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

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.

• Authors: Hélène Dano, Serdar Altinay, Laurent Arnould, Noella Bletard, Cecile Colpaert, Franceska Dedeurwaerdere, Benjamin Dessauvagie, Valérie Duwel, Giuseppe Floris, Stephen Fox, Clara Gerosa, Shabnam Jaffer, Eline Kurpershoek, Magali Lacroix-Triki, Andoni Laka, Kathleen Lambein, Gaëtan Marie MacGrogan, Caterina Marchió, Dolores Martin Martinez, Sharon Nofech-Mozes, Dieter Peeters, Alberto Ravarino, Emily Reisenbichler, Erika Resetkova, Souzan Sanati, Anne-Marie Schelfhout, Vera Schelfhout, Abeer M Shaaban, Renata Sinke, Claudia Maria Stanciu-Pop, Claudia Stobbe, Carolien H M van Deurzen, Koen Van de Vijver, Anne-Sophie Van Rompuy, Stephanie Verschuere, Anne Vincent-Salomon, Hannah Wen, Caroline Bouzin, Christine Galant, Mieke R Van Bockstal
• Journal: Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc (Mod Pathol) Vol. 33 Issue 3 Pg. 354-366 (03 2020) ISSN: 1530-0285 [Electronic] United States
• PMID: 31534203 (Publication Type: Journal Article, Multicenter Study, Research Support, Non-U.S. Gov't)

Topics

• Biopsy
• Breast Neoplasms (pathology, surgery)
• Calcinosis (pathology)
• Carcinoma, Intraductal, Noninfiltrating (pathology, surgery)
• Cell Nucleus (pathology)
• Female
• Humans
• Lymphocytes, Tumor-Infiltrating (pathology)
• Necrosis
• Observer Variation
• Pathologists
• Predictive Value of Tests
• Prognosis
• Reproducibility of Results
• Risk Assessment
• Risk Factors