Feasibility and Clinical Utility of Prediction Models for Breast Cancer–Related Lymphedema Incorporating Racial Differences in Disease Incidence

IMPORTANCE: Breast cancer–related lymphedema (BCRL) is a common complication of axillary lymph node dissection (ALND) but can also develop after sentinel lymph node biopsy (SLNB). Several models have been developed to predict the risk of disease development before and after surgery; however, these models have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, low sensitivity or specificity, and lack of risk assessment for patients treated with SLNB. OBJECTIVE: To create simple and accurate prediction models for BCRL that can be used to estimate preoperative or postoperative risk. DESIGN, SETTING, AND PARTICIPANTS: In this prognostic study, women with breast cancer who underwent ALND or SLNB from 1999 to 2020 at Memorial Sloan Kettering Cancer Center and the Mayo Clinic were included. Data were analyzed from September to December 2022. MAIN OUTCOMES AND MEASURES: Diagnosis of lymphedema based on measurements. Two predictive models were formulated via logistic regression: a preoperative model (model 1) and a postoperative model (model 2). Model 1 was externally validated using a cohort of 34 438 patients with an International Classification of Diseases diagnosis of breast cancer. RESULTS: Of 1882 included patients, all were female, and the mean (SD) age was 55.6 (12.2) years; 80 patients (4.3%) were Asian, 190 (10.1%) were Black, 1558 (82.8%) were White, and 54 (2.9%) were another race (including American Indian and Alaska Native, other race, patient refused to disclose, or unknown). A total of 218 patients (11.6%) were diagnosed with BCRL at a mean (SD) follow-up of 3.9 (1.8) years. The BCRL rate was significantly higher among Black women (42 of 190 [22.1%]) compared with all other races (Asian, 10 of 80 [12.5%]; White, 158 of 1558 [10.1%]; other race, 8 of 54 [14.8%]; P