Assessment of Tumor Regression of Esophageal Adenocarcinomas After Neoadjuvant Chemotherapy

Abstract

Histopathologic determination of tumor regression provides important prognostic information for locally advanced gastroesophageal carcinomas after neoadjuvant treatment. Regression grading systems mostly refer to the amount of therapy-induced fibrosis in relation to residual tumor or the estimated percentage of residual tumor in relation to the former tumor site. Although these methods are generally accepted, currently there is no common standard for reporting tumor regression in gastroesophageal cancers. We compared the application of these 2 major principles for assessment of tumor regression: hematoxylin and eosin-stained slides from 89 resection specimens of esophageal adenocarcinomas following neoadjuvant chemotherapy were independently reviewed by 3 pathologists from different institutions. Tumor regression was determined by the 5-tiered Mandard system (fibrosis/tumor relation) and the 4-tiered Becker system (residual tumor in %). Interobserver agreement for the Becker system showed better weighted κ values compared with the Mandard system (0.78 vs. 0.62). Evaluation of the whole embedded tumor site showed improved results (Becker: 0.83; Mandard: 0.73) as compared with only 1 representative slide (Becker: 0.68; Mandard: 0.71). Modification into simplified 3-tiered systems showed comparable interobserver agreement but better prognostic stratification for both systems (log rank Becker: P=0.015; Mandard P=0.03), with independent prognostic impact for overall survival (modified Becker: P=0.011, hazard ratio=3.07; modified Mandard: P=0.023, hazard ratio=2.72). In conclusion, both systems provide substantial to excellent interobserver agreement for estimation of tumor regression after neoadjuvant chemotherapy in esophageal adenocarcinomas. A simple 3-tiered system with the estimation of residual tumor in % (complete regression/1% to 50% residual tumor/>50% residual tumor) maintains the highest reproducibility and prognostic value.

Predicting Pathologic Response of Esophageal Cancer to Neoadjuvant Chemotherapy: The Implications of Metabolic Nodal Response for Personalized Therapy

“…The Mandard TRG has subsequently been validated for esophageal adenocarcinoma (41) although several other classifications have been described (42); all, however, remain relatively subjective and are tempered by potential interobserver variability and intratumoral sampling bias (43). Ultimately, the Mandard TRG is most frequently used and provides the basis for optimal prediction of survival (28,30). An additional limitation of this study is its retrospective design over a long time period, which although necessary to generate a sufficient cohort resulted in a change of PET/CT scanner, and the availability of additional metrics for the more recent scanner alone.…”

“…pTR was defined as Mandard Tumor Regression Grade (TRG) of 3 or less, after dedicated review by a consultant cellular pathologist (27). The Mandard TRG was used in preference to alternative TRGs, being the most frequently used TRG for esophageal cancer (28), with optimal prediction of survival (29,30).…”

The Incremental Value of Subjective and Quantitative Assessment of 18F-FDG PET for the Prediction of Pathologic Complete Response to Preoperative Chemoradiotherapy in Esophageal Cancer

“…PathCR (i.e., TRG 1) as opposed to any grade of residual carcinoma (i.e., TRGs 2-4) was considered the reference standard. Another commonly made distinction between TRGs 1 and 2 (i.e., 0%-10% residual carcinoma) and TRGs 3 and 4 (i.e., $11% residual carcinoma) was not made, because this distinction is rather arbitrary in terms of interpathologist reproducibility and overall survival (2,4,23), and the potential clinical consequences of such a distinction are unclear.…”

Histopathological markers of treatment response and recurrence risk in ovarian cancers and borderline tumors

“…Previous studies found intratumoral heterogeneity for allelic loss [96, 97] and gene amplification in breast cancer [98, 99]. Two recent reports described large variations in the mutational spectrum of triple negative breast cancer assessed by high-throughput RNA sequencing and deep re-sequencing of more than 2.400 somatic mutations [8, 9]. These studies applied sequencing in great depth of one single sample per tumor.…”