C M Focke1,2, T Decker3, P J van Diest4. 1. Department of Pathology, Dietrich Bonhoeffer Medical Centre, Neubrandenburg, Germany. Cornelia.Focke@web.de. 2. Department of Pathology, University Medical Centre Utrecht, Utrecht, The Netherlands. Cornelia.Focke@web.de. 3. Department of Pathology, Dietrich Bonhoeffer Medical Centre, Neubrandenburg, Germany. 4. Department of Pathology, University Medical Centre Utrecht, Utrecht, The Netherlands.
Abstract
BACKGROUND: Assessing prognostic and predictive factors like the Ki67 labelling index (Ki67-LI) in breast cancer core needle biopsies (CNB) may be hampered by undersampling. Our aim was to arrive at a representative assessment of Ki67-LI in CNB of luminal breast cancers by defining optimal cutoffs and establishing the minimum CNB volume needed for highest concordance of Ki67-LI between CNB and subsequent surgical excision biopsy (SEB). METHODS: We assessed the Ki67-LI in CNB and subsequent SEB of 170 luminal breast cancers according to two counting methods recommended by the International Ki67 in Breast Cancer Working Group and applied the cutoffs to distinguish low and high proliferation given by the St Gallen 2013 and 2015 consensus, respectively. We then compared CNB volume characteristics for cases with concordant and discordant Ki67-LI between CNB versus SEB. RESULTS: Highest concordance (75%, κ = 0.44) between CNB and SEB was achieved using the method that assesses the average tumor Ki67-LI and a cutoff of 20%. No significant differences were found between cases with concordant and discordant Ki67-LI in CNB versus SEB for number of biopsy cores, total core length, tumor tissue length, or total CNB or tumor tissue area size in the CNB for two various cutoffs. CONCLUSIONS: A concordance of 75% between CNB and SEB can be achieved for the Ki67-LI using a method assessing average Ki67-LI at the threshold of 20%. Increasing CNB volume did not result in improved agreement rates, indicating that reliability of Ki67 levels in CNB of luminal breast cancers is unaffected by CNB volume.
BACKGROUND: Assessing prognostic and predictive factors like the Ki67 labelling index (Ki67-LI) in breast cancer core needle biopsies (CNB) may be hampered by undersampling. Our aim was to arrive at a representative assessment of Ki67-LI in CNB of luminal breast cancers by defining optimal cutoffs and establishing the minimum CNB volume needed for highest concordance of Ki67-LI between CNB and subsequent surgical excision biopsy (SEB). METHODS: We assessed the Ki67-LI in CNB and subsequent SEB of 170 luminal breast cancers according to two counting methods recommended by the International Ki67 in Breast Cancer Working Group and applied the cutoffs to distinguish low and high proliferation given by the St Gallen 2013 and 2015 consensus, respectively. We then compared CNB volume characteristics for cases with concordant and discordant Ki67-LI between CNB versus SEB. RESULTS: Highest concordance (75%, κ = 0.44) between CNB and SEB was achieved using the method that assesses the average tumor Ki67-LI and a cutoff of 20%. No significant differences were found between cases with concordant and discordant Ki67-LI in CNB versus SEB for number of biopsy cores, total core length, tumor tissue length, or total CNB or tumor tissue area size in the CNB for two various cutoffs. CONCLUSIONS: A concordance of 75% between CNB and SEB can be achieved for the Ki67-LI using a method assessing average Ki67-LI at the threshold of 20%. Increasing CNB volume did not result in improved agreement rates, indicating that reliability of Ki67 levels in CNB of luminal breast cancers is unaffected by CNB volume.
Authors: Kristina A Tendl-Schulz; Fabian Rössler; Philipp Wimmer; Ulrike M Heber; Martina Mittlböck; Nicolas Kozakowski; Katja Pinker; Rupert Bartsch; Peter Dubsky; Florian Fitzal; Martin Filipits; Fanny Carolina Eckel; Eva-Maria Langthaler; Günther Steger; Michael Gnant; Christian F Singer; Thomas H Helbich; Zsuzsanna Bago-Horvath Journal: Virchows Arch Date: 2020-05-07 Impact factor: 4.064
Authors: Balazs Acs; Samuel C Y Leung; Kelley M Kidwell; Indu Arun; Renaldas Augulis; Sunil S Badve; Yalai Bai; Anita L Bane; John M S Bartlett; Jane Bayani; Gilbert Bigras; Annika Blank; Henk Buikema; Martin C Chang; Robin L Dietz; Andrew Dodson; Susan Fineberg; Cornelia M Focke; Dongxia Gao; Allen M Gown; Carolina Gutierrez; Johan Hartman; Zuzana Kos; Anne-Vibeke Lænkholm; Arvydas Laurinavicius; Richard M Levenson; Rustin Mahboubi-Ardakani; Mauro G Mastropasqua; Sharon Nofech-Mozes; C Kent Osborne; Frédérique M Penault-Llorca; Tammy Piper; Mary Anne Quintayo; Tilman T Rau; Stefan Reinhard; Stephanie Robertson; Roberto Salgado; Tomoharu Sugie; Bert van der Vegt; Giuseppe Viale; Lila A Zabaglo; Daniel F Hayes; Mitch Dowsett; Torsten O Nielsen; David L Rimm Journal: Mod Pathol Date: 2022-06-21 Impact factor: 8.209
Authors: Ferdia A Gallagher; Ramona Woitek; Mary A McLean; Andrew B Gill; Raquel Manzano Garcia; Elena Provenzano; Frank Riemer; Joshua Kaggie; Anita Chhabra; Stephan Ursprung; James T Grist; Charlie J Daniels; Fulvio Zaccagna; Marie-Christine Laurent; Matthew Locke; Sarah Hilborne; Amy Frary; Turid Torheim; Chris Boursnell; Amy Schiller; Ilse Patterson; Rhys Slough; Bruno Carmo; Justine Kane; Heather Biggs; Emma Harrison; Surrin S Deen; Andrew Patterson; Titus Lanz; Zoya Kingsbury; Mark Ross; Bristi Basu; Richard Baird; David J Lomas; Evis Sala; James Wason; Oscar M Rueda; Suet-Feung Chin; Ian B Wilkinson; Martin J Graves; Jean E Abraham; Fiona J Gilbert; Carlos Caldas; Kevin M Brindle Journal: Proc Natl Acad Sci U S A Date: 2020-01-21 Impact factor: 11.205