Related Experiment Video
Updated: May 21, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Failure patterns correlate with the tumor response after preoperative chemoradiotherapy for locally advanced rectal
Seok-Byung Lim1, Chang Sik Yu, Yong Sang Hong
1Department of Surgery, University of Ulsan College of Medicine and Asan Medical Center, Seoul, Korea.
Background And Objectives:
To determine whether the patterns of failure are correlated with the degree of response to preoperative chemoradiotherapy (CRT) and to evaluate outcomes after recurrence in rectal cancer patients who underwent CRT followed by resection.
Methods:
Response to CRT was evaluated according to tumor regression grade (TRG), with 581 patients categorized into two groups, a good response (GR, TRG 3/4, n = 224) and a poor response (PR, TRG 1/2, n = 357) group.
Results:
At a mean follow-up of 61 months, the 5-year overall (88.2% vs. 71.3%, P < 0.001) and disease-free (86.7% vs. 63.6%, P < 0.001) survival rates were higher in the GR group. In patients with recurrence, time to recurrence was shorter (13.5 months vs. 18.7 months, P = 0.01), and the cumulative 2-year recurrence rates (92.9% vs. 73.4%, P = 0.024) was higher in the GR group. Rates of local (1.3% vs. 9.5% P < 0.001) and systemic (11.6% vs. 27.2%, P < 0.001) recurrence were significantly lower in the GR group, as were rates of pulmonary (3.6% vs. 15.1%, P < 0.001) and systemic lymph node (1.3% vs. 5.9%, P = 0.009) recurrences. The 5-year overall survival rates after recurrence were similar (GR: 23.7% vs. PR: 16.0%, P = 0.911).
Conclusions:
More than one-third of patients with locally advanced rectal cancer showed good response to CRT, with improved local and systemic recurrence rates, especially low rates of pulmonary and systemic lymph node recurrence. Recurrence occurred earlier in the GR than the PR group, and oncologic outcomes after recurrence did not differ between the two groups.
More Related Videos
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
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