51. Predicting Cancer-related Lymphedema: A Decade of Longitudinal Outcomes From a Tertiary Cancer Center

PURPOSE: No clinically applicable method currently exists to predict which patients will develop lymphedema after axillary lymph node dissection (ALND) or when it will occur. This decade-long study aimed to identify lymphedema predictors and create an algorithm estimating both risk and timing of onset. METHODS: We conducted a longitudinal-study of patients who underwent ALND at a tertiary-cancer-center from 2013 to 2024. Demographic and clinical data, along with lymphedema onset, were recorded. Two multivariate-regression models were developed to predict 1) risk of lymphedema and 2) time to first diagnosis. RESULTS: Among 15,666 patients, 14.9% (2,345) developed lymphedema, with an average onset of 20.5 months post-ALND. Key predictors included chemotherapy (OR=2.3, 95% CI 2.1-2.5, p<0.0001), radiation (OR=1.9, 95% CI 1.8-2.1, p<0.0001), black race (OR=1.4, 95% CI 1.3-1.7, p<0.0001), BMI>30 (OR=1.4, 95% CI 1.3-1.5, p<0.0001), and diabetes (OR=1.2, 95% CI 1.1-1.3, p<0.0001). Rapid-onset predictors included black race (β=-4.2, 95% CI -6.8 to -1.4, p=0.002), radiation (β=-4.5, 95% CI -6.3 to -2.6, p<0.0001), and diabetes (β=-2.8, 95% CI -5.0 to -0.6, p=0.01). Hemoglobin-A1C was an independent predictive factor for both lymphedema development (OR=1.2, 95% CI 1.1-1.3, p=0.04) and rapid disease development (β=-3.3, 95% CI -6.1 to -1.2, p=0.003). Model accuracy was 79.65% (AUC=0.72, 95% CI 0.71-0.73, p<0.0001). CONCLUSION: This is the largest longitudinal study to provide clinically applicable prediction algorithms for individualized risk and time-to-diagnosis predictions, and the first to highlight Hb-A1C as a novel independent predictive marker. These findings offer a foundation for individualized screening protocols and early preventative measures in high-risk patients.