Related Experiment Video
Updated: Feb 21, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
A New Prediction Model for Local Recurrence After Curative Rectal Cancer Surgery: Development and Validation as an
Koya Hida1, Ryosuke Okamura, Soo Yeun Park
11 Department of Surgery, Kyoto University Hospital, Kyoto, Japan 2 Department of Surgery, Kyungpook National University Medical Center, Daegu, South Korea.
Background:
Local recurrence is one of the remaining problems in rectal and rectosigmoid cancer, and it is sometimes difficult to treat.
Objective:
This study aimed to explore various factors that are highly related to local recurrence and to develop a new prediction model for local recurrence after curative resection.
Design:
This is a retrospective cohort study SETTINGS:: This study was conducted at 2 academic hospitals in Japan and Korea.
Patients:
A total of 2237 patients with stage I to III rectal and rectosigmoid cancer who underwent a curative operation with a negative circumferential margin were selected.
Interventions:
Surgical treatment was the intervention.
Main Outcome Measures:
Local recurrence was the primary outcome measure.
Results:
A total of 1232 patients were selected, and rectosigmoid cancer with rare local recurrence (2/221) was excluded. A different set of 792 patients with rectal cancer were chosen for validation. Multivariate analysis showed the following factors as significant for local recurrence: poorly differentiated tumor (HR, 11.2; 95% CI, 4.5-28.0), tumor depth (HR, 5.0), lymph node metastasis (HR, 4.1), operative procedure (HR, 3.2), postoperative complications (HR, 2.9), tumor location (HR, 2.6), and CEA level (HR, 2.4); a new prediction score was created by using these factors. A poorly differentiated tumor was assigned 2 points, and all other factors were assigned 1 point each. Patients who scored more than 5 points (n = 21) were judged as "high risk," with a 2-year local recurrence rate of 66.5%. The new predictive model could also separate the patients into different risk groups in the validation set. The high-risk group had higher recurrence rates than medium- and low-risk groups (2-year local recurrence rate: 41%, 15%, and 2.1%).
Limitations:
This study was limited by its retrospective nature and potential for selection bias.
Conclusions:
Seven factors were shown to be significantly correlated with the local recurrence of rectal cancer, and the usefulness of this new prediction model was demonstrated. See Video Abstract at http://links.lww.com/DCR/A429.
More Related Videos
07:13Comparison 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
12:45Robot-assisted Total Mesorectal Excision and Lateral Pelvic Lymph Node Dissection for Locally Advanced Middle-low Rectal Cancer
Published on: February 12, 2022