Related Experiment Video
Updated: Jun 25, 2026
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
A short-term postoperative prediction model for colorectal cancer using comprehensive geriatric assessment
Di Yang1,2, Mengyu Cao2, Shaokang Yang3
1Department of Hepatology, Center of Infectious Diseases and Pathogen Biology, The First Hospital of Jilin University, Changchun, 130021, China.
Background:
Older colorectal cancer (CRC) patients face significant postoperative risks. This study aimed to develop a prediction model to quantify the short-term prognosis of these patients following laparoscopic surgery.
Methods:
This prospective study enrolled patients aged ≥ 60 years undergoing elective laparoscopic radical resection (May 2021-April 2024). The primary outcome was 90-day Major Adverse Postoperative Events (MAPE). A comprehensive geriatric assessment (CGA) was performed to identify independent risk factors.
Results:
MAPE occurred in 23.7% of the derivation cohort and 22.5% of the validation cohort. Multivariable logistic regression identified six independent preoperative predictors: weight loss (OR = 2.20, 95% CI 1.20-4.22), ADL scores (OR = 1.11, 95% CI 1.03-1.20), preoperative BUN (OR = 1.14, 95% CI 1.01-1.29), ASMI (OR = 0.68, 95% CI 0.47-0.98), hypoalbuminemia (OR = 1.33, 95% CI 1.02-1.89), and TNM stage (OR = 1.75, 95% CI 1.18-2.60). The prediction model demonstrated robust discrimination (AUC: derivation 0.802; validation 0.779) and excellent calibration. Decision curve analysis confirmed its clinical utility across a wide range of threshold probabilities.
Conclusions:
This CGA-based tool effectively predicts short-term prognosis, enabling personalized risk stratification and identifying high-risk candidates to guide future perioperative management strategies.
