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Related Experiment Video

Updated: May 14, 2025

Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis
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Optimizing Lymphedema Management After Breast Cancer: Predictive Risk Models in Clinical Practice.

Enrique Cano-Lallave1, Elisa Frutos-Bernal2, María Anciones-Polo2

  • 1Rehabilitation Service, University Hospital of Salamanca, Salamanca, Spain.

Journal of Surgical Oncology
|May 13, 2025
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Summary

Breast cancer treatment can cause lymphedema. This study developed predictive tools using patient data and treatment details to identify high-risk individuals for better prevention and management.

Keywords:
breast cancerlymphadenectomylymphedemapredictive toolsrisk factors

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Area of Science:

  • Oncology
  • Rehabilitation Medicine
  • Medical Statistics

Background:

  • Lymphedema is a common complication following breast cancer treatment, negatively impacting patient quality of life.
  • Existing methods for assessing individual lymphedema risk are insufficient.
  • This study addresses the need for improved risk stratification in breast cancer patients.

Purpose of the Study:

  • To develop predictive tools for lymphedema risk assessment after breast cancer treatment.
  • To integrate patient characteristics, tumor features, and treatment modalities into predictive models.
  • To optimize clinical surveillance, prevention strategies, and early diagnosis of lymphedema.

Main Methods:

  • Analysis of data from 309 breast cancer patients who underwent lymphadenectomy.
  • Inclusion of patient demographics, tumor clinicopathological features, and treatment details.
  • Application of univariate and multivariate regression analyses and nomogram development for risk prediction.

Main Results:

  • The cumulative incidence of lymphedema was 18.4%.
  • Identified independent risk factors include high BMI, sedentary lifestyle, N stage, and specific radiotherapy fields.
  • The predictive model achieved an AUC of 0.75, indicating good predictive performance.

Conclusions:

  • The developed predictive tools enable healthcare professionals to identify patients at high risk for lymphedema.
  • These tools support the implementation of individualized prevention and management strategies.
  • Enhanced risk identification can lead to improved patient outcomes and quality of life.