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Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis
Published on: February 6, 2020
Identification of a Cytokine Biomarker for Prognostic Modeling of Breast Cancer-Related Lymphedema
Alison J Wu1,2, Neil Lin1,2,3, Jie Su4
1MD Program, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada.
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 patients with breast cancer who had undergone serum cytokine profiling during their treatment at the Princess Margaret Cancer Centre from 2010 to 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 IFNα2A as a potential biomarker for lymphedema development [OR, 3.10; 95% confidence interval (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%) versus 85% (77%-94%) for below versus above median concentrations of IFNα2A (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 IFNα2A in 31% (eight of 26) of cases. Our combined logistic regression model using both IFNα2A 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 favorable improvement compared with the logistic regression model using clinical risk factors alone. IFNα2A in combination with established clinical risk factors may be useful for improving BCRL prognostication.
Significance:
The cytokine IFNα2A was identified as a potentially complementary biomarker to improve the stratification of high- and low-risk patients for BCRL. This will help enable earlier intervention to reduce long-term morbidity for those at high risk for lymphedema while minimizing burdensome interventions for those at low risk.
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