207 Participants NeededMy employer runs this trial

AI-Enhanced Review for Cancer Treatment Safety

OM
VX
Overseen ByVictoria Xu
Age: 18+
Sex: Any
Trial Phase: Academic
Sponsor: UNC Lineberger Comprehensive Cancer Center
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests a new AI tool designed to help doctors and staff catch mistakes in cancer treatment plans before treatment begins. By highlighting patterns and warning signs, the AI aims to improve patient safety and reduce errors. It focuses on enhancing care for prostate cancer patients receiving radiation therapy. The AI-Enhanced Pretreatment Peer-review Process plays a central role in this effort. The trial seeks prostate cancer patients undergoing radiation therapy and doctors involved in reviewing treatment plans at specific clinics.

As an unphased trial, this study offers patients the chance to contribute to innovative research that could enhance treatment safety and effectiveness.

Do I have to stop taking my current medications for this trial?

The trial does not specify whether you need to stop taking your current medications. Since the study involves reviewing treatment plans and not delivering any interventions to patients, it's unlikely that you would need to change your medications.

What prior data suggests that this AI-Enhanced Pretreatment Peer-review Process is safe?

Research has shown that using AI to review radiation therapy plans enhances treatment safety for patients. This AI tool identifies mistakes in treatment plans that might otherwise go unnoticed and ensures consistent safety standards across various healthcare settings. Studies indicate that AI effectively spots potential problems, reducing errors and improving safety.

This AI tool poses no direct safety concerns for patients, as it assists medical staff in planning treatments rather than interacting directly with patients. Acting as a safety net, the AI ensures treatments are correctly planned before they begin. The tool aims to improve outcomes by making treatment plans more accurate and safer.12345

Why are researchers excited about this trial?

Researchers are excited about this trial because it explores how AI can enhance the safety of cancer treatments. Unlike standard peer-review processes, which rely solely on human expertise, this AI-enhanced method assists radiation oncology providers by swiftly analyzing treatment plans and highlighting potential safety concerns. This innovative approach aims to improve patient outcomes by ensuring that radiation therapy is delivered as safely and effectively as possible. By integrating AI, researchers hope to streamline the review process, reduce errors, and ultimately enhance the overall quality of cancer care.

What evidence suggests that this AI-enhanced peer-review process is effective for improving cancer treatment safety?

This trial will evaluate the AI-Enhanced Pretreatment Peer-review Process for cancer treatment safety. Studies have shown that artificial intelligence (AI) in radiation therapy can enhance treatment safety and accuracy. Research indicates that AI-supported reviews can identify mistakes that might otherwise go unnoticed, maintaining consistent safety standards. Specifically, one study found that AI tools reduced review time and error rates, leading to better treatment outcomes. Additionally, AI can automatically segment images, significantly reducing the workload for medical teams. Overall, AI-assisted methods have made cancer treatment planning more reliable and effective.12345

Who Is on the Research Team?

LM

Lukasz Mazur, PhD

Principal Investigator

UNC Lineberger Comprehensive Cancer Center

Are You a Good Fit for This Trial?

This trial is for adults (18+) with prostate cancer receiving radiation therapy at participating clinics, and for healthcare providers involved in peer-review of treatment plans. Patients are not directly treated by the intervention. People unable to give consent or sites that can't use the workflow cannot join.

Inclusion Criteria

I am 18 or older and have had prostate cancer radiation at a participating site.
I am 18 or older and attend peer-review meetings at a participating clinic.

Exclusion Criteria

My healthcare team can follow all study procedures and requirements.
Has dementia, altered mental status, or any psychiatric or co-morbid condition prohibiting the understanding or rendering of informed consent

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Pre-treatment Peer Review

AI-enhanced peer review process to identify and correct potential errors in radiation therapy treatment plans before therapy begins

Baseline

Radiation Therapy

Patients receive radiation therapy with treatment plans reviewed and potentially adjusted based on AI-enhanced peer review

Varies per patient

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

  • AI-Enhanced Pretreatment Peer-review Process

Trial Overview

The study tests an AI tool that helps doctors and staff review radiation treatment plans before patients start therapy. The tool highlights differences in planning styles and points out important warning signs to help catch mistakes early, aiming to improve patient safety.

How Is the Trial Designed?

2

Treatment groups

Experimental Treatment

Active Control

Group I: ProvidersExperimental Treatment1 Intervention
Group II: PatientsActive Control1 Intervention

Find a Clinic Near You

Who Is Running the Clinical Trial?

UNC Lineberger Comprehensive Cancer Center

Lead Sponsor

Trials
377
Recruited
95,900+

Agency for Healthcare Research and Quality (AHRQ)

Collaborator

Trials
415
Recruited
6,777,000+

Citations

Enhanced Pretreatment Peer-review Process to Improve ...

This research aims to strengthen and automate the peer-review process using AI and machine learning (ML) to improve error detection and address complex ...

Artificial Intelligence (AI)-Enhanced Pretreatment Peer ...

AI-supported peer review can help catch errors that might otherwise go unnoticed and promote consistent, equitable safety standards across both rural and urban ...

AI in Radiation Oncology: A Comprehensive Review of ... - PMC

The efficiency of complex TMI/TMLI treatment planning can be significantly improved by AI auto-segmentation, achieving ~75% manual workload ...

Artificial Intelligence-Assisted Peer Review in Radiation ...

Our hypothesis is that artificial intelligence (AI) and machine language technologies can enhance peer-review efficacy by screening cases for ...

Enhanced Pretreatment Peer-review Process to Improve ...

"This prospective study will test artificial intelligence (AI) and machine learning (ML) decision support tools. This tool is designed to help doctors, phy…