used to diagnose and differentiate cardiovascular, oncologic, neurologic, and other diseases and disorders. Specifically, our research study endeavors to improve disease and disorder diagnosis to the earliest clinical states, in preclinical states, and to develop ensemble multivariate biomarker risk scores leading to cardiovascular, oncologic, neurologic, and other diseases and disorders. Additionally, the study aims to: * Evaluate data analysis techniques to improve diagnostic accuracy and reduce time to diagnosis. * Evaluate data analysis techniques to improve risk stratification for participants through machine learning algorithms. * Direct participants to relevant and applicable clinical trials.

Detailed description

Electronic medical records contain data that may indicate increased risk for certain diseases and disorders, but clinicians cannot easily discern the subtle patterns required to change their diagnostic and treatment patterns. This study seeks to use machine learning and data analysis techniques to increase diagnostic confidence and reduce time-to-diagnosis related to cardiovascular, oncologic, neurologic, and other diseases and disorders. The study endeavors to develop ensemble multivariate biomarker risk scores to predict future development of diseases and disorders, improve diagnosis in preclinical states and increase diagnostic accuracy in the earliest clinical states. We also aim to evaluate data analysis techniques to improve diagnostic accuracy and reduce time to diagnosis, improve risk stratification for participants through machine learning algorithms and direct participants to relevant and applicable clinical trials upon physician review, approval and recommendation.

Arms & interventions

Otherno interventions will be performed (observational)
Not applicable. (no interventions will be performed with this observational study

Outcome measures

Primary

Prostate cancer Gleason score
Measure a patient's prostate cancer Gleason score for patients with a prostate cancer diagnosis and record the measurement again at 3, 6, 9 months and annually for 5 years after treatment. We will use the pathology report submitted by the pathologist. The Gleason Score ranges from 1-5 and describes how much the cancer from a biopsy looks like healthy tissue (lower score) or abnormal tissue (higher score).
Time frame: Up to 5 years after treatment
Prostate cancer ISUP grade group
Measure a patient's prostate cancer ISUP grade group for patients with a prostate cancer diagnosis and record the measurement again at 3, 6, 9 months and annually for 5 years after treatment. We will use the pathology report submitted by the pathologist. The International Society of Urological Pathology (ISUP) guidelines grades the cancer between 1 and 5 depending on the Gleason score. The lower the grade the less likely the cancer is to spread.
Time frame: Up to 5 years after treatment
Prostate cancer staging parameters
TNM stage and metastasis-free survival, documentation of tumor, lymph node and osseous involvement
Time frame: Up to 5 years after treatment
Prostate cancer specific mortality
Proportion of men who expire directly due to prostate cancer
Time frame: Up to 5 years

Secondary

Lower urinary tract symptoms (LUTS)
Time frame: Up to 5 years after treatment
Erectile function
Time frame: Up to 5 years after treatment
Emotional well-being
Time frame: Up to 5 years after treatment
Incontinence level
Time frame: Up to 5 years after treatment
PI-RADS category
Time frame: Up to 5 years after treatment

Eligibility criteria

Sex: MaleAge: 45 Years to 90 YearsHealthy volunteers: No

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

Study locations (1)

Desert Medical Imaging

Indian Wells, California, 92210

Recruiting

Bernadette M. Greenwood, MSc · Contact

760-766-2047

ERIK PETERSON, BS · Contact

4147455773 ERIK.PETERSON@HALODX.COM

Chris R Hancock, MD · Principal Investigator

Bernadette M. Greenwood, BSc · Sub Investigator

Erik W Peterson, BS · Sub Investigator

References

Weng SF, Reps J, Kai J, Garibaldi JM, Qureshi N. Can machine-learning improve cardiovascular risk prediction using routine clinical data? PLoS One. 2017 Apr 4;12(4):e0174944. doi: 10.1371/journal.pone.0174944. eCollection 2017.(PubMed)
Wang X, Oldani MJ, Zhao X, Huang X, Qian D. A review of cancer risk prediction models with genetic variants. Cancer Inform. 2014 Sep 21;13(Suppl 2):19-28. doi: 10.4137/CIN.S13788. eCollection 2014.(PubMed)