Literature DB >> 24418853

Site-specific tumor grading system in colorectal cancer: multicenter pathologic review of the value of quantifying poorly differentiated clusters.

Hideki Ueno1, Kazuo Hase, Yojiro Hashiguchi, Hideyuki Shimazaki, Masafumi Tanaka, Ohki Miyake, Tadahiko Masaki, Yoshifumi Shimada, Yusuke Kinugasa, Yoshiyuki Mori, Mitsuo Kishimoto, Shingo Kameoka, Yu Sato, Keiji Matsuda, Koichi Nakadoi, Eiji Shinto, Takahiro Nakamura, Kenichi Sugihara.   

Abstract

The study aimed to determine the value of a novel site-specific grading system based on quantifying poorly differentiated clusters (PDC; Grade(PDC)) in colorectal cancer (CRC). A multicenter pathologic review involving 12 institutions was performed on 3243 CRC cases (stage I, 583; II, 1331; III, 1329). Cancer clusters of ≥5 cancer cells and lacking a gland-like structure (PDCs) were counted under a ×20 objective lens in a field containing the maximum clusters. Tumors with <5, 5 to 9, and ≥10 PDCs were classified as grades G1, G2, and G3, respectively. According to Grade(PDC), 1594, 1005, and 644 tumors were classified as G1, G2, and G3 and had 5-year recurrence-free survival rates of 91.6%, 75.4%, and 59.6%, respectively (P<0.0001). Multivariate analysis showed that Grade exerted an influence on prognostic outcome independently of TNM staging; approximately 20% and 46% of stage I and II patients, respectively, were selected by Grade(PDC) as a population whose survival estimate was comparable to or even worse than that of stage III patients. Grade(PDC) surpassed TNM staging in the ability to stratify patients by recurrence-free survival (Akaike information criterion, 2915.6 vs. 2994.0) and had a higher prognostic value than American Joint Committee on Cancer (AJCC) grading (Grade(AJCC)) at all stages. Regarding judgment reproducibility of grading tumors, weighted κ among the 12 institutions was 0.40 for Grade(AJCC) and 0.52 for Grade(PDC). Grade(PDC) has a robust prognostic power and promises to be of sufficient clinical value to merit implementation as a site-specific grading system in CRC.

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Year:  2014        PMID: 24418853     DOI: 10.1097/PAS.0000000000000113

Source DB:  PubMed          Journal:  Am J Surg Pathol        ISSN: 0147-5185            Impact factor:   6.394


  31 in total

1.  Poorly Differentiated Clusters Predict Colon Cancer Recurrence: An In-Depth Comparative Analysis of Invasive-Front Prognostic Markers.

Authors:  Tsuyoshi Konishi; Yoshifumi Shimada; Lik Hang Lee; Marcela S Cavalcanti; Meier Hsu; Jesse Joshua Smith; Garrett M Nash; Larissa K Temple; José G Guillem; Philip B Paty; Julio Garcia-Aguilar; Efsevia Vakiani; Mithat Gonen; Jinru Shia; Martin R Weiser
Journal:  Am J Surg Pathol       Date:  2018-06       Impact factor: 6.394

2.  Prognostic significance of histological categorization of desmoplastic reaction in colorectal liver metastases.

Authors:  Tadakazu Ao; Yoshiki Kajiwara; Keisuke Yonemura; Eiji Shinto; Satsuki Mochizuki; Koichi Okamoto; Suefumi Aosasa; Hideki Ueno
Journal:  Virchows Arch       Date:  2019-05-10       Impact factor: 4.064

3.  Poorly differentiated clusters (PDCs) as a novel histological predictor of nodal metastases in pT1 colorectal cancer.

Authors:  Valeria Barresi; Giovanni Branca; Antonio Ieni; Luca Reggiani Bonetti; Luigi Baron; Stefania Mondello; Giovanni Tuccari
Journal:  Virchows Arch       Date:  2014-04-27       Impact factor: 4.064

Review 4.  Unraveling tumor grading and genomic landscape in lung neuroendocrine tumors.

Authors:  Giuseppe Pelosi; Mauro Papotti; Guido Rindi; Aldo Scarpa
Journal:  Endocr Pathol       Date:  2014-06       Impact factor: 3.943

5.  Clinical Calculator Based on Molecular and Clinicopathologic Characteristics Predicts Recurrence Following Resection of Stage I-III Colon Cancer.

Authors:  Martin R Weiser; Meier Hsu; Philip S Bauer; William C Chapman; Iván A González; Deyali Chatterjee; Deepak Lingam; Matthew G Mutch; Ajaratu Keshinro; Jinru Shia; Efsevia Vakiani; Tsuyoshi Konishi; Yoshifumi Shimada; Zsofia Stadler; Neil H Segal; Andrea Cercek; Leonard Saltz; Rona Yaeger; Anna Varghese; Maria Widmar; Iris H Wei; Emmanouil P Pappou; J Joshua Smith; Garrett Nash; Philip Paty; Julio Garcia-Aguilar; Mithat Gonen
Journal:  J Clin Oncol       Date:  2021-01-13       Impact factor: 44.544

6.  Colon Cancer Grading Using Infrared Spectroscopic Imaging-Based Deep Learning.

Authors:  Saumya Tiwari; Kianoush Falahkheirkhah; Georgina Cheng; Rohit Bhargava
Journal:  Appl Spectrosc       Date:  2022-03-25       Impact factor: 3.588

Review 7.  Prognostic stratification of colorectal cancer patients: current perspectives.

Authors:  Nora I Schneider; Cord Langner
Journal:  Cancer Manag Res       Date:  2014-07-02       Impact factor: 3.989

8.  Poorly differentiated clusters with larger extents have a greater impact on survival: a semi-quantitative pathological evaluation for 239 patients with non-mucinous pT2-3 colorectal carcinoma.

Authors:  Osamu Kinoshita; Mitsuo Kishimoto; Yasutoshi Murayama; Satoru Yasukawa; Eiichi Konishi; Eigo Otsuji; Akio Yanagisawa
Journal:  World J Surg Oncol       Date:  2015-04-08       Impact factor: 2.754

9.  Prognostic value of poorly differentiated clusters in invasive breast cancer.

Authors:  Ying Sun; Fenli Liang; Wei Cao; Kai Wang; Jianjun He; Hongyan Wang; Yili Wang
Journal:  World J Surg Oncol       Date:  2014-10-12       Impact factor: 2.754

10.  Prognostic impact of histological categorisation of epithelial-mesenchymal transition in colorectal cancer.

Authors:  H Ueno; E Shinto; Y Kajiwara; S Fukazawa; H Shimazaki; J Yamamoto; K Hase
Journal:  Br J Cancer       Date:  2014-09-23       Impact factor: 7.640

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