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Background <p>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.</p> Methods <p>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.</p> Results <p>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.</p> Conclusions <p>This CGA-based tool effectively predicts short-term prognosis, enabling personalized risk stratification and identifying high-risk candidates to guide future perioperative management strategies.</p> Graphical abstract <p></p>

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A short-term postoperative prediction model for colorectal cancer using comprehensive geriatric assessment

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月24日

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  • Di Yang,
  • Mengyu Cao,
  • Shaokang Yang,
  • Yujia Chen,
  • Qinglong Jin,
  • Jiyan Leng

摘要

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.

Graphical abstract