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Arm Swelling Occurence in Breast Cancer Patients With Nodal Radiotherapy: Impact of Informing Them of AI-predicted Risk

NCT07187726 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 724

Last updated 2026-05-19

No results posted yet for this study

Summary

Radiotherapy after breast cancer surgery can lead to side effects like arm lymphedema (arm swelling). Lymphedema can cause long-term discomfort and affect quality of life.

The goal of this clinical investigation is to determine whether using an artificial intelligence (AI) tool to predict the risk of developing arm lymphedema after breast cancer radiotherapy can help patients and physicians make better treatment decisions.

This AI tool has been developed to determine each patient's personalized risk of developing lymphedema. The risk is shown using a web app that explains the factors involved and offers suggestions like using a compression sleeve to reduce the risk.

Women (≥18 years) with breast cancer (cT1-4, cN0-N3, M0) requiring regional lymph node irradiation post-mastectomy or breast-conserving surgery are eligible, regardless of hormone receptor status, tumor grade, or HER2 status.

Patients will be randomly divided into two groups:

* Experimental group: Patients and physicians will see the AI-predicted risk and use it to guide treatment choices.
* Control group: The risk is not shown.

The radiotherapy treatment will be exactly the same as the treatment that you would have received if you had not taken part in this clinical investigation. The only intervention will be whether or not the risk you are informed of the risk of developing lymphedema.

All patients will be followed for two years to monitor:

* How risk communication influences radiotherapy treatment choices
* The occurrence of side effects
* The predictive performance of the AI tool
* Patients' quality of life
* Compliance with compression sleeve use
* Loco-regional recurrence-free survival, distant disease-free survival, and overall survival

Conditions

  • Unilateral Breast Neoplasms

Interventions

DEVICE

XAINET AI tool

The AI-based prediction of arm lymphedema risk is communicated to the patient and treating physician.

Sponsors & Collaborators

  • UNICANCER

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-10-07
Primary Completion
2029-01-31
Completion
2029-01-31

Countries

  • France
  • Netherlands

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07187726 on ClinicalTrials.gov