Annals of Surgical Oncology

, Volume 19, Issue 8, pp 2580–2589 | Cite as

Nomograms for Predicting the Risk of Arm Lymphedema after Axillary Dissection in Breast Cancer

  • José Luiz B. BevilacquaEmail author
  • Michael W. Kattan
  • Yu Changhong
  • Sergio Koifman
  • Inês E. Mattos
  • Rosalina J. Koifman
  • Anke Bergmann
Breast Oncology



Lymphedema (LE) after axillary lymph node dissection (ALND) is a multifactorial, chronic, and disabling condition that currently affects an estimated 4 million people worldwide. Although several risk factors have been described, it is difficult to estimate the risk in individual patients. We therefore developed nomograms based on a large data set.


Clinicopathologic features were collected from a prospective cohort comprising 1,054 women with unilateral breast cancer undergoing ALND as part of their surgical treatment from August 2001 to November 2002. LE was defined as a volume difference of at least 200 ml between arms at 6 months or more after surgery. The cumulative incidence of LE was ascertained by the Kaplan–Meier method, and Cox proportional hazard models were used to predict the risk of developing LE on the basis of the available data at each time point: model 1, preoperatively; model 2, within 6 months from surgery; and model 3, at 6 months or later after surgery.


The 5 year cumulative incidence of LE was 30.3%. Independent risk factors for LE were age, body mass index, ipsilateral arm chemotherapy infusions, level of ALND, location of radiotherapy field, development of postoperative seroma, infection, and early edema. When applied to the validation set, the concordance indices were 0.706, 0.729, and 0.736 for models 1, 2, and 3, respectively.


The proposed nomograms can help physicians and patients predict the 5 year probability of LE after ALND for breast cancer. Free online versions of the nomograms are available at


Breast Cancer Sentinel Lymph Node Sentinel Lymph Node Biopsy Lymphedema Axillary Lymph Node Dissection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to express their deepest gratitude to all patients, surgeons, and physical therapists at HCIII/INCA, Rio de Janeiro, Brazil; and to Dr. Kimberly Van Zee of Memorial Sloan-Kettering Cancer Center, NY; to Dr. Mauro Figueiredo Andrade of Faculdade de Medicina da Universidade de São Paulo, Brazil, for their insights, encouragement, and constructive criticism; to Dr. C. Greg Hagerty for his assistance in the computer application; and to Dr. Everardo Saad for proofreading. Supported by Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Postdoctoral grant E-26/100.851/2007, Conselho Nacional de Pesquisas e Desenvolvimento Tecnológico (CNPq), and Escola Nacional de Saúde Púbica, FIOCRUZ.

Supplementary material

10434_2012_2290_MOESM1_ESM.doc (83 kb)
Supplementary material 1 (DOC 83 kb)


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Copyright information

© Society of Surgical Oncology 2012

Authors and Affiliations

  • José Luiz B. Bevilacqua
    • 1
    • 2
    Email author
  • Michael W. Kattan
    • 3
  • Yu Changhong
    • 3
  • Sergio Koifman
    • 1
  • Inês E. Mattos
    • 1
  • Rosalina J. Koifman
    • 1
  • Anke Bergmann
    • 4
    • 5
  1. 1.Escola Nacional de Saúde Pública/FIOCRUZRio de JaneiroBrazil
  2. 2.Hospital Sirio-LibanesSao PauloBrazil
  3. 3.Department of Quantitative Health SciencesCleveland ClinicClevelandUSA
  4. 4.Instituto Nacional de Câncer (INCA)Rio de JaneiroBrazil
  5. 5.Centro Universitario Augusto Motta-UNISUAMRio de JaneiroBrazil

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