Tumor budding score based on 10 high-power fields is a promising basis for a standardized prognostic scoring system in stage II colorectal cancer

Tumor budding is recognized by the World Health Organization as an additional prognostic factor in colorectal cancer but remains unreported in diagnostic work due to the absence of a standardized scoring method. This study aims to assess the most prognostic and reproducible scoring systems for tumor budding in colorectal cancer. Tumor budding on pancytokeratin-stained whole tissue sections from 105 well-characterized stage II patients was scored by 3 observers using 7 methods: lime, Nakamura, Ueno, Wang (conventional and rapid method), densest high-power field, and 10 densest high-power fields. The predictive value for clinicopathologic features, the prognostic significance, and interobserver variability of each scoring method was analyzed. Pancytokeratin staining allowed accurate evaluation of tumor buds. Interobserver agreement for 3 observers was excellent for densest high-power field (intraclass correlation coefficient, 0.83) and 10 densest high-power fields (intraclass correlation coefficient, 0.91). Agreement was moderate to substantial for the conventional Wang method (kappa = 0.46-0.62) and moderate for the rapid method (kappa = 0.46-0.58). For Nakamura, moderate agreement (kappa = 0.41-0.52) was reached, whereas concordance was fair to moderate for Ueno (kappa = 0.39-0.56) and Has (kappa = 0.29-0.51). The Hase, Ueno, densest high-power field, and 10 densest high-power field methods identified a significant association of tumor budding with tumor border configuration. In multivariate analysis, only tumor budding as evaluated in densest high-power field and 10 densest high-power fields had significant prognostic effects on patient survival (P < .01), with high prognostic accuracy over the full 10-year follow-up. Scoring tumor buds in 10 densest high-power fields is a promising method to identify stage II patients at high risk for recurrence in daily diagnostics; it is highly reproducible, accounts for heterogeneity, and has a strong predictive value for adverse outcome. (C) 2013 Elsevier Inc. All rights reserved.