Predictive models for breast cancer-related lymphedema after mastectomy.

OBJECTIVES

To establish a nomogram incorporating clinical characteristics to predict the risk of breast cancer-related lymphedema (BCRL).

METHODS

In this retrospective study, we included 200 consecutive patients with breast cancer undergoing radical mastectomy from January 2022 to December 2023. Of these, 98 patients diagnosed with BCRL were designated as the experimental group, while 102 patients served as the control group. Logistic regression analyses were conducted to explore factors associated with clinical prognosis and to construct and validate a nomogram for predicting the risk of BCRL using R language version 4.1.2.

RESULTS

Univariate and multivariate logistic regression analyses identified six independent risk factors: the number of lymph node dissections (95% CI: 1.425-8.956, P < 0.01), radiotherapy (95% CI: 1.134-2.341, P < 0.01), lack of functional exercise (95% CI: 4.908-19.064, P = 0.001), adjuvant and neoadjuvant chemotherapy (95% CI: 1.763-4.287, P = 0.001), BMI (95% CI: 1.075-2.897, P < 0.05), and hypertension (95% CI: 1.077-2.999, P < 0.05). Using these variables, we developed a nomogram to predict the incidence of BCRL. The AUC value for the model was 0.74 (95% CI: 0.675-0.887), indicating acceptable agreement between predicted and observed outcomes. Decision curve analysis demonstrated good positive net benefits for the model.

CONCLUSION

The number of lymph node dissections, radiotherapy, lack of functional exercise, adjuvant and neoadjuvant chemotherapy, BMI, and hypertension are independent risk factors for BCRL. Moreover, the nomogram prediction model showed good predictive performance, high accuracy, and clinical applicability.