Ingrid van den Hoven1, Gert Kuijt1, Rudi Roumen1,2, Adri Voogd2,3, Ewout W Steyerberg4, Yvonne Vergouwe4. 1. Department of Surgery, Máxima Medical Center, Veldhoven, The Netherlands. 2. Maastricht University Medical Center, GROW-school for Oncology and Developmental Biology, Maastricht, The Netherlands. 3. Department of Research, Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands. 4. Department of Public Health, Erasmus Medical Center, Rotterdam, The Netherlands.
Abstract
BACKGROUND AND OBJECTIVES: This study was conducted to evaluate the performance of available tools predicting non-sentinel lymph node (non-SLN) status in women with SLN positive breast cancer and to see if they can be safely used in everyday clinical practice. METHODS: Data of 220 women with breast cancer who underwent a SLN biopsy at the Máxima Medical Centre between 2000-2008 were analysed. Tools evaluated were: the models from Memorial Sloan Kettering Cancer Centre, Stanford, Mayo, Cambridge, Gur, and MOU, and the scores from Saidi, Tenon, and MDA. Model performance was assessed using calibration, discrimination and Nagelkerke's explained variation. RESULTS: The MSKCC nomogram showed best overall performance with best discrimination (AUC 0.69), second best calibration, and highest explained variation (31%). The 10% low risk threshold led to defining only 22% (38/176) of the women as being low risk while in fact 66% (116/176) were non-SLN negative. The false negative rate was 13% (5/38). CONCLUSIONS: Current models for predicting non-SLN metastases in SLN positive breast cancer are not yet ready for implementation in general practice. Further research efforts should improve model performance in selecting patients or perhaps find a role in support in the paradigm shift to a "treat none unless" approach.
BACKGROUND AND OBJECTIVES: This study was conducted to evaluate the performance of available tools predicting non-sentinel lymph node (non-SLN) status in women with SLN positive breast cancer and to see if they can be safely used in everyday clinical practice. METHODS: Data of 220 women with breast cancer who underwent a SLN biopsy at the Máxima Medical Centre between 2000-2008 were analysed. Tools evaluated were: the models from Memorial Sloan Kettering Cancer Centre, Stanford, Mayo, Cambridge, Gur, and MOU, and the scores from Saidi, Tenon, and MDA. Model performance was assessed using calibration, discrimination and Nagelkerke's explained variation. RESULTS: The MSKCC nomogram showed best overall performance with best discrimination (AUC 0.69), second best calibration, and highest explained variation (31%). The 10% low risk threshold led to defining only 22% (38/176) of the women as being low risk while in fact 66% (116/176) were non-SLN negative. The false negative rate was 13% (5/38). CONCLUSIONS: Current models for predicting non-SLNmetastases in SLN positive breast cancer are not yet ready for implementation in general practice. Further research efforts should improve model performance in selecting patients or perhaps find a role in support in the paradigm shift to a "treat none unless" approach.
Authors: Matthew S Katz; Linda McCall; Karla Ballman; Reshma Jagsi; Bruce G Haffty; Armando E Giuliano Journal: Breast Cancer Res Treat Date: 2020-02-10 Impact factor: 4.872
Authors: Franco Di Filippo; Simona Di Filippo; Anna Maria Ferrari; Raffaele Antonetti; Alessandro Battaglia; Francesca Becherini; Laia Bernet; Renzo Boldorini; Catherine Bouteille; Simonetta Buglioni; Paolo Burelli; Rafael Cano; Vincenzo Canzonieri; Pierluigi Chiodera; Alfredo Cirilli; Luigi Coppola; Stefano Drago; Luca Di Tommaso; Privato Fenaroli; Roberto Franchini; Andrea Gianatti; Diana Giannarelli; Carmela Giardina; Florence Godey; Massimo M Grassi; Giuseppe B Grassi; Siobhan Laws; Samuele Massarut; Giuseppe Naccarato; Maria Iole Natalicchio; Sergio Orefice; Fabrizio Palmieri; Tiziana Perin; Manuela Roncella; Massimo G Roncalli; Antonio Rulli; Angelo Sidoni; Corrado Tinterri; Maria C Truglia; Isabella Sperduti Journal: J Exp Clin Cancer Res Date: 2016-12-08
Authors: N Maeseele; J Faes; T Van de Putte; J Vlasselaer; E de Jonge; J C Schobbens; K Deraedt; G Debrock; G Van de Putte Journal: Facts Views Vis Obgyn Date: 2017-03