medwireNews: Mammographic breast density is independently associated with lymphedema risk in women who undergo curative surgery for breast cancer and could be added to established risk factors to predict lymphedema severity, say researchers.
“Currently, most lymphedema risk models are based on cancer and treatment risk factors, yet these features do not fully account for the risk,” write Fei-Fei Liu (Princess Margaret Cancer Centre, Toronto, Ontario, Canada) and co-authors in JAMA Network Open.
They add: “Improved risk modeling that incorporates the underlying patient-specific biological drivers of this condition is required for a more accurate and personalized risk assessment.”
To address this, Lui and team investigated whether mammographic breast density, as a surrogate for adiposity, was associated with lymphedema in 373 women (median age 52 years) who had completed curative treatment for a first diagnosis of breast cancer.
The researchers divided the women into training (n=247) and validation (n=126) cohorts and found that, in the training cohort, lower mammographic breast density, higher age, BMI, and number of pathologic lymph nodes, and treatment with axillary lymph node dissection (ALND) were each independently associated with an increased risk for lymphedema.
Using these variables, the researchers developed an equation to predict upper extremity lymphedema volume.
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.
Further analysis showed that more than 75% of predicted values were within 200 mL of the measured value.
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 2-year lymphedema-free survival rates were 68% in the women with a predicted lymphedema volume of more than 200 mL and 83% in those with a lower predicted volume. This translated to a significant 2.39-fold increased risk for developing lymphedema greater than 200 mL in patients with high- versus low-volume prediction.
Lui and co-authors say their model will allow patients to be stratified into four lymphedema risk categories ranging from unlikely to develop any lymphedema to likely to develop severe lymphedema.
Treatment can then be based on risk, for example for “patients who are likely to develop limited or mild lymphedema, early modification of risk factors (eg, exercise and BMI reduction), conservative use of ALND, and/or more frequent monitoring for lymphedema development will facilitate early initiation of conservative therapies (eg, compression therapies) that minimize morbidity from lymphedema,” they write.
In an accompanying comment, Maggie Lee DiNome, from the University of California, Los Angeles in the USA, says that as more patients with breast cancer are cured, “the implications of the available treatments for long-term quality-of-life outcomes must continue to be addressed.”
She believes that Liu et al “have identified a novel predictor of lymphedema” in mammographic breast density, which “could improve the identification of patients at risk,” but cautions that the model “needs to be further validated against independent data sets.”
In spite of this, DiNome concludes that “the uniform availability of mammographic breast density data makes this model a readily available and attractive tool.”
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JAMA Netw Open 2020; 3: e2024373
JAMA Netw Open 2020; 3: e2024923