Development and Validation of a Nomogram to Predict Lymphedema After Axillary Surgery and Radiation Therapy in Women With Breast Cancer From the NCIC CTG MA.20 Randomized Trial
Journal Articles
Overview
Research
Identity
Additional Document Info
View All
Overview
abstract
PURPOSE: Regional nodal irradiation for women with breast cancer is known to be an important risk factor for the development of upper extremity lymphedema, but tools to accurately predict lymphedema risks for individual patients are lacking. This study sought to develop and validate a nomogram to predict lymphedema risk after axillary surgery and radiation therapy in women with breast cancer. METHODS AND MATERIALS: Data from 1832 women accrued on the MA.20 trial between March 2000 and February 2007 were used to create a prognostic model with National Cancer Institute Common Toxicity Criteria Version 2.0 grade 2 or higher lymphedema as the primary endpoint. Multivariable logistic regression estimated model performance. External validation was performed on data from a single large academic cancer center (N = 785). RESULTS: In the MA.20 trial cohort, 3 risk factors were predictive of lymphedema risk: body mass index (adjusted odds ratio, 1.05 per unit body mass index; 95% confidence interval [CI], 1.03-1.08, P < .001), extent of axillary surgery (adjusted odds radio for 8-11 lymph nodes removed, 3.28 [95% CI, 1.53-7.89] P = .004; 12-15 lymph nodes, 4.04 [95% CI, 1.76-10.26] P = .002; ≥16 nodes, 5.08 [95% CI, 2.26-12.70] P < .001), and extent of nodal irradiation (adjusted odds radio for limited, 1.66 [95% CI, 1.08-2.56] P = .02; for extensive, 2.31 [95% CI, 1.28-4.10] P = .004). A nomogram was created from these data that predicted lymphedema risk with reasonable accuracy confirmed by both internal (concordance index, 0.69; 95% CI, 0.64-0.74) and external validation (concordance index, 0.71; 95% CI, 0.66-0.76). CONCLUSIONS: The nomogram created from the MA.20 randomized trial data using clinical information may be useful for lymphedema screening and risk stratification for therapeutic intervention trials.