Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 9, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

Worst Histology-Based Risk Stratification for Lymph Node Metastasis in Patients With T1b Colorectal Cancer: A

Satomi Shibata1, Shin-Ichiro Horiguchi2, Koichi Koizumi1

  • 1Department of Gastroenterology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital Tokyo Japan.

DEN Open
|June 8, 2026
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Case of Colon Cancer-Induced Hemophagocytic Lymphohistiocytosis with Lymphangitic Carcinomatosis.

Surgical case reports·2026
Same author

[Clinical outcomes of idecabtagene vicleucel therapy for relapsed/refractory multiple myeloma: a single-center retrospective analysis].

[Rinsho ketsueki] The Japanese journal of clinical hematology·2026
Same author

Distinct clinical course and poor outcomes of small bowel bleeding in acute hematochezia: a nationwide multicenter study.

Scientific reports·2026
Same author

Successful Preservation of the Penis After en Bloc Resection of Locally Recurrent Rectal Cancer Involving the Left Crus of the Corpus Cavernosum and Corpus Spongiosum.

IJU case reports·2026
Same author

A kappa opioid receptor agonist, difelikefalin, improves acute kidney injury in experimental sepsis models.

PloS one·2026
Same author

Chronic neutrophilic leukemia with transformation to B-lymphoblastic leukemia.

Leukemia research·2026

A new worst histology (WH) approach improves risk stratification for lymph node metastasis in T1b colorectal cancer (CRC). This method helps identify low-risk patients, potentially avoiding unnecessary surgeries.

Area of Science:

  • Oncology
  • Pathology
  • Surgical Oncology

Background:

  • Histological subtype is crucial for risk stratifying lymph node metastasis (LNM) in T1 colorectal cancer (CRC).
  • Conventional assessment may overlook poorly differentiated components in T1b CRC, impacting accurate risk stratification.
  • A reproducible worst histology (WH) approach is needed for T1b CRC.

Purpose of the Study:

  • To develop and validate a T1b-specific risk stratification framework using a reproducible worst histology (WH) approach.
  • To compare the performance of WH-based methods against dominant histology (DH) and conventional criteria for predicting LNM in T1b CRC.

Main Methods:

  • Retrospective analysis of 488 patients with pT1b CRC who underwent surgical resection and lymph node dissection.
  • Histological evaluation using dominant histology (DH), worst histology (WH), and WH focusing on poorly differentiated adenocarcinoma (WH-por).
Keywords:
T1 colorectal cancerlymph node metastasispoorly differentiated adenocarcinomarisk stratificationworst histology

More Related Videos

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

Related Experiment Videos

Last Updated: Jun 9, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

  • Identification of independent risk factors for LNM for each approach and comparison with Japanese Society for Cancer of the Colon and Rectum (JSCCR) criteria.
  • Main Results:

    • The WH-por approach showed better LNM risk identification in T1b colon cancer compared to DH and WH.
    • The WH approach performed better than WH-por in T1b rectal cancer.
    • Low-risk subgroup in colon cancer had a 1.7% LNM rate (vs. 4.1% JSCCR); in rectal cancer, it was 8.0% (vs. 8.6% JSCCR).

    Conclusions:

    • A WH-based approach enhances LNM risk stratification in T1b CRC.
    • This framework aids in identifying selected low-risk patients, supporting individualized treatment decisions.
    • It may help refine the necessity of additional surgical resection for T1b CRC patients.