Highlights
- •Predictors of lymphoedema risk included time since breast cancer surgery, level of lymph node dissection, number of lymph nodes dissected, radiotherapy, and postoperative BMI.
- •These results have potential value in guiding strategies for early identification and monitoring of lymphoedema and patient education in clinical practice.
Abstract
Objective
Breast cancer-related lymphedema (BCRL) is a common post-operative complication in
patients with breast cancer. Here, we sought to develop and validate a predictive
model of BCRL in Chinese patients with breast cancer.
Methods
Clinical and demographic data on patients with breast cancer were collected between
2016 and 2021 at a Cancer Hospital in China. A nomogram for predicting the risk of
lymphedema in postoperative patients with breast cancer was constructed and verified
using R 3.5.2 software. Model performance was evaluated using area under the ROC curve
(AUC) and goodness-of-fit statistics, and the model was internally validated.
Results
A total of 1732 postoperative patients with breast cancer, comprising 1212 and 520
patients in the development and validation groups, respectively, were included. Of
these 438 (25.39%) developed lymphedema. Significant predictors identified in the
predictive model were time since breast cancer surgery, level of lymph node dissection,
number of lymph nodes dissected, radiotherapy, and postoperative body mass index.
At the 31.9% optimal cut-off the model had AUC values of 0.728 and 0.710 in the development
and validation groups, respectively. Calibration plots showed a good match between
predicted and observed rates. In decision curve analysis, the net benefit of the model
was better between threshold probabilities of 10%–80%.
Conclusion
The model has good discrimination and accuracy for lymphedema risk assessment, which
can provide a reference for individualized clinical prediction of the risk of BCRL.
Multicenter prospective trials are required to verify the predictive value of the
model.
Keywords
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Article info
Publication history
Published online: December 31, 2022
Accepted:
December 14,
2022
Received in revised form:
December 5,
2022
Received:
August 26,
2022
Identification
Copyright
© 2022 Published by Elsevier Ltd.
