Breast cancer‐related lymphoedema: Risk factors and prediction model

Abstract

Aims: To identify the risk factors for lymphoedema following axillary lymph node dissection (ALND) in a European sample and to propose a lymphoedema prediction model for this population. Design: Predictive retrospective cohort study comparing women who developed lymphoedema in 2 years of undergoing ALND with those who did not developed lymphoedema. Methods: We reviewed the clinical records of 504 women who, between January 2008 and May 2018, underwent surgery for breast cancer that involved ALND. Logistic regression was used to identify significant risk factors for lymphoedema. The prediction accuracy of the model was assessed by calculating the area under the receiver operating characteristic curve. Results: Of the 504 women whose records were analysed, 156 developed lymphoedema. Significant predictors identified in the regression model were level of lymph node dissection, lymph node status, post-operative complications, body mass index (BMI) and number of lymph nodes extracted. The prediction model showed good sensitivity (80%) in the study population. Conclusions:The factor contributing most to the risk of lymphoedema was the level of lymph node dissection, and the only patient-related factor in the prediction model was BMI. The model offers good predictive capacity in this population and it is a simple tool that breast care units could use to assess the risk of lymphoedema following ALND. Nurses with specialist knowledge of lymphoedema have a key role to play in ensuring that women receive holistic and individualized care.

Multidisciplinary preventive intervention for breast cancer‐related lymphedema: An international consensus

“…Consistent with these results, a 2021 study in a European population found that the only patient-related risk factor for lymphedema following ALND was elevated BMI (Martínez-Jaimez et al, 2022). In light of these findings, our aim here was to achieve an expert consensus regarding weight control strategies for these patients, most of whom will be receiving (or have received) hormone therapy or chemotherapy, both of which can lead to weight gain.…”

Prediction models for breast cancer-related lymphedema: a systematic review and critical appraisal

“…The risk of bias was mainly derived from questions 1, 4, 5, 6, and 8, of which 1 was the sample size, and the researchers believed the number of events per variable (EPV) should be at least 20 [ 45 , 46 ]. And in Liu et al, Kim et al, Wang et al, Penn et al, Basta et al, Byun et al, and Martinez-Jaimez et al [ 13 , 29 , 30 , 32 , 35 , 36 , 39 ], EPV was higher than 20. Question 4 is about participants with missing data handled: most studies did not report changes in follow-up data; only Yuan et al, Liu et al, and Li et al [ 12 , 14 , 30 ] were at a low-bias risk; the study of Yuan et al [ 14 ] has no missing data; and Liu et al and Li et al [ 12 , 30 ] are cross-sectional analysis without missing data.…”

“…Question 4 is about participants with missing data handled: most studies did not report changes in follow-up data; only Yuan et al, Liu et al, and Li et al [ 12 , 14 , 30 ] were at a low-bias risk; the study of Yuan et al [ 14 ] has no missing data; and Liu et al and Li et al [ 12 , 30 ] are cross-sectional analysis without missing data. Question 5 is about the selection of predictors, and only Gross et al and Martinez-Jaimez et al [ 11 , 13 ] avoided selecting the predictors with a statistically significant univariable association. Question 8 is about the model performance.…”

“…At present, the risk prediction model mainly includes a nomogram, equation, and table. Most of the prediction models in our study included are nomograms; the studies of Martinez-Jaimez et al, Penn et al, and Kim et al [ 13 , 32 , 39 ] only report the final included predictors, without the specific content of the prediction model. In addition, the detailed description of the risk prediction model can promote its clinical application.…”

Evaluation of Circulating MicroRNAs and Adipokines in Breast Cancer Survivors with Arm Lymphedema

“…Although the survival rates for breast cancer are increasing, cancer survivors face several challenges following cancer treatment including arm lymphedema [ 3 , 4 ]. Arm or secondary lymphedema is characterized by abnormal swelling of one or both arms due to an accumulation of lymph fluid in the interstitial tissue spaces following surgery-associated damage of the lymphatic vessels such as axillary lymph nodes dissection, mastectomy, and regional radiotherapy [ 5 , 6 ]. Due to its multifactorial nature, the pathogenesis of secondary lymphedema remains unclear and the search for molecular factors associated with this condition is still ongoing.…”