Journal of cancer research and clinical oncology · 2011
Molecular indicators of non-sentinel node status in breast cancer determined in preoperative biopsies by multiplexed sandwich immunoassays.
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Sauer Georg, Schneiderhan-Marra Nicole, Muche Rainer, Koretz Karin, Kazmaier Cornelia, Kreienberg Rolf, Joos Thomas, Deissler Helmut
Аннотация
PURPOSE: 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.
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.
Предметные рубрики MeSH
AdenocarcinomaAdultAgedAlgorithmsArea Under CurveAxillaBiomarkers, TumorBiopsy, NeedleBreast NeoplasmsCarcinoma, Ductal, BreastCarcinoma, LobularFemaleHumansImmunoassayLogistic ModelsLymph Node ExcisionLymph NodesLymphatic MetastasisMiddle AgedMultivariate AnalysisNeoplasm StagingPredictive Value of TestsPreoperative PeriodROC CurveSentinel Lymph Node Biopsy