Risk factors analysis of breast cancer-related lymphedema based on the proportion of the arm lymph flow above and below the axillary vein / 中华普通外科杂志

ABSTRACT

Objective:To develop and validate an clinical prediction model for the risk of breast cancer-related lymphedema (BCRL).Methods:Breast cancer patients who were prepared to undergo axillary lymph node dissection were propsectively enrolled, indocyanine green combined with Photodynamic Eye (PDE) was applied to reveal the arm lymphatic flow . The arm lymphatic fluorescence images were collected to calculate the proportion of arm lymph flow above and below the axilla vein. Volumetric measurements of both arms and subjective questionnaire were performed to evaluate the occurrence of lymphedema. A difference in volume between the arms >10% was defined as lymphedema. Univariate logistic regression analysis was used to analyze the relationship between each factor and BCRL. The stepwise forward method was used to include multiple factors in the logistic regression analysis to establish the prediction model.Results:Three hundred and twelve patients were enrolled. Fourty-five (14.4%) patients developed BCRL. Using the coefficients obtained from multivariate analysis, BMI ( OR 95% CI 1.34 (1.25-1.77), P<0.05), chemotherapy ( OR 95% CI 2.26 (1.97-2.63), P<0.05), regional lymph node radiotherapy ( OR 95% CI 1.59 (1.05-2.41), P<0.05) and the proportion of arm lymph flow above the level of the axillary vein ( OR 95% CI 0.70 (0.68-0.81), P<0.05) were identified as independent predictive factors for BCRL, and the following prediction equation was derived Y=0.369×(BMI at surgery)+0.713×(taxane-based chemotherapy)+0.862×(radiotherapy)-9.058×(proportion of the arm lymph above the axillary vein)-6.859 8. The ROC curve was screened to the optimal boundary value of 0.118 6 by the Youden's index. The sensitivity, specificity, positive predictive value and negative predictive value of prediction of this model were 93.3%, 79.4%, 73.3%, 98.6%, respectively. Conclusion:With the guidance of the predictive model, particular patients who need the preservation of axillary lymphatic system can be identified, and timely intervention can be carried out.