Lymphedema Prospective Surveillance and Risk Reduction

Stout, Nicole L.; Armer, Jane M.

doi:10.1007/978-3-030-93039-4_4

Cited by 1 publication

(2 citation statements)

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“…In terms of postoperative surveillance, standard surveillance measures, such as arm circumference measurements and bioimpedance spectroscopy, are similarly resource and time intensive. 61 Use of our postoperative model can decrease the number of clinic visits that patients need to make for repeated arm measurements. Patients' predicted risk of BCRL can be calculated based on a simple 1-question survey about arm swelling; those that screen above the desired risk threshold can be called in for additional evaluation.…”

Section: Discussionmentioning

confidence: 99%

“…A similar approach may be applied to preventive drug therapies. In terms of postoperative surveillance, standard surveillance measures, such as arm circumference measurements and bioimpedance spectroscopy, are similarly resource and time intensive . Use of our postoperative model can decrease the number of clinic visits that patients need to make for repeated arm measurements.…”

Section: Discussionmentioning

confidence: 99%

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Feasibility and Clinical Utility of Prediction Models for Breast Cancer–Related Lymphedema Incorporating Racial Differences in Disease Incidence

et al. 2023

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ImportanceBreast cancer–related lymphedema (BCRL) is a common complication of axillary lymph node dissection (ALND) but can also develop after sentinel lymph node biopsy (SLNB). Several models have been developed to predict the risk of disease development before and after surgery; however, these models have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, low sensitivity or specificity, and lack of risk assessment for patients treated with SLNB.ObjectiveTo create simple and accurate prediction models for BCRL that can be used to estimate preoperative or postoperative risk.Design, Setting, and ParticipantsIn this prognostic study, women with breast cancer who underwent ALND or SLNB from 1999 to 2020 at Memorial Sloan Kettering Cancer Center and the Mayo Clinic were included. Data were analyzed from September to December 2022.Main Outcomes and MeasuresDiagnosis of lymphedema based on measurements. Two predictive models were formulated via logistic regression: a preoperative model (model 1) and a postoperative model (model 2). Model 1 was externally validated using a cohort of 34 438 patients with an International Classification of Diseases diagnosis of breast cancer.ResultsOf 1882 included patients, all were female, and the mean (SD) age was 55.6 (12.2) years; 80 patients (4.3%) were Asian, 190 (10.1%) were Black, 1558 (82.8%) were White, and 54 (2.9%) were another race (including American Indian and Alaska Native, other race, patient refused to disclose, or unknown). A total of 218 patients (11.6%) were diagnosed with BCRL at a mean (SD) follow-up of 3.9 (1.8) years. The BCRL rate was significantly higher among Black women (42 of 190 [22.1%]) compared with all other races (Asian, 10 of 80 [12.5%]; White, 158 of 1558 [10.1%]; other race, 8 of 54 [14.8%]; P &lt; .001). Model 1 included age, weight, height, race, ALND/SLNB status, any radiation therapy, and any chemotherapy. Model 2 included age, weight, race, ALND/SLNB status, any chemotherapy, and patient-reported arm swelling. Accuracy was 73.0% for model 1 (sensitivity, 76.6%; specificity, 72.5%; area under the receiver operating characteristic curve [AUC], 0.78; 95% CI, 0.75-0.81) at a cutoff of 0.18, and accuracy was 81.1% for model 2 (sensitivity, 78.0%; specificity, 81.5%; AUC, 0.86; 95% CI, 0.83-0.88) at a cutoff of 0.10. Both models demonstrated high AUCs on external (model 1: 0.75; 95% CI, 0.74-0.76) or internal (model 2: 0.82; 95% CI, 0.79-0.85) validation.Conclusions and RelevanceIn this study, preoperative and postoperative prediction models for BCRL were highly accurate and clinically relevant tools comprised of accessible inputs and underscored the effects of racial differences on BCRL risk. The preoperative model identified high-risk patients who require close monitoring or preventative measures. The postoperative model can be used for screening of high-risk patients, thus decreasing the need for frequent clinic visits and arm volume measurements.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%