Clinical trial · Interventional
System for High-Intensity Evaluation During Radiotherapy
System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT): A Prospective Randomized Study of Machine Learning-directed Clinical Evaluations During Outpatient Cancer Radiation and Chemoradiation
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This quality improvement project will evaluate the implementation of a previously described intervention (twice per week on-treatment clinical evaluations) in a feasible fashion using a previously described machine learning algorithm identifying patients identified at high risk for an emergency visit or hospitalization during radiation therapy.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Chemotherapeutic Toxicity | — | UNRESOLVED | — |
| Radiation Therapy Complication | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Machine learning algorithm | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- ACTIVE_COMPARATOR
- label
- Once weekly clinical evaluation
- description
- Outpatient participants evaluated as high risk by the machine learning algorithm and provided once weekly clinical evaluations
- interventionNames
- Other: Machine learning algorithm
- type
- EXPERIMENTAL
- label
- Twice weekly clinical evaluation
- description
- Outpatient participants evaluated as high risk by the machine learning algorithm and provided twice weekly clinical evaluations
- interventionNames
- Other: Machine learning algorithm
Primary outcomes (1)
- measure
- Number of unplanned emergency department visits or hospital admissions
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: • started outpatient radiation therapy with or without concurrent systemic therapy at Duke Cancer Center Exclusion Criteria: * undergoing total body radiation therapy for hematopoetic stem cell transplantation * undergoing therapy as inpatient * treating physician who opted out of randomization * completed radiation therapy prior to algorithm execution
References
Publications (4)
- RESULTHong JC, Eclov NCW, Dalal NH, Thomas SM, Stephens SJ, Malicki M, Shields S, Cobb A, Mowery YM, Niedzwiecki D, Tenenbaum JD, Palta M. System for High-Intensity Evaluation During Radiation Therapy (SHIELD-RT): A Prospective Randomized Study of Machine Learning-Directed Clinical Evaluations During Radiation and Chemoradiation. J Clin Oncol. 2020 Nov 1;38(31):3652-3661. doi: 10.1200/JCO.20.01688. Epub 2020 Sep 4. PMID 32886536
- DERIVEDJames B Yu Md Mhs Fastro, Hong JC. AI Use in Prostate Cancer: Potential Improvements in Treatments and Patient Care. Oncology (Williston Park). 2024 May 13;38(5):208-209. doi: 10.46883/2024.25921021. PMID 38776517
- DERIVEDNatesan D, Eisenstein EL, Thomas SM, Eclov NCW, Dalal NH, Stephens SJ, Malicki M, Shields S, Cobb A, Mowery YM, Niedzwiecki D, Tenenbaum JD, Palta M, Hong JC. Health Care Cost Reductions with Machine Learning-Directed Evaluations during Radiation Therapy - An Economic Analysis of a Randomized Controlled Study. NEJM AI. 2024 Apr;1(4):10.1056/aioa2300118. doi: 10.1056/aioa2300118. Epub 2024 Mar 15. PMID 38586278
- DERIVEDHong JC, Eclov NCW, Stephens SJ, Mowery YM, Palta M. Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized controlled study. BMC Bioinformatics. 2022 Sep 30;23(Suppl 12):408. doi: 10.1186/s12859-022-04940-3. PMID 36180836