Tumor Budding Assessment in Colorectal Carcinoma

Abstract

Tumor budding (TB) is a powerful prognostic factor in colorectal cancer (CRC). An internationally standardized method for its assessment (International Tumor Budding Consensus Conference [ITBCC] method) has been adopted by most CRC pathology protocols. This method requires that TB counts are reported by field area (0.785 mm2) rather than objective lens and a normalization factor is applied for this purpose. However, the validity of this approach is yet to be tested. We sought to validate the ITBCC method with a particular emphasis on normalization as a tool for standardization. In a cohort of 365 stage I-III CRC, both normalized and non-normalized TB were significantly associated with disease-specific survival and recurrence-free survival (P<0.0001). Examining both 0.95 and 0.785 mm2 field areas in a subset of patients (n=200), we found that normalization markedly overcorrects TB counts: Counts obtained in a 0.95 mm2 hotspot field were reduced by an average of 17.5% following normalization compared with only 3.8% when counts were performed in an actual 0.785 mm2 field. This resulted in 45 (11.3%) cases being downgraded using ITBCC grading criteria following normalization, compared with only 5 cases (1.3%, P=0.0007) downgraded when a true 0.785 mm2 field was examined. In summary, the prognostic value of TB was retained regardless of whether TB counts in a 0.95 mm2 field were normalized. Normalization resulted in overcorrecting TB counts with consequent downgrading of most borderline cases. This has implications for risk stratification and adjuvant treatment decisions, and suggests the need to re-evaluate the role of normalization in TB assessment.

The Relationship between Tumor Budding and Tumor Deposits in Patients with Stage III Colorectal Carcinoma

“…The importance of TB reporting has been subsequently confirmed through validation in numerous clinical research studies. Some of the new topics addressed in research papers following the ITBCC include the reproducibility of TB assessment, the development of automated algorithms for TB detection using the latest technologies, and the reevaluation of the ideal cut-off value, whether through a binary classification system or a three-tier classification system, for detecting points significantly affecting overall survival in most of the clinical scenarios [52][53][54][55][56][57][58].…”