A M Moorman1, E J Th Rutgers2, E A Kouwenhoven3. 1. Department of Surgery, Hospital Group Twente, Almelo, The Netherlands. yvettemoorman@gmail.com. 2. Department of Surgery, Antoni van Leeuwenhoek/The Netherlands Cancer Institute, Amsterdam, The Netherlands. 3. Department of Surgery, Hospital Group Twente, Almelo, The Netherlands.
Abstract
BACKGROUNDS: Sentinel lymph node biopsy (SLNB) is standard care as a staging procedure in patients with invasive breast cancer. The axillary recurrence rate, even after positive SLNB, is low. This raises serious doubts regarding the clinical value of SLNB in early breast cancer. The purpose of this study is to select patients with low suspected axillary burden in whom SLNB might be omitted. PATIENTS AND METHODS: We retrospectively analyzed 2015 primary breast cancer patients between 2007 and 2015, with 982 patients allocated to the training and 961 to the validation cohort. Variables associated with nodal disease were analyzed and used to build a nomogram for predicting nodal disease. RESULTS: A total of 32.8% of patients had macrometastatic disease. A predictive model was constructed based on age, cN0, morphology, grade, multifocality, and tumor size with an area under the receiver operating characteristic curve (AUC) of 0.83. Considering a false-negative rate of 5%, 32.8% of patients could be spared axillary surgery. In a subanalysis of patients with relatively favorable characteristics, 26.8% had less than 5% chance of macrometastases. CONCLUSIONS: We present a model with excellent predictive value that can select one-third of patients in whom SLNB is deemed not necessary because of less than 5% chance of nodal involvement. Whether missing 1 in 20 patients with macrometastatic disease is worthwhile balanced against preventing side-effects of the SLN procedure remains to be established. A number of ongoing large prospective trials evaluating the outcome of omitting SLNB are awaited. Meanwhile, this nomogram may be used for individual decision-making.
BACKGROUNDS: Sentinel lymph node biopsy (SLNB) is standard care as a staging procedure in patients with invasive breast cancer. The axillary recurrence rate, even after positive SLNB, is low. This raises serious doubts regarding the clinical value of SLNB in early breast cancer. The purpose of this study is to select patients with low suspected axillary burden in whom SLNB might be omitted. PATIENTS AND METHODS: We retrospectively analyzed 2015 primary breast cancer patients between 2007 and 2015, with 982 patients allocated to the training and 961 to the validation cohort. Variables associated with nodal disease were analyzed and used to build a nomogram for predicting nodal disease. RESULTS: A total of 32.8% of patients had macrometastatic disease. A predictive model was constructed based on age, cN0, morphology, grade, multifocality, and tumor size with an area under the receiver operating characteristic curve (AUC) of 0.83. Considering a false-negative rate of 5%, 32.8% of patients could be spared axillary surgery. In a subanalysis of patients with relatively favorable characteristics, 26.8% had less than 5% chance of macrometastases. CONCLUSIONS: We present a model with excellent predictive value that can select one-third of patients in whom SLNB is deemed not necessary because of less than 5% chance of nodal involvement. Whether missing 1 in 20 patients with macrometastatic disease is worthwhile balanced against preventing side-effects of the SLN procedure remains to be established. A number of ongoing large prospective trials evaluating the outcome of omitting SLNB are awaited. Meanwhile, this nomogram may be used for individual decision-making.
Authors: Takamaru Ashikaga; David N Krag; Stephanie R Land; Thomas B Julian; Stewart J Anderson; Ann M Brown; Joan M Skelly; Seth P Harlow; Donald L Weaver; Eleftherios P Mamounas; Joseph P Costantino; Norman Wolmark Journal: J Surg Oncol Date: 2010-08-01 Impact factor: 3.454
Authors: Jerri S Fant; Michael D Grant; Sally M Knox; Sheryl A Livingston; Kimberly Ridl; Ronald C Jones; Joseph A Kuhn Journal: Ann Surg Oncol Date: 2003-03 Impact factor: 5.344
Authors: David N Krag; Stewart J Anderson; Thomas B Julian; Ann M Brown; Seth P Harlow; Joseph P Costantino; Takamaru Ashikaga; Donald L Weaver; Eleftherios P Mamounas; Lynne M Jalovec; Thomas G Frazier; R Dirk Noyes; André Robidoux; Hugh Mc Scarth; Norman Wolmark Journal: Lancet Oncol Date: 2010-10 Impact factor: 41.316
Authors: Jacqueline Sara Jeruss; David J Winchester; Stephen F Sener; Erika M Brinkmann; Malcolm M Bilimoria; Ermilo Barrera; Eihab Alwawi; Angel Nickolov; G M Schermerhorn; David J Winchester Journal: Ann Surg Oncol Date: 2004-12-27 Impact factor: 5.344
Authors: Umberto Veronesi; Giuseppe Viale; Giovanni Paganelli; Stefano Zurrida; Alberto Luini; Viviana Galimberti; Paolo Veronesi; Mattia Intra; Patrick Maisonneuve; Francesca Zucca; Giovanna Gatti; Giovanni Mazzarol; Concetta De Cicco; Dario Vezzoli Journal: Ann Surg Date: 2010-04 Impact factor: 12.969
Authors: Arpana M Naik; Jane Fey; Mary Gemignani; Alexandra Heerdt; Leslie Montgomery; Jeanne Petrek; Elisa Port; Virgilio Sacchini; Lisa Sclafani; Kimberly VanZee; Raquel Wagman; Patrick I Borgen; Hiram S Cody Journal: Ann Surg Date: 2004-09 Impact factor: 12.969
Authors: J Michael Guenther; Nora M Hansen; L Andrew DiFronzo; Armando E Giuliano; J Craig Collins; Baiba L Grube; Theodore X O'Connell Journal: Arch Surg Date: 2003-01
Authors: Karl Y Bilimoria; David J Bentrem; Nora M Hansen; Kevin P Bethke; Alfred W Rademaker; Clifford Y Ko; David P Winchester; David J Winchester Journal: J Clin Oncol Date: 2009-04-13 Impact factor: 44.544
Authors: Rosa F Hwang; Ana M Gonzalez-Angulo; Min Yi; Thomas A Buchholz; Funda Meric-Bernstam; Henry M Kuerer; Gildy V Babiera; Welela Tereffe; Diane D Liu; Kelly K Hunt Journal: Cancer Date: 2007-08-15 Impact factor: 6.860