{"@context":"https://schema.org","@type":"ScholarlyArticle","headline":"Nomogram for predicting risk of arm lymphedema following axillary lymph node dissection in breast cancer patients.","author":[{"@type":"Person","name":"Miaomiao Jia"},{"@type":"Person","name":"Lihui Pan"},{"@type":"Person","name":"Haibo Yang"},{"@type":"Person","name":"Jinnan Gao"},{"@type":"Person","name":"Wenzhuang Shen"},{"@type":"Person","name":"Xiaojun Zhang"}],"datePublished":"2025","isPartOf":{"@type":"Periodical","name":"Frontiers in oncology"},"identifier":"https://doi.org/10.3389/fonc.2025.1667939","description":"\n Purpose\n Breast cancer-related arm lymphedema (BCRaL) is a prevalent and severe complication post-breast cancer treatment, especially following axillary lymph node dissection (ALND). This study aimed to develop a nomogram for BCRaL risk prediction by identifying and integrating key risk factors, including chemotherapy type (neoadjuvant vs. adjuvant), to enhance individualized patient monitoring and prevention strategies.\n \n \n Patients and methods\n We conducted a retrospective analysis of clinical data from 535 breast cancer patients who received ALND and chemotherapy. Patients were divided into a training cohort (70%) and a validation cohort (30%). Univariate and multivariate Cox regression analyses identified independent risk factors for BCRaL, which were subsequently used to construct a nomogram. The model’s performance was assessed through calibration curves, ROC curves, and clinical decision curve analysis (DCA).\n \n \n Results\n The incidence of BCRaL in our cohort was 20.6%. Multivariate analysis identified several independent risk factors for BCRaL, including elevated body mass index (BMI), increased number of positive axillary lymph nodes, neoadjuvant chemotherapy (NAC), HER2-targeted therapy, and supraclavicular radiotherapy (SCRT). The nomogram developed based on these factors demonstrated strong predictive accuracy, with C-index values of 0.692 in the training cohort and 0.719 in the validation cohort. ROC curve analysis revealed AUC values reaching 0.760, indicating good discriminative ability. Time-dependent ROC curves further confirmed the model’s consistency across different follow-up periods. DCA validated the clinical utility of the nomogram, while survival analysis clearly distinguished between high-risk and low-risk BCRaL groups.\n \n \n Conclusion\n This study developed and internally validated a predictive model that integrates modern treatment modalities (NAC, HER2-targeted therapy, SCRT) with traditional risk factors to identify high-risk BCRaL patients undergoing ALND and chemotherapy. The model requires external validation in future studies. Consequently, the nomogram presents a potential tool for strategizing precision prevention, necessitating further evaluation before its broader adoption in clinical practice.\n ","url":"https://innscience.ca/en/community/literature/c819f12f-c65a-4112-8441-7ae94d6255a0"}