Related Experiment Video
Updated: Aug 19, 2026

Clinical Application of Single-Surgeon, Three-Port, Laparoscopic Resection for Colorectal Cancer with Natural Orifice Specimen Extraction
Published on: March 24, 2023
Operative mortality in colorectal cancer: prospective national study
Paris P Tekkis1, Jan D Poloniecki, Michael R Thompson
1Department of Surgery, St Mark's Hospital, Harrow HA1 3UJ.
Objective:
To develop a mathematical model that will predict the probability of death after surgery for colorectal cancer.
Design:
Descriptive study using routinely collected clinical data.
Data Source:
The database of the Association of Coloproctology of Great Britain and Ireland (ACPGBI), encompassing 8077 patients with a new diagnosis of colorectal cancer in 73 hospitals during a 12 month period.
Statistical Analysis:
A three level hierarchical logistic regression model was used to identify independent predictors of operative mortality. The model was developed on 60% of the patient population and its validity tested on the remaining 40%.
Results:
Overall postoperative mortality was 7.5% (95% confidence interval 6.9% to 8.1%). Independent predictors of death were age, American Society of Anesthesiology (ASA) grade, Dukes's stage, urgency of the operation, and cancer excision. When tested the predictive model showed good discrimination (area under the receiver operating characteristic curve = (0.775) and calibration (comparison of observed with expected mortality across different procedures; Hosmer-Lemeshow statistic = 6.34, 8 df, P = 0.610).
Conclusions:
Clinicians can predict postoperative death by using a simple numerical table derived from the statistical model of the ACPGBI. The model can be used in everyday practice for preoperative counselling of patients and their carers as a part of multidisciplinary care. It may also be used to compare the outcomes between multidisciplinary teams for colorectal cancer.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
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