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Mod Pathol. 2019 Sep 18. doi: 10.1038/s41379-019-0367-9. [Epub ahead of print]

Interobserver variability in upfront dichotomous histopathological assessment of ductal carcinoma in situ of the breast: the DCISion study.

Author information

1
Department of pathology, Cliniques universitaires Saint-Luc Bruxelles, Avenue Hippocrate 10, 1200, Woluwé-Saint-Lambert, Belgium.
2
Department of Pathology, Bakirköy Dr. Sadi Konuk Health Application and Research Center, University of Health Sciences, 34147, Istanbul, Turkey.
3
Département de Biologie et de Pathologie des Tumeurs, Centre George-François Leclerc, 1 Rue Pr. Marion, 21000, Dijon, France.
4
Department of Pathology, CHU de Liège-site Sart Tilman, Avenue de l'Hòpital 1, 4000, Liège, Belgium.
5
Department of Pathology, GZA/ZNA Hospitals, 2610, Wilrijk, Belgium.
6
Department of Pathology, AZ Delta, Westlaan 123, 8800, Roeselare, Belgium.
7
Division of Pathology and Laboratory Medicine, Medical School, The University of Western Australia, Crawley, WA, 6009, Australia.
8
Department of pathology, AZ Klina Brasschaat, Augustijnslei 100, 2930, Brasschaat, Belgium.
9
Department of pathology, University Hospitals Leuven, KU Leuven-University of Leuven, Herestraat 49, 3000, Leuven, Belgium.
10
Department of Imaging and Pathology, Laboratory of Translational Cell & Tissue Research, KU Leuven-University of Leuven, Leuven, Belgium.
11
Department of Pathology, Peter MacCallum Cancer Center and the University of Melbourne, Melbourne, VIC, 3000, Australia.
12
Department of Pathology, University of Cagliari, AOU San Giovanni di Dio, Via Ospedale 54, 09124, Cagliari, Italy.
13
Department of Pathology, Mount Sinai Hospital and Icahn School of Medicine, New York, NY, 10029, USA.
14
Pathan BV, Kleiweg 500, 3045 PM, Rotterdam, The Netherlands.
15
Department of Pathology, Gustave-Roussy Cancer Campus, 114 Rue Edouard-Vaillant, 94805, Villejuif, France.
16
Department of Pathology, Clinique Notre-Dame de Grâce (CNDG), Chaussée de Nivelles 212, 6041, Gosselies, Belgium.
17
Department of pathology, St. Lucas Hospital, Groenebriel 1, 9000, Ghent, Belgium.
18
Surgical Pathology Unit, Department of Pathobiology, Institut Bergonié, F-33076, Bordeaux, France.
19
Department of Medical Sciences, University of Turin, 10126, Torino, Italy.
20
Pathology Unit, FPO-IRCCS, Candiolo Cancer Institute, Candiolo, Italy.
21
Curepath, Rue de Borfilet 12A, 6040, Jumet, Belgium.
22
Department of Laboratory Medicine and Molecular Diagnostics, Sunnybrook Health Sciences Center, University of Toronto, Toronto, Ontario, ON, M4N 3M5, Canada.
23
Department of Pathology, AZ St. Maarten, Liersesteenweg 435, 2800, Mechelen, Belgium.
24
Histopathology, Imaging and Quantification Unit, HistoGeneX, Sint-Bavostraat 78, 2610, Antwerp, Belgium.
25
Department of Pathology, Yale School of Medicine, Yale New Haven Hospital, 310 Cedar Street, New Haven, CT, 06510, USA.
26
The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
27
Department of Pathology and Immunology, Washington University School of Medicine, 660S Euclid Boulevard, St. Louis, MO, 63110, USA.
28
Department of Pathology, Onze-Lieve-Vrouwziekenhuis Aalst, Moorselbaan 164, 9300, Aalst, Belgium.
29
Department of Cellular Pathology, Queen Elizabeth Hospital Birmingham, University of Birmingham, Birmingham, B15 2GW, UK.
30
Department of Pathology, CHU UCL Namur, Site Godinne, Avenue Docteur G. Thérasse 1, 5530, Yvoir, Belgium.
31
Department of Pathology, Erasmus Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
32
Department of Pathology, Ghent University Hospital, C. Heymanslaan 10, 9000, Ghent, Belgium.
33
Pôle de Médicine Diagnostique & Théranostique, INSERM U934, Institut Curie, 26 Rue d'Ulm, 75248, Paris, Cedex 05, France.
34
Department of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
35
2IP IREC Imaging Platform, Institute of Clinical and Experimental Research (IREC), Université catholique de Louvain, Avenue Hippocrate 55, 1200, Brussels, Belgium.
36
Institute of Clinical and Experimental Research (IREC), Université catholique de Louvain, Avenue Hippocrate 55, 1200, Brussels, Belgium.
37
Department of pathology, Cliniques universitaires Saint-Luc Bruxelles, Avenue Hippocrate 10, 1200, Woluwé-Saint-Lambert, Belgium. mieke.vanbockstal@uclouvain.be.
38
Institute of Clinical and Experimental Research (IREC), Université catholique de Louvain, Avenue Hippocrate 55, 1200, Brussels, Belgium. mieke.vanbockstal@uclouvain.be.

Abstract

Histopathological assessment of ductal carcinoma in situ, a nonobligate precursor of invasive breast cancer, is characterized by considerable interobserver variability. Previously, post hoc dichotomization of multicategorical variables was used to determine the "ideal" cutoffs for dichotomous assessment. The present international multicenter study evaluated interobserver variability among 39 pathologists who performed upfront dichotomous evaluation of 149 consecutive ductal carcinomas in situ. All pathologists independently assessed nuclear atypia, necrosis, solid ductal carcinoma in situ architecture, calcifications, stromal architecture, and lobular cancerization in one digital slide per lesion. Stromal inflammation was assessed semiquantitatively. Tumor-infiltrating lymphocytes were quantified as percentages and dichotomously assessed with a cutoff at 50%. Krippendorff's alpha (KA), Cohen's kappa and intraclass correlation coefficient were calculated for the appropriate variables. Lobular cancerization (KA = 0.396), nuclear atypia (KA = 0.422), and stromal architecture (KA = 0.450) showed the highest interobserver variability. Stromal inflammation (KA = 0.564), dichotomously assessed tumor-infiltrating lymphocytes (KA = 0.520), and comedonecrosis (KA = 0.539) showed slightly lower interobserver disagreement. Solid ductal carcinoma in situ architecture (KA = 0.602) and calcifications (KA = 0.676) presented with the lowest interobserver variability. Semiquantitative assessment of stromal inflammation resulted in a slightly higher interobserver concordance than upfront dichotomous tumor-infiltrating lymphocytes assessment (KA = 0.564 versus KA = 0.520). High stromal inflammation corresponded best with dichotomously assessed tumor-infiltrating lymphocytes when the cutoff was set at 10% (kappa = 0.881). Nevertheless, a post hoc tumor-infiltrating lymphocytes cutoff set at 20% resulted in the highest interobserver agreement (KA = 0.669). Despite upfront dichotomous evaluation, the interobserver variability remains considerable and is at most acceptable, although it varies among the different histopathological features. Future studies should investigate its impact on ductal carcinoma in situ prognostication. Forthcoming machine learning algorithms may be useful to tackle this substantial diagnostic challenge.

PMID:
31534203
DOI:
10.1038/s41379-019-0367-9

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