Acute Risk Monitoring for Oncology Therapy Regimen
Part of paid clinical trials in San Francisco, California.
- Sponsor
- University of California, San Francisco
- Study ID
- NCT07601802
- Status
- Completed
Conditions
- Acute Care Service Utilization
- Cancer
Eligibility Criteria
- Sex
- ALL
- Age
- 18 Years - N/A
- Healthy Volunteers
- Not accepted
Interventions
- Medical record review — OTHERRetrospective chart reviews for data collection will be conducted.
Study Details
Patients undergoing outpatient infusion systemic therapy for cancer are at risk for potentially preventable, unplanned acute care in the form of emergency department (ED) visits and hospitalizations. These events impact patient outcomes, treatment decisions, and healthcare costs. To address this need, the Centers for Medicare \& Medicaid Services developed the chemotherapy measure (OP-35). Recent randomized controlled studies indicate that electronic health record (EHR)-based machine learning (ML) approaches accurately direct supportive care to reduce acute care during radiotherapy. This study aims to develop and prospectively validate ML approaches to predict the risk of OP-35 qualifying, potentially preventable, acute care events within 30 days of infusion systemic therapy.
Key Dates
- Start date
- Jul 1, 2017
- Status verified
- May 2026
- Primary completion
- Mar 31, 2024
- Completion
- Mar 31, 2024
Study Design
- Enrollment
- 4,740 participants (actual)
Arms
- Arm: Patients receiving cancer therapy at University of California, San Francisco (UCSF)All adults undergoing systemic cancer-related therapy from July 2017 to March 2024 at any UCSF outpatient, infusion center with available OP-35 data.
Primary Outcome Measure
Area under the receiver operating characteristic curve (AUROC) for OP-35 prediction model. [ Time Frame: Up to 6.75 years ]
Locations (1)
| Facility | City | State | ZIP | Site coordinators |
|---|---|---|---|---|
| University of California, San Francisco | San Francisco | California | 94143 | - |
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