Machine Learning to Predict Acute Care During Cancer Therapy (Chemo-SHIELD)

September 19, 2023 updated by: Duke University

Generalizable Machine Learning to Predict Acute Care During Outpatient Systemic Cancer

The objective of this study is to apply a validated machine-learning based model (SHIELD-RT, NCT04277650) to a cohort of patients undergoing systemic therapy as outpatient cancer treatment to generate an automatic system for the prediction of unplanned hospital admission rates and emergency department encounters.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

A previously described machine learning (ML)-based model accurately predicted ED visits or hospitalizations for cancer patients undergoing radiation therapy or chemoradiation. An IRB approved prospective randomized trial, SHIELD-RT (NCT04277650) found that preemptive intervention for patients undergoing radiation and chemoradiation based on the ML model's risk stratification decreased the relative risk of acute care visits by 50%, showing that ML-guided escalation of care improved personalized supportive care and treatment compliance while decreasing healthcare costs.

The objective of this study is to apply this validated ML based model to a cohort of patients undergoing systemic therapy as outpatient cancer treatment to generate an automatic system for the prediction of unplanned hospital admission rates and emergency department encounters. Once validated, this study will add to the previously published body of evidence supporting a randomized trial evaluating the ML algorithm's ability to assign intervention for patients receiving systemic therapy at highest risk for acute care encounters.

Study Type

Observational

Enrollment (Actual)

12000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • United States
    • North Carolina
      • Durham, North Carolina, United States, 27710
        • Duke University Health System

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

Duke patients undergoing chemotherapy who had at least one treatment encounter between 1/7/2019 and 6/30/2019

Description

Inclusion Criteria:

  • had treatment encounter in the Duke Medical Oncology department from January 7th, 2019 to June 30th, 2019
  • DUHS medical record available

Exclusion Criteria:

-

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
number of unplanned of hospital admission or emergency department visits during systemic therapy
Time Frame: 12 months
12 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Duke University

Collaborators

University of California, San Francisco

Investigators

  • Principal Investigator: Manisha Palta, MD, Duke Health

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 3, 2022

Primary Completion (Actual)

September 19, 2023

Study Completion (Actual)

September 19, 2023

Study Registration Dates

First Submitted

November 5, 2021

First Submitted That Met QC Criteria

November 5, 2021

First Posted (Actual)

November 16, 2021

Study Record Updates

Last Update Posted (Actual)

September 21, 2023

Last Update Submitted That Met QC Criteria

September 19, 2023

Last Verified

September 1, 2023

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • Pro00109633

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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