A novel integrated model combining CT body composition and inflammation-nutrition indices for predicting the complications of obstructive colorectal cancer patients
10.3760/cma.j.cn112139-20250324-00152
- VernacularTitle:结合CT机体组成成分和炎症-营养指标的预测模型在梗阻性结直肠癌患者并发症预测中的应用
- Author:
Zhenying XU
1
;
Wentao XIE
1
;
Yuan GAO
1
;
Wenzhi WU
1
;
Mingyu YANG
1
;
Tianxu MA
1
;
Hanyu YANG
1
;
Yun LU
1
Author Information
1. 青岛大学附属医院胃肠外科，青岛266000
- Publication Type:Journal Article
- Keywords:
Colorectal neoplasms;
Postoperative complications;
Inflammatory and nutritional indicators;
Predictors;
Nomogram
- From:
Chinese Journal of Surgery
2025;63(10):911-919
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the impact of body composition and inflammatory nutritional indicators on postoperative complications in patients with obstructive colorectal cancer,and to develop and validate a nomogram model.Methods:This is a retrospective case series study. The clinical data of 293 patients with obstructive colorectal cancer who were treated at the Department of Gastrointestinal Surgery,the Affiliated Hospital of Qingdao University,between January 2016 and January 2024,were retrospectively collected. The cohort included 182 males and 111 females,aged (65.0±12.1) years (range: 18 to 80 years). The dataset was randomly divided into a training group ( n=196) and a validation group ( n=97) with a 7∶3 ratio. Independent sample t test and multivariate logistic regression analysis were employed to identify independent risk factors associated with postoperative complications in patients with obstructive colorectal cancer. A preoperative nomogram model was subsequently developed for predicting postoperative complications,which was further validated using a validation cohort. Results:The training group comprised 119 males and 77 females,with 68 cases experiencing postoperative complications and 128 cases without complications. The validation group included 63 males and 34 females,with 30 cases experiencing postoperative complications and 67 cases without complications.Univariate analysis and multivariate analysis revealed that low skeletal muscle index ( OR=0.867,95% CI: 0.795 to 0.947),high visceral fat index ( OR=1.058,95% CI: 1.028 to 1.089),high systemic immune inflammation index ( OR=1.002, 95% CI: 1.000 to 1.003), low prognostic nutritional index ( OR=0.847,95% CI: 0.782 to 0.917),and preoperative anemia ( OR=2.714,95% CI: 1.161 to 6.344) were independent risk factors for postoperative complications (all P<0.05). A nomogram prediction model based on these five indicators was established. The area under the receiver operating characteristic (ROC) curve for the prediction model was 0.878 (95% CI: 0.829 to 0.928) in the training group and 0.849 (95% CI:0.767 to 0.930) in the validation group. Conclusions:The preoperative nomogram model,which incorporates inflammatory and nutritional indicators,demonstrates a good accuracy in predicting postoperative complications for patients with obstructive colorectal cancer. This model can effectively assist in guiding treatment decisions.
