Lymphedema becomes increasingly challenging to treat over time because of the development of progressive fibrosis during the late stages of this condition. Understanding who is at greatest risk of lymphedema will facilitate monitoring, earlier disease diagnosis, and early initiation of therapies to decrease disease morbidity. To date, the main biological factor identified is high body mass index. Biologically, BMI is a gross estimate of the body adiposity of an individual based on height and weight. Across different studies, BMI has demonstrated a high variation in the significance and effect size with regard to lymphedema risk. To appropriately triage and monitor these patients for timely diagnosis and treatment, robust risk models are required. For this purpose researchers of Toronto, Canada conducted a study to evaluate the prognostic value of mammographic breast density in estimating lymphedema severity.

It was a randomized prognostic study of 373 women (median age 52 years) who had completed curative treatment for the first diagnosis of breast cancer. Researchers collected data from July 16, 2018, to March 3, 2020, from the electronic health records of patients of the Cancer Rehabilitation and Survivorship Program at the Princess Margaret Cancer Centre in Toronto, Ontario, Canada. They were randomly assigned to either training (n=247) or validation (n=126) cohorts. They also included patients who received follow-up care at the study center from January 1, 2016, to May 1, 2018. Researchers assessed the patients demographic and clinical characteristics included age, sex, body mass index (BMI), medical history, cancer characteristics, and cancer treatment. They used Spearman correlation model to calculate the measured and predicted volume of lymphedema. They determined Area under the curve (AUC) values for predicting the occurrence of at least mild lymphedema (volume, >200 mL) and severe lymphedema (volume, >500 mL) at the time of initial lymphedema diagnosis.

Key findings of the result:

♦ Upon multivariate linear regression, they identified 3 patient factors (age, BMI, and mammographic breast density), 1 cancer factor (number of pathological lymph nodes), and 1 treatment factor (axillary lymph node dissection) as independent prognostic variables.

♦ The found that there was a significant moderate correlation between the predicted and measured values of lymphedema volume, with Spearman correlation coefficients of 0.53 and 0.42 in the training and validation data sets, respectively.

♦ In the validation cohort, the area under the receiver operating characteristic curve values were 0.72 for predicting mild lymphedema (>200 to ≤500 mL) and 0.83 for severe lymphedema (>500 mL).

The authors concluded, "This prognostic study found that patients with low breast density appeared to be at a higher risk of developing severe lymphedema. The finding suggests that by combining breast density with established risk factors a multivariate linear regression model could be used to predict the development of lymphedema and provide volumetric estimates of lymphedema severity in patients with breast cancer".

For further information:

https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2772800