Validation of a nomogram for predicting the risk of lymphedema following contemporary treatment for breast cancer: a large multi-institutional study (KROG 20-05)

Purpose We previously constructed a nomogram for predicting the risk of arm lymphedema following contemporary breast cancer treatment. This nomogram should be validated in patients with different background characteristics before use. Therefore, we aimed to externally validate the nomogram in a large multi-institutional cohort. Methods Overall, 8835 patients who underwent breast cancer surgery during 2007-2017 were identified. Data of variables in the nomogram and arm lymphedema were collected. The nomogram was validated externally using C-index and integrated area under the curve (iAUC) with 1000 bootstrap samples and by calibration plots. Results Overall, 1377 patients (15.6%) developed lymphedema. The median time from surgery to lymphedema development was 11.4 months. Lymphedema rates at 2, 3, and 5 years were 11.2%, 13.1%, and 15.6%, respectively. Patients with lymphedema had significantly higher body mass index (median, 24.1 kg/m(2) vs. 23.4 kg/m(2)) and a greater number of removed nodes (median, 17 vs. 6) and more frequently underwent taxane-based chemotherapy (85.7% vs. 41.9%), total mastectomy (73.1% vs. 52.1%), conventionally fractionated radiotherapy (71.9% vs. 54.2%), and regional nodal irradiation (70.7% vs 22.4%) than those who did not develop lymphedema (all P < 0.001). The C-index of the nomogram was 0.7887, and iAUC was 0.7628, indicating good predictive accuracy. Calibration plots confirmed that the predicted lymphedema risks were well correlated with the actual lymphedema rates. Conclusion This nomogram, which was developed using factors related to multimodal breast cancer treatment and was validated in a large multi-institutional cohort, can well predict the risk of breast cancer-related lymphedema.

Automated summary

The study externally validated a nomogram for predicting the risk of breast cancer-related lymphedema, demonstrating good predictive accuracy and the ability to predict the risk of lymphedema occurrence effectively.