title: Molecular indicators of non-sentinel node status in breast cancer determined in preoperative biopsies by multiplexed sandwich immunoassays.
abstract: OBJECTIVE
  Purpose of this study was to determine the accuracy of prediction of non-sentinel lymph node (NSLN) involvement in sentinel node (SLN)-positive breast cancer patients based on protein concentrations measured in lysates from initially taken breast biopsies.
  
  
  METHODS
  Data on protein expression, previously generated by multiplexed bead-based immunoassays, were analysed by multivariate logistic regression to define parameter sets of value to predict NSLN involvement. Receiver-operator characteristics (ROCs) were calculated as indicators of diagnostic significance.
  
  
  RESULTS
  Analyses of data from all patients (n = 99) resulted in parameter sets that allowed direct prediction of the NSLN status with a ROC area under the curve (AUC) of 0.83. The clinically most relevant prediction of NSLN status in SLN-positive patients (n = 37) based on only seven parameters (including TIMP-2 as the most relevant single value) was possible with high accuracy indicated by an AUC of 0.89.
  
  
  CONCLUSIONS
  Parallel assessment of protein concentrations in breast biopsies is a highly promising approach to predict nodal involvement and even the NSLN status in SLN-negative breast cancer patients. Such diagnostic information could substantially reduce the number of completion axillary lymph node dissections in clinical practice.
authors.affiliation: Department of Obstetrics and Gynaecology, University of Ulm, Prittwitzstr. 43, 89075 Ulm, Germany.
authors.forename: Georg
authors.initials: G
authors.lastname: Sauer
authors.forename: Nicole
authors.initials: N
authors.lastname: Schneiderhan-Marra
authors.forename: Rainer
authors.initials: R
authors.lastname: Muche
authors.forename: Karin
authors.initials: K
authors.lastname: Koretz
authors.forename: Cornelia
authors.initials: C
authors.lastname: Kazmaier
authors.forename: Rolf
authors.initials: R
authors.lastname: Kreienberg
authors.forename: Thomas
authors.initials: T
authors.lastname: Joos
authors.forename: Helmut
authors.initials: H
authors.lastname: Deissler
mesh_terms: D000230:Adenocarcinoma / Q000737:chemistry / Q000556:secondary; D000328:Adult; D000368:Aged; D000465:Algorithms; D019540:Area Under Curve; D001365:Axilla; D014408:Biomarkers, Tumor / Q000032:analysis*; D001707:Biopsy, Needle; D001943:Breast Neoplasms / Q000737:chemistry* / Q000473:pathology* / Q000601:surgery; D018270:Carcinoma, Ductal, Breast / Q000737:chemistry / Q000556:secondary; D018275:Carcinoma, Lobular / Q000737:chemistry / Q000556:secondary; D005260:Female; D006801:Humans; D007118:Immunoassay / Q000379:methods*; D016015:Logistic Models; D008197:Lymph Node Excision; D008198:Lymph Nodes / Q000473:pathology*; D008207:Lymphatic Metastasis; D008875:Middle Aged; D015999:Multivariate Analysis; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D057234:Preoperative Period; D012372:ROC Curve; D021701:Sentinel Lymph Node Biopsy
chemical_list: D014408:Biomarkers, Tumor