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Trial Title:
Value-based Integrated Recommendation Software Guiding Ovarian Cancer Treatment (VIRGO2)
NCT ID:
NCT05523700
Condition:
Ovarian Cancer
Conditions: Official terms:
Ovarian Neoplasms
Carcinoma, Ovarian Epithelial
Conditions: Keywords:
Mobile Application
Study type:
Interventional
Study phase:
N/A
Overall status:
Recruiting
Study design:
Allocation:
Randomized
Intervention model:
Parallel Assignment
Intervention model description:
This is a prospective multicenter, randomized control trial to assess the efficacy of an
AI-based recommendation program to improve healthcare outcomes in women with ovarian,
fallopian tube, or primary peritoneal cancer occurring in the outpatient setting.
Primary purpose:
Supportive Care
Masking:
None (Open Label)
Intervention:
Intervention type:
Other
Intervention name:
Mobile Application
Description:
Intervention is a mobile application than combines patient data via EMR with PROMIS
outcome measures.
Arm group label:
Interventional Arm
Summary:
This study will evaluate the use of a mobile application in improving the
patient-reported health outcome measures (PROMIS) for patients diagnosed with advanced
stage ovarian, fallopian tube, and primary peritoneal cancer. The application will
incorporate clinical data from the patient's medical chart as well as capture
patient-reported outcome measures on an ongoing basis to better inform physicians and the
care team so that necessary interventions may be implemented.
Detailed description:
The study will employ the complete utility of the mobile application by incorporating
highly coordinated ovarian cancer care pathways, associated evidence-based
recommendations, and delivering these 'at the fingertips' of providers and patients when
appropriate. The AI-based mobile application requires both clinical data-input as well as
continuously captured patient-reported outcome measures (PROMs) including those related
to disease progression, medication side effects, medication adherence, anxiety and
depression, and quality of life. The continuous assessment of outcome measures will
provide ongoing monitoring that is delivered directly to the electronic medical record
(EMR). This data allows abnormal outcome measures to trigger immediate expert-based
recommendations for care management with one click in the EMR through implementation of
the AI-driven ovarian cancer care pathways. Provider recommendations will be continuously
generated for the optimization of care that is based upon individual risk profiles,
disease stage, and health outcomes, resulting in dynamic and risk-dependent
recommendations. Remote patient monitoring will also allow for improved education and
instruction, including appointment reminders and medication adherence optimization. The
application will also provide nutritional support, mental support, and caregiver
connectivity. Given ovarian cancer will be a chronic condition for 80% of patients, the
critical challenge is to deliver high level care that improves patient outcomes while not
increasing the cost of health care. This project will assess a process by which this can
be done with the electronic medical record, a patient application, and AI-generated
patient care pathways. The development of such AI-powered care pathways designed for
ovarian cancer will be coordinated throughout the induction and maintenance treatment
phases of ovarian cancer management.
Criteria for eligibility:
Criteria:
Inclusion Criteria:
1. Female ≥18 years of age at Screening Visit.
2. Diagnosed with ovarian cancer, fallopian tube, or primary peritoneal cancer
3. Undergoing active treatment at some point during the study period including
chemotherapy, immunotherapy, targeted agent or hormonal therapy. If active treatment
has not yet started at time of screening, active treatment must be anticipated to
begin within 30 days of enrollment.
4. Written informed consent (and assent when applicable) obtained from subject or
subject's legal representative and ability for subject to comply with the
requirements of the study.
5. Access to IOS or Android-based smart phone
Exclusion Criteria:
1. Unwilling or unable to adhere to the protocol
2. Unwilling or unable to adhere to the informed consent
3. Age <18yo
4. Concurrent non-gynecologic cancer diagnosis requiring active treatment at enrollment
5. Presence of a condition or abnormality that in the opinion of the Investigator would
compromise the safety of the patient or the quality of the data.
Gender:
Female
Gender based:
Yes
Gender description:
Must have been diagnosed with ovarian cancer
Minimum age:
18 Years
Maximum age:
90 Years
Healthy volunteers:
No
Locations:
Facility:
Name:
UCLA / Jonsson Comprehensive Cancer Center
Address:
City:
Los Angeles
Zip:
90095-1406
Country:
United States
Status:
Recruiting
Contact:
Last name:
Jenny Lester
Phone:
310-794-9728
Email:
jlester@mednet.ucla.edu
Start date:
October 17, 2023
Completion date:
October 1, 2028
Lead sponsor:
Agency:
Jonsson Comprehensive Cancer Center
Agency class:
Other
Collaborator:
Agency:
University of California, Davis
Agency class:
Other
Collaborator:
Agency:
University of California, Irvine
Agency class:
Other
Collaborator:
Agency:
University of California, San Francisco
Agency class:
Other
Collaborator:
Agency:
University of California, San Diego
Agency class:
Other
Source:
Jonsson Comprehensive Cancer Center
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05523700