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February 8, 2026Cancer Research Communications0 citationsOpen Access

Identification of a Cytokine Biomarker for Prognostic Modeling of Breast Cancer-Related Lymphedema

AWAlison WuNLNeil LinJSJie Su

Key Points

  • The aim is to evaluate blood-based cytokine biomarkers for predicting breast cancer-related lymphedema (BCRL).
  • Secondary analysis of a cohort of 147 breast cancer patients
  • Evaluation of serum cytokine profiling
  • Selection of prognostic cytokine variables via regression analysis
  • Kaplan-Meier analysis for lymphedema-free survival
  • Combined logistic regression modeling for risk prediction
  • Identified IFN-α2A as a potential biomarker for lymphedema (OR 3.10, p=0.042)
  • 3-year lymphedema-free survival of 95% with low IFN-α2A vs. 85% with high levels (p=0.026)
  • 31% of high-risk patients reclassified as low risk based on IFN-α2A levels
  • Combined model increased predictive performance (AUC: 0.895) compared to clinical factors alone

Abstract

Abstract Lymphedema is a chronic complication of breast cancer treatment, and early intervention is crucial to reduce morbidity. This study evaluated the role of blood-based cytokine biomarkers in the prognostication of breast cancer-related lymphedema (BCRL) to improve risk prediction. A secondary analysis of inflammatory biomarkers for BCRL was performed using a previously published cohort of 147 breast cancer patients who had undergone serum cytokine profiling during their treatment at the Princess Margaret Cancer Centre from 2010-2014. Prognostic cytokine variables for lymphedema were selected by regression analysis and independence from known clinical risk factors. Regression-based modeling was employed to integrate prognostic variables for the prediction of lymphedema occurrence. We identified the immunostimulatory cytokine IFN-α2A as a potential biomarker for lymphedema development (OR 3.10, 95% CI 1.05-9.51, p=0.042), independent from known clinical risk factors. Furthermore, Kaplan-Meier analysis demonstrated 3-year lymphedema-free survival of 95% (90-100%) vs. 85% (77-94%) for below vs. above median concentrations of IFN-α2A (p=0.026). In combination with an established clinical risk regression-based model, patients identified as high risk based on clinical factors alone were able to be correctly reclassified as low risk by IFN-α2A in 31% (8/26) of cases. Our combined logistic regression model using both IFN-α2A and clinical risk score achieved an AUC of 0.895 (95% CI: 0.796 - 0.971) and Brier Score of 0.101 (95% CI: 0.061 - 0.149), representing a favourable improvement compared to the logistic regression model using clinical risk factors alone. IFN-α2A in combination with established clinical risk factors may be useful for improving BCRL prognostication.

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Cite This Study

Wu et al. (2026) studied this question.

synapsesocial.com/papers/698827a20fc35cd7a8846740https://doi.org/10.1158/2767-9764.crc-25-0541
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